diff --git a/Gemfile b/Gemfile
index 8c0bb82a5..dfcdb3e30 100644
--- a/Gemfile
+++ b/Gemfile
@@ -195,10 +195,10 @@ gem 'reverse_markdown'
gem 'iso-639'
gem 'ruby-openai'
-gem 'ai-agents', '>= 0.9.1'
+gem 'ai-agents', '>= 0.10.0'
# TODO: Move this gem as a dependency of ai-agents
-gem 'ruby_llm', '>= 1.8.2'
+gem 'ruby_llm', '>= 1.14.1'
gem 'ruby_llm-schema'
gem 'cld3', '~> 3.7'
diff --git a/Gemfile.lock b/Gemfile.lock
index bd21b7a36..15d9b2614 100644
--- a/Gemfile.lock
+++ b/Gemfile.lock
@@ -126,8 +126,8 @@ GEM
jbuilder (~> 2)
rails (>= 4.2, < 7.2)
selectize-rails (~> 0.6)
- ai-agents (0.9.1)
- ruby_llm (~> 1.9.1)
+ ai-agents (0.10.0)
+ ruby_llm (~> 1.14)
annotaterb (4.20.0)
activerecord (>= 6.0.0)
activesupport (>= 6.0.0)
@@ -307,8 +307,8 @@ GEM
faraday-mashify (1.0.0)
faraday (~> 2.0)
hashie
- faraday-multipart (1.0.4)
- multipart-post (~> 2)
+ faraday-multipart (1.2.0)
+ multipart-post (~> 2.0)
faraday-net_http (3.4.2)
net-http (~> 0.5)
faraday-net_http_persistent (2.1.0)
@@ -466,7 +466,7 @@ GEM
rails-dom-testing (>= 1, < 3)
railties (>= 4.2.0)
thor (>= 0.14, < 2.0)
- json (2.19.2)
+ json (2.19.5)
json_refs (0.1.8)
hana
json_schemer (0.2.24)
@@ -835,17 +835,17 @@ GEM
ruby2ruby (2.5.0)
ruby_parser (~> 3.1)
sexp_processor (~> 4.6)
- ruby_llm (1.9.2)
+ ruby_llm (1.15.0)
base64
event_stream_parser (~> 1)
faraday (>= 1.10.0)
faraday-multipart (>= 1)
faraday-net_http (>= 1)
faraday-retry (>= 1)
- marcel (~> 1.0)
- ruby_llm-schema (~> 0.2.1)
+ marcel (~> 1)
+ ruby_llm-schema (~> 0)
zeitwerk (~> 2)
- ruby_llm-schema (0.2.5)
+ ruby_llm-schema (0.3.0)
ruby_parser (3.20.0)
sexp_processor (~> 4.16)
sass (3.7.4)
@@ -1019,7 +1019,7 @@ GEM
working_hours (1.4.1)
activesupport (>= 3.2)
tzinfo
- zeitwerk (2.7.4)
+ zeitwerk (2.7.5)
PLATFORMS
arm64-darwin-20
@@ -1039,7 +1039,7 @@ DEPENDENCIES
administrate (>= 0.20.1)
administrate-field-active_storage (>= 1.0.3)
administrate-field-belongs_to_search (>= 0.9.0)
- ai-agents (>= 0.9.1)
+ ai-agents (>= 0.10.0)
annotaterb
attr_extras
audited (~> 5.4, >= 5.4.1)
@@ -1144,7 +1144,7 @@ DEPENDENCIES
rubocop-rails
rubocop-rspec
ruby-openai
- ruby_llm (>= 1.8.2)
+ ruby_llm (>= 1.14.1)
ruby_llm-schema
scout_apm
scss_lint
diff --git a/config/llm_models.json b/config/llm_models.json
index e2fe0e938..00c2038e5 100644
--- a/config/llm_models.json
+++ b/config/llm_models.json
@@ -4,7 +4,7 @@
"name": "Claude Haiku 3.5",
"provider": "anthropic",
"family": "claude-haiku",
- "created_at": "2024-10-22 00:00:00 +0530",
+ "created_at": "2024-10-22 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 8192,
"knowledge_cutoff": "2024-07-31",
@@ -27,7 +27,8 @@
"standard": {
"input_per_million": 0.8,
"output_per_million": 4,
- "cached_input_per_million": 0.08
+ "cache_read_input_per_million": 0.08,
+ "cache_write_input_per_million": 1
}
}
},
@@ -56,7 +57,7 @@
"name": "Claude Haiku 3.5 (latest)",
"provider": "anthropic",
"family": "claude-haiku",
- "created_at": "2024-10-22 00:00:00 +0530",
+ "created_at": "2024-10-22 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 8192,
"knowledge_cutoff": "2024-07-31",
@@ -79,7 +80,8 @@
"standard": {
"input_per_million": 0.8,
"output_per_million": 4,
- "cached_input_per_million": 0.08
+ "cache_read_input_per_million": 0.08,
+ "cache_write_input_per_million": 1
}
}
},
@@ -108,7 +110,7 @@
"name": "Claude Sonnet 3.5",
"provider": "anthropic",
"family": "claude-sonnet",
- "created_at": "2024-06-20 00:00:00 +0530",
+ "created_at": "2024-06-20 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 8192,
"knowledge_cutoff": "2024-04-30",
@@ -131,7 +133,8 @@
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -160,7 +163,7 @@
"name": "Claude Sonnet 3.5 v2",
"provider": "anthropic",
"family": "claude-sonnet",
- "created_at": "2024-10-22 00:00:00 +0530",
+ "created_at": "2024-10-22 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 8192,
"knowledge_cutoff": "2024-04-30",
@@ -183,7 +186,8 @@
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -212,7 +216,7 @@
"name": "Claude Sonnet 3.7",
"provider": "anthropic",
"family": "claude-sonnet",
- "created_at": "2025-02-19 00:00:00 +0530",
+ "created_at": "2025-02-19 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2024-10-31",
@@ -236,7 +240,8 @@
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -265,7 +270,7 @@
"name": "Claude Haiku 3",
"provider": "anthropic",
"family": "claude-haiku",
- "created_at": "2024-03-13 00:00:00 +0530",
+ "created_at": "2024-03-13 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 4096,
"knowledge_cutoff": "2023-08-31",
@@ -288,7 +293,8 @@
"standard": {
"input_per_million": 0.25,
"output_per_million": 1.25,
- "cached_input_per_million": 0.03
+ "cache_read_input_per_million": 0.03,
+ "cache_write_input_per_million": 0.3
}
}
},
@@ -317,7 +323,7 @@
"name": "Claude Opus 3",
"provider": "anthropic",
"family": "claude-opus",
- "created_at": "2024-02-29 00:00:00 +0530",
+ "created_at": "2024-02-29 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 4096,
"knowledge_cutoff": "2023-08-31",
@@ -340,7 +346,8 @@
"standard": {
"input_per_million": 15,
"output_per_million": 75,
- "cached_input_per_million": 1.5
+ "cache_read_input_per_million": 1.5,
+ "cache_write_input_per_million": 18.75
}
}
},
@@ -369,7 +376,7 @@
"name": "Claude Sonnet 3",
"provider": "anthropic",
"family": "claude-sonnet",
- "created_at": "2024-03-04 00:00:00 +0530",
+ "created_at": "2024-03-04 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 4096,
"knowledge_cutoff": "2023-08-31",
@@ -392,7 +399,8 @@
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 0.3
}
}
},
@@ -421,7 +429,7 @@
"name": "Claude Haiku 4.5 (latest)",
"provider": "anthropic",
"family": "claude-haiku",
- "created_at": "2025-10-15 00:00:00 +0530",
+ "created_at": "2025-10-15 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-02-28",
@@ -445,7 +453,8 @@
"standard": {
"input_per_million": 1,
"output_per_million": 5,
- "cached_input_per_million": 0.1
+ "cache_read_input_per_million": 0.1,
+ "cache_write_input_per_million": 1.25
}
}
},
@@ -474,7 +483,7 @@
"name": "Claude Haiku 4.5",
"provider": "anthropic",
"family": "claude-haiku",
- "created_at": "2025-10-15 00:00:00 +0530",
+ "created_at": "2025-10-15 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-02-28",
@@ -498,7 +507,8 @@
"standard": {
"input_per_million": 1,
"output_per_million": 5,
- "cached_input_per_million": 0.1
+ "cache_read_input_per_million": 0.1,
+ "cache_write_input_per_million": 1.25
}
}
},
@@ -527,7 +537,7 @@
"name": "Claude Opus 4 (latest)",
"provider": "anthropic",
"family": "claude-opus",
- "created_at": "2025-05-22 00:00:00 +0530",
+ "created_at": "2025-05-22 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 32000,
"knowledge_cutoff": "2025-03-31",
@@ -551,7 +561,8 @@
"standard": {
"input_per_million": 15,
"output_per_million": 75,
- "cached_input_per_million": 1.5
+ "cache_read_input_per_million": 1.5,
+ "cache_write_input_per_million": 18.75
}
}
},
@@ -580,7 +591,7 @@
"name": "Claude Opus 4.1 (latest)",
"provider": "anthropic",
"family": "claude-opus",
- "created_at": "2025-08-05 00:00:00 +0530",
+ "created_at": "2025-08-05 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 32000,
"knowledge_cutoff": "2025-03-31",
@@ -604,7 +615,8 @@
"standard": {
"input_per_million": 15,
"output_per_million": 75,
- "cached_input_per_million": 1.5
+ "cache_read_input_per_million": 1.5,
+ "cache_write_input_per_million": 18.75
}
}
},
@@ -633,7 +645,7 @@
"name": "Claude Opus 4.1",
"provider": "anthropic",
"family": "claude-opus",
- "created_at": "2025-08-05 00:00:00 +0530",
+ "created_at": "2025-08-05 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 32000,
"knowledge_cutoff": "2025-03-31",
@@ -657,7 +669,8 @@
"standard": {
"input_per_million": 15,
"output_per_million": 75,
- "cached_input_per_million": 1.5
+ "cache_read_input_per_million": 1.5,
+ "cache_write_input_per_million": 18.75
}
}
},
@@ -686,7 +699,7 @@
"name": "Claude Opus 4",
"provider": "anthropic",
"family": "claude-opus",
- "created_at": "2025-05-22 00:00:00 +0530",
+ "created_at": "2025-05-22 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 32000,
"knowledge_cutoff": "2025-03-31",
@@ -710,7 +723,8 @@
"standard": {
"input_per_million": 15,
"output_per_million": 75,
- "cached_input_per_million": 1.5
+ "cache_read_input_per_million": 1.5,
+ "cache_write_input_per_million": 18.75
}
}
},
@@ -739,7 +753,7 @@
"name": "Claude Opus 4.5 (latest)",
"provider": "anthropic",
"family": "claude-opus",
- "created_at": "2025-11-24 00:00:00 +0530",
+ "created_at": "2025-11-24 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-03-31",
@@ -763,7 +777,8 @@
"standard": {
"input_per_million": 5,
"output_per_million": 25,
- "cached_input_per_million": 0.5
+ "cache_read_input_per_million": 0.5,
+ "cache_write_input_per_million": 6.25
}
}
},
@@ -792,7 +807,7 @@
"name": "Claude Opus 4.5",
"provider": "anthropic",
"family": "claude-opus",
- "created_at": "2025-11-01 00:00:00 +0530",
+ "created_at": "2025-11-01 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-03-31",
@@ -816,7 +831,8 @@
"standard": {
"input_per_million": 5,
"output_per_million": 25,
- "cached_input_per_million": 0.5
+ "cache_read_input_per_million": 0.5,
+ "cache_write_input_per_million": 6.25
}
}
},
@@ -845,10 +861,10 @@
"name": "Claude Opus 4.6",
"provider": "anthropic",
"family": "claude-opus",
- "created_at": "2026-02-05 00:00:00 +0530",
+ "created_at": "2026-02-05 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 128000,
- "knowledge_cutoff": null,
+ "knowledge_cutoff": "2025-05-31",
"modalities": {
"input": [
"text",
@@ -869,7 +885,8 @@
"standard": {
"input_per_million": 5,
"output_per_million": 25,
- "cached_input_per_million": 0.5
+ "cache_read_input_per_million": 0.5,
+ "cache_write_input_per_million": 6.25
}
}
},
@@ -890,7 +907,61 @@
"context": 1000000,
"output": 128000
},
- "knowledge": "2025-05"
+ "knowledge": "2025-05-31"
+ }
+ },
+ {
+ "id": "claude-opus-4-7",
+ "name": "Claude Opus 4.7",
+ "provider": "anthropic",
+ "family": "claude-opus",
+ "created_at": "2026-04-16 00:00:00 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 128000,
+ "knowledge_cutoff": "2026-01-31",
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "pdf"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "reasoning",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 5,
+ "output_per_million": 25,
+ "cache_read_input_per_million": 0.5,
+ "cache_write_input_per_million": 6.25
+ }
+ }
+ },
+ "metadata": {
+ "source": "models.dev",
+ "provider_id": "anthropic",
+ "open_weights": false,
+ "attachment": true,
+ "temperature": false,
+ "last_updated": "2026-04-16",
+ "cost": {
+ "input": 5,
+ "output": 25,
+ "cache_read": 0.5,
+ "cache_write": 6.25
+ },
+ "limit": {
+ "context": 1000000,
+ "output": 128000
+ },
+ "knowledge": "2026-01-31"
}
},
{
@@ -898,7 +969,7 @@
"name": "Claude Sonnet 4 (latest)",
"provider": "anthropic",
"family": "claude-sonnet",
- "created_at": "2025-05-22 00:00:00 +0530",
+ "created_at": "2025-05-22 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-03-31",
@@ -922,7 +993,8 @@
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -951,7 +1023,7 @@
"name": "Claude Sonnet 4",
"provider": "anthropic",
"family": "claude-sonnet",
- "created_at": "2025-05-22 00:00:00 +0530",
+ "created_at": "2025-05-22 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-03-31",
@@ -975,7 +1047,8 @@
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -1004,7 +1077,7 @@
"name": "Claude Sonnet 4.5 (latest)",
"provider": "anthropic",
"family": "claude-sonnet",
- "created_at": "2025-09-29 00:00:00 +0530",
+ "created_at": "2025-09-29 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-07-31",
@@ -1028,7 +1101,8 @@
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -1057,7 +1131,7 @@
"name": "Claude Sonnet 4.5",
"provider": "anthropic",
"family": "claude-sonnet",
- "created_at": "2025-09-29 00:00:00 +0530",
+ "created_at": "2025-09-29 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-07-31",
@@ -1081,7 +1155,8 @@
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -1110,10 +1185,10 @@
"name": "Claude Sonnet 4.6",
"provider": "anthropic",
"family": "claude-sonnet",
- "created_at": "2026-02-17 00:00:00 +0530",
+ "created_at": "2026-02-17 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 64000,
- "knowledge_cutoff": null,
+ "knowledge_cutoff": "2025-08-31",
"modalities": {
"input": [
"text",
@@ -1134,7 +1209,8 @@
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -1155,7 +1231,8577 @@
"context": 1000000,
"output": 64000
},
- "knowledge": "2025-08"
+ "knowledge": "2025-08-31"
+ }
+ },
+ {
+ "id": "AI21-Jamba-1.5-Large",
+ "name": "AI21-Jamba-1.5-Large",
+ "provider": "azure",
+ "family": null,
+ "created_at": null,
+ "context_window": 4096,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.5,
+ "output_per_million": 1.5
+ }
+ }
+ },
+ "metadata": {
+ "object": "model",
+ "owned_by": null
+ }
+ },
+ {
+ "id": "AI21-Jamba-1.5-Mini",
+ "name": "AI21-Jamba-1.5-Mini",
+ "provider": "azure",
+ "family": null,
+ "created_at": null,
+ "context_window": 4096,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.5,
+ "output_per_million": 1.5
+ }
+ }
+ },
+ "metadata": {
+ "object": "model",
+ "owned_by": null
+ }
+ },
+ {
+ "id": "AI21-Jamba-Instruct",
+ "name": "AI21-Jamba-Instruct",
+ "provider": "azure",
+ "family": null,
+ "created_at": null,
+ "context_window": 4096,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.5,
+ "output_per_million": 1.5
+ }
+ }
+ },
+ "metadata": {
+ "object": "model",
+ "owned_by": null
+ }
+ },
+ {
+ "id": "Codestral-2501-2",
+ "name": "Codestral-2501-2",
+ "provider": "azure",
+ "family": null,
+ "created_at": null,
+ "context_window": 4096,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.5,
+ "output_per_million": 1.5
+ }
+ }
+ },
+ "metadata": {
+ "object": "model",
+ "owned_by": null
+ }
+ },
+ {
+ "id": "Cohere-command-r",
+ "name": "Cohere-command-r",
+ "provider": "azure",
+ "family": null,
+ "created_at": null,
+ "context_window": 4096,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.5,
+ "output_per_million": 1.5
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+ "name": "text-similarity-davinci-001",
+ "provider": "azure",
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+ }
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+ "name": "whisper",
+ "provider": "azure",
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+ "created_at": null,
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+ "output_per_million": 0.006
+ }
+ }
+ },
+ "metadata": {
+ "object": "model",
+ "owned_by": null
+ }
+ },
+ {
+ "id": "whisper-001",
+ "name": "whisper-001",
+ "provider": "azure",
+ "family": null,
+ "created_at": null,
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+ "knowledge_cutoff": null,
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+ "metadata": {
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}
},
{
@@ -1163,7 +9809,7 @@
"name": "Nova 2 Lite",
"provider": "bedrock",
"family": "nova",
- "created_at": "2024-12-01 00:00:00 +0530",
+ "created_at": "2024-12-01 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -1206,12 +9852,44 @@
}
}
},
+ {
+ "id": "amazon.nova-2-sonic-v1:0",
+ "name": "Nova 2 Sonic",
+ "provider": "bedrock",
+ "family": "Nova",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "audio"
+ ],
+ "output": [
+ "audio",
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Amazon",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/amazon.nova-2-sonic-v1:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {}
+ }
+ },
{
"id": "amazon.nova-lite-v1:0",
"name": "Nova Lite",
"provider": "bedrock",
"family": "nova-lite",
- "created_at": "2024-12-03 00:00:00 +0530",
+ "created_at": "2024-12-03 00:00:00 UTC",
"context_window": 300000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -1234,7 +9912,7 @@
"standard": {
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"output_per_million": 0.24,
- "cached_input_per_million": 0.015
+ "cache_read_input_per_million": 0.015
}
}
},
@@ -1262,7 +9940,7 @@
"name": "Nova Micro",
"provider": "bedrock",
"family": "nova-micro",
- "created_at": "2024-12-03 00:00:00 +0530",
+ "created_at": "2024-12-03 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -1282,7 +9960,7 @@
"standard": {
"input_per_million": 0.035,
"output_per_million": 0.14,
- "cached_input_per_million": 0.00875
+ "cache_read_input_per_million": 0.00875
}
}
},
@@ -1310,7 +9988,7 @@
"name": "Nova Premier",
"provider": "bedrock",
"family": "nova",
- "created_at": "2024-12-03 00:00:00 +0530",
+ "created_at": "2024-12-03 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 16384,
"knowledge_cutoff": null,
@@ -1355,12 +10033,208 @@
"knowledge": "2024-10"
}
},
+ {
+ "id": "amazon.nova-premier-v1:0:1000k",
+ "name": "Nova Premier",
+ "provider": "bedrock",
+ "family": "nova",
+ "created_at": "2024-12-03 00:00:00 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "video"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "reasoning",
+ "vision",
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 2.5,
+ "output_per_million": 12.5
+ }
+ }
+ },
+ "metadata": {
+ "provider_name": "Amazon",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/amazon.nova-premier-v1:0:1000k",
+ "inference_types": [],
+ "converse": {},
+ "source": "models.dev",
+ "provider_id": "amazon-bedrock",
+ "open_weights": false,
+ "attachment": true,
+ "temperature": true,
+ "last_updated": "2024-12-03",
+ "cost": {
+ "input": 2.5,
+ "output": 12.5
+ },
+ "limit": {
+ "context": 1000000,
+ "output": 16384
+ },
+ "knowledge": "2024-10"
+ }
+ },
+ {
+ "id": "amazon.nova-premier-v1:0:20k",
+ "name": "Nova Premier",
+ "provider": "bedrock",
+ "family": "nova",
+ "created_at": "2024-12-03 00:00:00 UTC",
+ "context_window": 20000,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "video"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "reasoning",
+ "vision",
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 2.5,
+ "output_per_million": 12.5
+ }
+ }
+ },
+ "metadata": {
+ "provider_name": "Amazon",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/amazon.nova-premier-v1:0:20k",
+ "inference_types": [],
+ "converse": {},
+ "source": "models.dev",
+ "provider_id": "amazon-bedrock",
+ "open_weights": false,
+ "attachment": true,
+ "temperature": true,
+ "last_updated": "2024-12-03",
+ "cost": {
+ "input": 2.5,
+ "output": 12.5
+ },
+ "limit": {
+ "context": 1000000,
+ "output": 16384
+ },
+ "knowledge": "2024-10"
+ }
+ },
+ {
+ "id": "amazon.nova-premier-v1:0:8k",
+ "name": "Nova Premier",
+ "provider": "bedrock",
+ "family": "nova",
+ "created_at": "2024-12-03 00:00:00 UTC",
+ "context_window": 8000,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "video"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "reasoning",
+ "vision",
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 2.5,
+ "output_per_million": 12.5
+ }
+ }
+ },
+ "metadata": {
+ "provider_name": "Amazon",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/amazon.nova-premier-v1:0:8k",
+ "inference_types": [],
+ "converse": {},
+ "source": "models.dev",
+ "provider_id": "amazon-bedrock",
+ "open_weights": false,
+ "attachment": true,
+ "temperature": true,
+ "last_updated": "2024-12-03",
+ "cost": {
+ "input": 2.5,
+ "output": 12.5
+ },
+ "limit": {
+ "context": 1000000,
+ "output": 16384
+ },
+ "knowledge": "2024-10"
+ }
+ },
+ {
+ "id": "amazon.nova-premier-v1:0:mm",
+ "name": "Nova Premier",
+ "provider": "bedrock",
+ "family": "amazon",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "video"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Amazon",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/amazon.nova-premier-v1:0:mm",
+ "inference_types": [],
+ "converse": {}
+ }
+ },
{
"id": "amazon.nova-pro-v1:0",
"name": "Nova Pro",
"provider": "bedrock",
"family": "nova-pro",
- "created_at": "2024-12-03 00:00:00 +0530",
+ "created_at": "2024-12-03 00:00:00 UTC",
"context_window": 300000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -1383,7 +10257,7 @@
"standard": {
"input_per_million": 0.8,
"output_per_million": 3.2,
- "cached_input_per_million": 0.2
+ "cache_read_input_per_million": 0.2
}
}
},
@@ -1406,15 +10280,259 @@
"knowledge": "2024-10"
}
},
+ {
+ "id": "amazon.rerank-v1:0",
+ "name": "Rerank 1.0",
+ "provider": "bedrock",
+ "family": "amazon",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Amazon",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/amazon.rerank-v1:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {}
+ }
+ },
+ {
+ "id": "amazon.titan-embed-g1-text-02",
+ "name": "Titan Text Embeddings v2",
+ "provider": "bedrock",
+ "family": "amazon",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "embeddings"
+ ]
+ },
+ "capabilities": [
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Amazon",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/amazon.titan-embed-g1-text-02",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {}
+ }
+ },
+ {
+ "id": "amazon.titan-embed-image-v1",
+ "name": "Titan Multimodal Embeddings G1",
+ "provider": "bedrock",
+ "family": "amazon",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "embeddings"
+ ]
+ },
+ "capabilities": [
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Amazon",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/amazon.titan-embed-image-v1",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {}
+ }
+ },
+ {
+ "id": "amazon.titan-embed-image-v1:0",
+ "name": "Titan Multimodal Embeddings G1",
+ "provider": "bedrock",
+ "family": "amazon",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "embeddings"
+ ]
+ },
+ "capabilities": [
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Amazon",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/amazon.titan-embed-image-v1:0",
+ "inference_types": [
+ "PROVISIONED"
+ ],
+ "converse": {}
+ }
+ },
+ {
+ "id": "amazon.titan-embed-text-v1",
+ "name": "Titan Embeddings G1 - Text",
+ "provider": "bedrock",
+ "family": "amazon",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "embeddings"
+ ]
+ },
+ "capabilities": [
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Amazon",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/amazon.titan-embed-text-v1",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {}
+ }
+ },
+ {
+ "id": "amazon.titan-embed-text-v1:2:8k",
+ "name": "Titan Embeddings G1 - Text",
+ "provider": "bedrock",
+ "family": "amazon",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "embeddings"
+ ]
+ },
+ "capabilities": [
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Amazon",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/amazon.titan-embed-text-v1:2:8k",
+ "inference_types": [
+ "PROVISIONED"
+ ],
+ "converse": {}
+ }
+ },
+ {
+ "id": "amazon.titan-embed-text-v2:0",
+ "name": "Titan Text Embeddings V2",
+ "provider": "bedrock",
+ "family": "amazon",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "embeddings"
+ ]
+ },
+ "capabilities": [
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Amazon",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/amazon.titan-embed-text-v2:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {}
+ }
+ },
+ {
+ "id": "amazon.titan-image-generator-v2:0",
+ "name": "Titan Image Generator G1 v2",
+ "provider": "bedrock",
+ "family": "amazon",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "image"
+ ]
+ },
+ "capabilities": [
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Amazon",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/amazon.titan-image-generator-v2:0",
+ "inference_types": [
+ "PROVISIONED",
+ "ON_DEMAND"
+ ],
+ "converse": {}
+ }
+ },
{
"id": "anthropic.claude-3-5-haiku-20241022-v1:0",
"name": "Claude Haiku 3.5",
"provider": "bedrock",
"family": "claude-haiku",
- "created_at": "2024-10-22 00:00:00 +0530",
+ "created_at": "2024-10-22 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 8192,
- "knowledge_cutoff": null,
+ "knowledge_cutoff": "2024-07-31",
"modalities": {
"input": [
"text",
@@ -1427,18 +10545,26 @@
},
"capabilities": [
"function_calling",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.8,
"output_per_million": 4,
- "cached_input_per_million": 0.08
+ "cache_read_input_per_million": 0.08,
+ "cache_write_input_per_million": 1
}
}
},
"metadata": {
+ "provider_name": "Anthropic",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-3-5-haiku-20241022-v1:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {},
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": false,
@@ -1455,7 +10581,7 @@
"context": 200000,
"output": 8192
},
- "knowledge": "2024-07"
+ "knowledge": "2024-07-31"
}
},
{
@@ -1463,10 +10589,10 @@
"name": "Claude Sonnet 3.5",
"provider": "bedrock",
"family": "claude-sonnet",
- "created_at": "2024-06-20 00:00:00 +0530",
+ "created_at": "2024-06-20 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 8192,
- "knowledge_cutoff": null,
+ "knowledge_cutoff": "2024-04-30",
"modalities": {
"input": [
"text",
@@ -1486,7 +10612,8 @@
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -1507,7 +10634,7 @@
"context": 200000,
"output": 8192
},
- "knowledge": "2024-04"
+ "knowledge": "2024-04-30"
}
},
{
@@ -1515,7 +10642,7 @@
"name": "Claude Sonnet 3.5 v2",
"provider": "bedrock",
"family": "claude-sonnet",
- "created_at": "2024-10-22 00:00:00 +0530",
+ "created_at": "2024-10-22 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -1538,7 +10665,8 @@
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -1567,7 +10695,7 @@
"name": "Claude Sonnet 3.7",
"provider": "bedrock",
"family": "claude-sonnet",
- "created_at": "2025-02-19 00:00:00 +0530",
+ "created_at": "2025-02-19 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -1590,7 +10718,8 @@
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -1619,7 +10748,7 @@
"name": "Claude Haiku 3",
"provider": "bedrock",
"family": "claude-haiku",
- "created_at": "2024-03-13 00:00:00 +0530",
+ "created_at": "2024-03-13 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -1635,7 +10764,8 @@
},
"capabilities": [
"function_calling",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -1646,6 +10776,12 @@
}
},
"metadata": {
+ "provider_name": "Anthropic",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-3-haiku-20240307-v1:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {},
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": false,
@@ -1663,12 +10799,220 @@
"knowledge": "2024-02"
}
},
+ {
+ "id": "anthropic.claude-3-haiku-20240307-v1:0:200k",
+ "name": "Claude Haiku 3",
+ "provider": "bedrock",
+ "family": "claude-haiku",
+ "created_at": "2024-03-13 00:00:00 UTC",
+ "context_window": 200000,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "pdf"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "vision",
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.25,
+ "output_per_million": 1.25
+ }
+ }
+ },
+ "metadata": {
+ "provider_name": "Anthropic",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-3-haiku-20240307-v1:0:200k",
+ "inference_types": [
+ "PROVISIONED"
+ ],
+ "converse": {},
+ "source": "models.dev",
+ "provider_id": "amazon-bedrock",
+ "open_weights": false,
+ "attachment": true,
+ "temperature": true,
+ "last_updated": "2024-03-13",
+ "cost": {
+ "input": 0.25,
+ "output": 1.25
+ },
+ "limit": {
+ "context": 200000,
+ "output": 4096
+ },
+ "knowledge": "2024-02"
+ }
+ },
+ {
+ "id": "anthropic.claude-3-haiku-20240307-v1:0:48k",
+ "name": "Claude Haiku 3",
+ "provider": "bedrock",
+ "family": "claude-haiku",
+ "created_at": "2024-03-13 00:00:00 UTC",
+ "context_window": 48000,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "pdf"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "vision",
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.25,
+ "output_per_million": 1.25
+ }
+ }
+ },
+ "metadata": {
+ "provider_name": "Anthropic",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-3-haiku-20240307-v1:0:48k",
+ "inference_types": [
+ "PROVISIONED"
+ ],
+ "converse": {},
+ "source": "models.dev",
+ "provider_id": "amazon-bedrock",
+ "open_weights": false,
+ "attachment": true,
+ "temperature": true,
+ "last_updated": "2024-03-13",
+ "cost": {
+ "input": 0.25,
+ "output": 1.25
+ },
+ "limit": {
+ "context": 200000,
+ "output": 4096
+ },
+ "knowledge": "2024-02"
+ }
+ },
+ {
+ "id": "anthropic.claude-3-sonnet-20240229-v1:0",
+ "name": "Claude 3 Sonnet",
+ "provider": "bedrock",
+ "family": "anthropic",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Anthropic",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-3-sonnet-20240229-v1:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {}
+ }
+ },
+ {
+ "id": "anthropic.claude-3-sonnet-20240229-v1:0:200k",
+ "name": "Claude 3 Sonnet",
+ "provider": "bedrock",
+ "family": "anthropic",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Anthropic",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-3-sonnet-20240229-v1:0:200k",
+ "inference_types": [
+ "PROVISIONED"
+ ],
+ "converse": {}
+ }
+ },
+ {
+ "id": "anthropic.claude-3-sonnet-20240229-v1:0:28k",
+ "name": "Claude 3 Sonnet",
+ "provider": "bedrock",
+ "family": "anthropic",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Anthropic",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-3-sonnet-20240229-v1:0:28k",
+ "inference_types": [
+ "PROVISIONED"
+ ],
+ "converse": {}
+ }
+ },
{
"id": "anthropic.claude-haiku-4-5-20251001-v1:0",
"name": "Claude Haiku 4.5",
"provider": "bedrock",
"family": "claude-haiku",
- "created_at": "2025-10-15 00:00:00 +0530",
+ "created_at": "2025-10-15 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-02-28",
@@ -1693,7 +11037,8 @@
"standard": {
"input_per_million": 1,
"output_per_million": 5,
- "cached_input_per_million": 0.1
+ "cache_read_input_per_million": 0.1,
+ "cache_write_input_per_million": 1.25
}
}
},
@@ -1722,7 +11067,7 @@
"name": "Claude Opus 4.1",
"provider": "bedrock",
"family": "claude-opus",
- "created_at": "2025-08-05 00:00:00 +0530",
+ "created_at": "2025-08-05 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 32000,
"knowledge_cutoff": "2025-03-31",
@@ -1746,7 +11091,8 @@
"standard": {
"input_per_million": 15,
"output_per_million": 75,
- "cached_input_per_million": 1.5
+ "cache_read_input_per_million": 1.5,
+ "cache_write_input_per_million": 18.75
}
}
},
@@ -1775,10 +11121,10 @@
"name": "Claude Opus 4",
"provider": "bedrock",
"family": "claude-opus",
- "created_at": "2025-05-22 00:00:00 +0530",
+ "created_at": "2025-05-22 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 32000,
- "knowledge_cutoff": null,
+ "knowledge_cutoff": "2025-03-31",
"modalities": {
"input": [
"text",
@@ -1799,7 +11145,8 @@
"standard": {
"input_per_million": 15,
"output_per_million": 75,
- "cached_input_per_million": 1.5
+ "cache_read_input_per_million": 1.5,
+ "cache_write_input_per_million": 18.75
}
}
},
@@ -1820,7 +11167,7 @@
"context": 200000,
"output": 32000
},
- "knowledge": "2024-04"
+ "knowledge": "2025-03-31"
}
},
{
@@ -1828,7 +11175,7 @@
"name": "Claude Opus 4.5",
"provider": "bedrock",
"family": "claude-opus",
- "created_at": "2025-11-24 00:00:00 +0530",
+ "created_at": "2025-11-24 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-03-31",
@@ -1853,7 +11200,8 @@
"standard": {
"input_per_million": 5,
"output_per_million": 25,
- "cached_input_per_million": 0.5
+ "cache_read_input_per_million": 0.5,
+ "cache_write_input_per_million": 6.25
}
}
},
@@ -1882,10 +11230,10 @@
"name": "Claude Opus 4.6",
"provider": "bedrock",
"family": "claude-opus",
- "created_at": "2026-02-05 00:00:00 +0530",
+ "created_at": "2026-02-05 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 128000,
- "knowledge_cutoff": null,
+ "knowledge_cutoff": "2025-05-31",
"modalities": {
"input": [
"text",
@@ -1907,7 +11255,8 @@
"standard": {
"input_per_million": 5,
"output_per_million": 25,
- "cached_input_per_million": 0.5
+ "cache_read_input_per_million": 0.5,
+ "cache_write_input_per_million": 6.25
}
}
},
@@ -1917,7 +11266,7 @@
"open_weights": false,
"attachment": true,
"temperature": true,
- "last_updated": "2026-03-18",
+ "last_updated": "2026-03-13",
"cost": {
"input": 5,
"output": 25,
@@ -1928,7 +11277,62 @@
"context": 1000000,
"output": 128000
},
- "knowledge": "2025-05"
+ "knowledge": "2025-05-31"
+ }
+ },
+ {
+ "id": "anthropic.claude-opus-4-7",
+ "name": "Claude Opus 4.7",
+ "provider": "bedrock",
+ "family": "claude-opus",
+ "created_at": "2026-04-16 00:00:00 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 128000,
+ "knowledge_cutoff": "2026-01-31",
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "pdf"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "reasoning",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 5,
+ "output_per_million": 25,
+ "cache_read_input_per_million": 0.5,
+ "cache_write_input_per_million": 6.25
+ }
+ }
+ },
+ "metadata": {
+ "source": "models.dev",
+ "provider_id": "amazon-bedrock",
+ "open_weights": false,
+ "attachment": true,
+ "temperature": false,
+ "last_updated": "2026-04-16",
+ "cost": {
+ "input": 5,
+ "output": 25,
+ "cache_read": 0.5,
+ "cache_write": 6.25
+ },
+ "limit": {
+ "context": 1000000,
+ "output": 128000
+ },
+ "knowledge": "2026-01-31"
}
},
{
@@ -1936,10 +11340,10 @@
"name": "Claude Sonnet 4",
"provider": "bedrock",
"family": "claude-sonnet",
- "created_at": "2025-05-22 00:00:00 +0530",
+ "created_at": "2025-05-22 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
- "knowledge_cutoff": null,
+ "knowledge_cutoff": "2025-03-31",
"modalities": {
"input": [
"text",
@@ -1960,7 +11364,8 @@
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -1981,7 +11386,7 @@
"context": 200000,
"output": 64000
},
- "knowledge": "2024-04"
+ "knowledge": "2025-03-31"
}
},
{
@@ -1989,7 +11394,7 @@
"name": "Claude Sonnet 4.5",
"provider": "bedrock",
"family": "claude-sonnet",
- "created_at": "2025-09-29 00:00:00 +0530",
+ "created_at": "2025-09-29 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-07-31",
@@ -2014,7 +11419,8 @@
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -2043,10 +11449,10 @@
"name": "Claude Sonnet 4.6",
"provider": "bedrock",
"family": "claude-sonnet",
- "created_at": "2026-02-17 00:00:00 +0530",
+ "created_at": "2026-02-17 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 64000,
- "knowledge_cutoff": null,
+ "knowledge_cutoff": "2025-08-31",
"modalities": {
"input": [
"text",
@@ -2067,7 +11473,8 @@
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -2077,7 +11484,7 @@
"open_weights": false,
"attachment": true,
"temperature": true,
- "last_updated": "2026-03-18",
+ "last_updated": "2026-03-13",
"cost": {
"input": 3,
"output": 15,
@@ -2088,15 +11495,337 @@
"context": 1000000,
"output": 64000
},
+ "knowledge": "2025-08-31"
+ }
+ },
+ {
+ "id": "au.anthropic.claude-opus-4-6-v1",
+ "name": "AU Anthropic Claude Opus 4.6",
+ "provider": "bedrock",
+ "family": "claude-opus",
+ "created_at": "2026-02-05 00:00:00 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 128000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "pdf"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "reasoning",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 16.5,
+ "output_per_million": 82.5,
+ "cache_read_input_per_million": 1.65,
+ "cache_write_input_per_million": 20.625
+ }
+ }
+ },
+ "metadata": {
+ "source": "models.dev",
+ "provider_id": "amazon-bedrock",
+ "open_weights": false,
+ "attachment": true,
+ "temperature": true,
+ "last_updated": "2026-02-05",
+ "cost": {
+ "input": 16.5,
+ "output": 82.5,
+ "cache_read": 1.65,
+ "cache_write": 20.625
+ },
+ "limit": {
+ "context": 1000000,
+ "output": 128000
+ },
+ "knowledge": "2025-05"
+ }
+ },
+ {
+ "id": "au.anthropic.claude-sonnet-4-6",
+ "name": "AU Anthropic Claude Sonnet 4.6",
+ "provider": "bedrock",
+ "family": "claude-sonnet",
+ "created_at": "2026-02-17 00:00:00 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 128000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "pdf"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "reasoning",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 3.3,
+ "output_per_million": 16.5,
+ "cache_read_input_per_million": 0.33,
+ "cache_write_input_per_million": 4.125
+ }
+ }
+ },
+ "metadata": {
+ "source": "models.dev",
+ "provider_id": "amazon-bedrock",
+ "open_weights": false,
+ "attachment": true,
+ "temperature": true,
+ "last_updated": "2026-02-17",
+ "cost": {
+ "input": 3.3,
+ "output": 16.5,
+ "cache_read": 0.33,
+ "cache_write": 4.125
+ },
+ "limit": {
+ "context": 1000000,
+ "output": 128000
+ },
"knowledge": "2025-08"
}
},
+ {
+ "id": "cohere.command-r-plus-v1:0",
+ "name": "Command R+",
+ "provider": "bedrock",
+ "family": "cohere",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Cohere",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/cohere.command-r-plus-v1:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {}
+ }
+ },
+ {
+ "id": "cohere.command-r-v1:0",
+ "name": "Command R",
+ "provider": "bedrock",
+ "family": "cohere",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Cohere",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/cohere.command-r-v1:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {}
+ }
+ },
+ {
+ "id": "cohere.embed-english-v3",
+ "name": "Embed English",
+ "provider": "bedrock",
+ "family": "cohere",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "embeddings"
+ ]
+ },
+ "capabilities": [
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Cohere",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/cohere.embed-english-v3",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {}
+ }
+ },
+ {
+ "id": "cohere.embed-english-v3:0:512",
+ "name": "Embed English",
+ "provider": "bedrock",
+ "family": "cohere",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "embeddings"
+ ]
+ },
+ "capabilities": [
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Cohere",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/cohere.embed-english-v3:0:512",
+ "inference_types": [
+ "PROVISIONED"
+ ],
+ "converse": {}
+ }
+ },
+ {
+ "id": "cohere.embed-multilingual-v3",
+ "name": "Embed Multilingual",
+ "provider": "bedrock",
+ "family": "cohere",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "embeddings"
+ ]
+ },
+ "capabilities": [
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Cohere",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/cohere.embed-multilingual-v3",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {}
+ }
+ },
+ {
+ "id": "cohere.embed-multilingual-v3:0:512",
+ "name": "Embed Multilingual",
+ "provider": "bedrock",
+ "family": "cohere",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "embeddings"
+ ]
+ },
+ "capabilities": [
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Cohere",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/cohere.embed-multilingual-v3:0:512",
+ "inference_types": [
+ "PROVISIONED"
+ ],
+ "converse": {}
+ }
+ },
+ {
+ "id": "cohere.rerank-v3-5:0",
+ "name": "Rerank 3.5",
+ "provider": "bedrock",
+ "family": "cohere",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Cohere",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/cohere.rerank-v3-5:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {}
+ }
+ },
{
"id": "deepseek.r1-v1:0",
"name": "DeepSeek-R1",
"provider": "bedrock",
"family": "deepseek-thinking",
- "created_at": "2025-01-20 00:00:00 +0530",
+ "created_at": "2025-01-20 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -2143,7 +11872,7 @@
"name": "DeepSeek-V3.1",
"provider": "bedrock",
"family": "deepseek",
- "created_at": "2025-09-18 00:00:00 +0530",
+ "created_at": "2025-09-18 00:00:00 UTC",
"context_window": 163840,
"max_output_tokens": 81920,
"knowledge_cutoff": null,
@@ -2158,7 +11887,8 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -2169,6 +11899,24 @@
}
},
"metadata": {
+ "provider_name": "DeepSeek",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/deepseek.v3-v1:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "{\"reasoningConfig\":{\"enabled\":{\"type\":\"boolean\",\"default\":false}}}",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 163840,
+ "reasoningSupported": {
+ "embedded": false
+ },
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -2191,7 +11939,7 @@
"name": "DeepSeek-V3.2",
"provider": "bedrock",
"family": "deepseek",
- "created_at": "2026-02-06 00:00:00 +0530",
+ "created_at": "2026-02-06 00:00:00 UTC",
"context_window": 163840,
"max_output_tokens": 81920,
"knowledge_cutoff": null,
@@ -2205,7 +11953,8 @@
},
"capabilities": [
"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -2216,6 +11965,24 @@
}
},
"metadata": {
+ "provider_name": "DeepSeek",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/deepseek.v3.2",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "{\"reasoningConfig\":{\"enabled\":{\"type\":\"boolean\",\"default\":false}}}",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 163840,
+ "reasoningSupported": {
+ "embedded": false
+ },
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -2238,7 +12005,7 @@
"name": "Claude Haiku 4.5 (EU)",
"provider": "bedrock",
"family": "claude-haiku",
- "created_at": "2025-10-15 00:00:00 +0530",
+ "created_at": "2025-10-15 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-02-28",
@@ -2263,7 +12030,8 @@
"standard": {
"input_per_million": 1,
"output_per_million": 5,
- "cached_input_per_million": 0.1
+ "cache_read_input_per_million": 0.1,
+ "cache_write_input_per_million": 1.25
}
}
},
@@ -2292,7 +12060,7 @@
"name": "Claude Opus 4.5 (EU)",
"provider": "bedrock",
"family": "claude-opus",
- "created_at": "2025-11-24 00:00:00 +0530",
+ "created_at": "2025-11-24 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-03-31",
@@ -2317,7 +12085,8 @@
"standard": {
"input_per_million": 5,
"output_per_million": 25,
- "cached_input_per_million": 0.5
+ "cache_read_input_per_million": 0.5,
+ "cache_write_input_per_million": 6.25
}
}
},
@@ -2346,10 +12115,10 @@
"name": "Claude Opus 4.6 (EU)",
"provider": "bedrock",
"family": "claude-opus",
- "created_at": "2026-02-05 00:00:00 +0530",
+ "created_at": "2026-02-05 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 128000,
- "knowledge_cutoff": null,
+ "knowledge_cutoff": "2025-05-31",
"modalities": {
"input": [
"text",
@@ -2371,7 +12140,8 @@
"standard": {
"input_per_million": 5,
"output_per_million": 25,
- "cached_input_per_million": 0.5
+ "cache_read_input_per_million": 0.5,
+ "cache_write_input_per_million": 6.25
}
}
},
@@ -2381,7 +12151,7 @@
"open_weights": false,
"attachment": true,
"temperature": true,
- "last_updated": "2026-03-18",
+ "last_updated": "2026-03-13",
"cost": {
"input": 5,
"output": 25,
@@ -2392,7 +12162,62 @@
"context": 1000000,
"output": 128000
},
- "knowledge": "2025-05"
+ "knowledge": "2025-05-31"
+ }
+ },
+ {
+ "id": "eu.anthropic.claude-opus-4-7",
+ "name": "Claude Opus 4.7 (EU)",
+ "provider": "bedrock",
+ "family": "claude-opus",
+ "created_at": "2026-04-16 00:00:00 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 128000,
+ "knowledge_cutoff": "2026-01-31",
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "pdf"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "reasoning",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
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+ "output_per_million": 25,
+ "cache_read_input_per_million": 0.5,
+ "cache_write_input_per_million": 6.25
+ }
+ }
+ },
+ "metadata": {
+ "source": "models.dev",
+ "provider_id": "amazon-bedrock",
+ "open_weights": false,
+ "attachment": true,
+ "temperature": false,
+ "last_updated": "2026-04-16",
+ "cost": {
+ "input": 5,
+ "output": 25,
+ "cache_read": 0.5,
+ "cache_write": 6.25
+ },
+ "limit": {
+ "context": 1000000,
+ "output": 128000
+ },
+ "knowledge": "2026-01-31"
}
},
{
@@ -2400,10 +12225,10 @@
"name": "Claude Sonnet 4 (EU)",
"provider": "bedrock",
"family": "claude-sonnet",
- "created_at": "2025-05-22 00:00:00 +0530",
+ "created_at": "2025-05-22 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
- "knowledge_cutoff": null,
+ "knowledge_cutoff": "2025-03-31",
"modalities": {
"input": [
"text",
@@ -2424,7 +12249,8 @@
"standard": {
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"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -2445,7 +12271,7 @@
"context": 200000,
"output": 64000
},
- "knowledge": "2024-04"
+ "knowledge": "2025-03-31"
}
},
{
@@ -2453,7 +12279,7 @@
"name": "Claude Sonnet 4.5 (EU)",
"provider": "bedrock",
"family": "claude-sonnet",
- "created_at": "2025-09-29 00:00:00 +0530",
+ "created_at": "2025-09-29 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-07-31",
@@ -2478,7 +12304,8 @@
"standard": {
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"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -2507,10 +12334,10 @@
"name": "Claude Sonnet 4.6 (EU)",
"provider": "bedrock",
"family": "claude-sonnet",
- "created_at": "2026-02-17 00:00:00 +0530",
+ "created_at": "2026-02-17 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 64000,
- "knowledge_cutoff": null,
+ "knowledge_cutoff": "2025-08-31",
"modalities": {
"input": [
"text",
@@ -2531,7 +12358,8 @@
"standard": {
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"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -2541,7 +12369,7 @@
"open_weights": false,
"attachment": true,
"temperature": true,
- "last_updated": "2026-03-18",
+ "last_updated": "2026-03-13",
"cost": {
"input": 3,
"output": 15,
@@ -2552,7 +12380,7 @@
"context": 1000000,
"output": 64000
},
- "knowledge": "2025-08"
+ "knowledge": "2025-08-31"
}
},
{
@@ -2560,7 +12388,7 @@
"name": "Claude Haiku 4.5 (Global)",
"provider": "bedrock",
"family": "claude-haiku",
- "created_at": "2025-10-15 00:00:00 +0530",
+ "created_at": "2025-10-15 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-02-28",
@@ -2585,7 +12413,8 @@
"standard": {
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"output_per_million": 5,
- "cached_input_per_million": 0.1
+ "cache_read_input_per_million": 0.1,
+ "cache_write_input_per_million": 1.25
}
}
},
@@ -2614,7 +12443,7 @@
"name": "Claude Opus 4.5 (Global)",
"provider": "bedrock",
"family": "claude-opus",
- "created_at": "2025-11-24 00:00:00 +0530",
+ "created_at": "2025-11-24 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-03-31",
@@ -2639,7 +12468,8 @@
"standard": {
"input_per_million": 5,
"output_per_million": 25,
- "cached_input_per_million": 0.5
+ "cache_read_input_per_million": 0.5,
+ "cache_write_input_per_million": 6.25
}
}
},
@@ -2668,10 +12498,10 @@
"name": "Claude Opus 4.6 (Global)",
"provider": "bedrock",
"family": "claude-opus",
- "created_at": "2026-02-05 00:00:00 +0530",
+ "created_at": "2026-02-05 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 128000,
- "knowledge_cutoff": null,
+ "knowledge_cutoff": "2025-05-31",
"modalities": {
"input": [
"text",
@@ -2693,7 +12523,8 @@
"standard": {
"input_per_million": 5,
"output_per_million": 25,
- "cached_input_per_million": 0.5
+ "cache_read_input_per_million": 0.5,
+ "cache_write_input_per_million": 6.25
}
}
},
@@ -2703,7 +12534,7 @@
"open_weights": false,
"attachment": true,
"temperature": true,
- "last_updated": "2026-03-18",
+ "last_updated": "2026-03-13",
"cost": {
"input": 5,
"output": 25,
@@ -2714,7 +12545,62 @@
"context": 1000000,
"output": 128000
},
- "knowledge": "2025-05"
+ "knowledge": "2025-05-31"
+ }
+ },
+ {
+ "id": "global.anthropic.claude-opus-4-7",
+ "name": "Claude Opus 4.7 (Global)",
+ "provider": "bedrock",
+ "family": "claude-opus",
+ "created_at": "2026-04-16 00:00:00 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 128000,
+ "knowledge_cutoff": "2026-01-31",
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "pdf"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "reasoning",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 5,
+ "output_per_million": 25,
+ "cache_read_input_per_million": 0.5,
+ "cache_write_input_per_million": 6.25
+ }
+ }
+ },
+ "metadata": {
+ "source": "models.dev",
+ "provider_id": "amazon-bedrock",
+ "open_weights": false,
+ "attachment": true,
+ "temperature": false,
+ "last_updated": "2026-04-16",
+ "cost": {
+ "input": 5,
+ "output": 25,
+ "cache_read": 0.5,
+ "cache_write": 6.25
+ },
+ "limit": {
+ "context": 1000000,
+ "output": 128000
+ },
+ "knowledge": "2026-01-31"
}
},
{
@@ -2722,10 +12608,10 @@
"name": "Claude Sonnet 4 (Global)",
"provider": "bedrock",
"family": "claude-sonnet",
- "created_at": "2025-05-22 00:00:00 +0530",
+ "created_at": "2025-05-22 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
- "knowledge_cutoff": null,
+ "knowledge_cutoff": "2025-03-31",
"modalities": {
"input": [
"text",
@@ -2746,7 +12632,8 @@
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -2767,7 +12654,7 @@
"context": 200000,
"output": 64000
},
- "knowledge": "2024-04"
+ "knowledge": "2025-03-31"
}
},
{
@@ -2775,7 +12662,7 @@
"name": "Claude Sonnet 4.5 (Global)",
"provider": "bedrock",
"family": "claude-sonnet",
- "created_at": "2025-09-29 00:00:00 +0530",
+ "created_at": "2025-09-29 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-07-31",
@@ -2800,7 +12687,8 @@
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -2829,10 +12717,10 @@
"name": "Claude Sonnet 4.6 (Global)",
"provider": "bedrock",
"family": "claude-sonnet",
- "created_at": "2026-02-17 00:00:00 +0530",
+ "created_at": "2026-02-17 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 64000,
- "knowledge_cutoff": null,
+ "knowledge_cutoff": "2025-08-31",
"modalities": {
"input": [
"text",
@@ -2853,7 +12741,8 @@
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
@@ -2863,7 +12752,7 @@
"open_weights": false,
"attachment": true,
"temperature": true,
- "last_updated": "2026-03-18",
+ "last_updated": "2026-03-13",
"cost": {
"input": 3,
"output": 15,
@@ -2874,7 +12763,7 @@
"context": 1000000,
"output": 64000
},
- "knowledge": "2025-08"
+ "knowledge": "2025-08-31"
}
},
{
@@ -2882,7 +12771,7 @@
"name": "Google Gemma 3 12B",
"provider": "bedrock",
"family": "gemma",
- "created_at": "2024-12-01 00:00:00 +0530",
+ "created_at": "2024-12-01 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -2897,7 +12786,9 @@
},
"capabilities": [
"structured_output",
- "vision"
+ "vision",
+ "streaming",
+ "function_calling"
],
"pricing": {
"text_tokens": {
@@ -2908,6 +12799,27 @@
}
},
"metadata": {
+ "provider_name": "Google",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/google.gemma-3-12b-it",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "{\"reasoningConfig\":{\"enabled\":{\"type\":\"boolean\",\"default\":false}}}",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 131072,
+ "reasoningSupported": null,
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [
+ "png",
+ "jpeg",
+ "gif",
+ "webp"
+ ],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": false,
@@ -2930,7 +12842,7 @@
"name": "Google Gemma 3 27B Instruct",
"provider": "bedrock",
"family": "gemma",
- "created_at": "2025-07-27 00:00:00 +0530",
+ "created_at": "2025-07-27 00:00:00 UTC",
"context_window": 202752,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -2946,7 +12858,8 @@
"capabilities": [
"function_calling",
"structured_output",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -2957,6 +12870,27 @@
}
},
"metadata": {
+ "provider_name": "Google",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/google.gemma-3-27b-it",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "{\"reasoningConfig\":{\"enabled\":{\"type\":\"boolean\",\"default\":false}}}",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 131072,
+ "reasoningSupported": null,
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [
+ "png",
+ "jpeg",
+ "gif",
+ "webp"
+ ],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -2979,7 +12913,7 @@
"name": "Gemma 3 4B IT",
"provider": "bedrock",
"family": "gemma",
- "created_at": "2024-12-01 00:00:00 +0530",
+ "created_at": "2024-12-01 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -2994,7 +12928,8 @@
},
"capabilities": [
"function_calling",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -3005,6 +12940,27 @@
}
},
"metadata": {
+ "provider_name": "Google",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/google.gemma-3-4b-it",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "{\"reasoningConfig\":{\"enabled\":{\"type\":\"boolean\",\"default\":false}}}",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 131072,
+ "reasoningSupported": null,
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [
+ "png",
+ "jpeg",
+ "gif",
+ "webp"
+ ],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": false,
@@ -3021,12 +12977,42 @@
}
}
},
+ {
+ "id": "luma.ray-v2:0",
+ "name": "Ray v2",
+ "provider": "bedrock",
+ "family": "luma ai",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "video"
+ ]
+ },
+ "capabilities": [
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Luma AI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/luma.ray-v2:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {}
+ }
+ },
{
"id": "meta.llama3-1-405b-instruct-v1:0",
"name": "Llama 3.1 405B Instruct",
"provider": "bedrock",
"family": "llama",
- "created_at": "2024-07-23 00:00:00 +0530",
+ "created_at": "2024-07-23 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -3039,7 +13025,8 @@
]
},
"capabilities": [
- "function_calling"
+ "function_calling",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -3050,6 +13037,12 @@
}
},
"metadata": {
+ "provider_name": "Meta",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/meta.llama3-1-405b-instruct-v1:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {},
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -3072,7 +13065,7 @@
"name": "Llama 3.1 70B Instruct",
"provider": "bedrock",
"family": "llama",
- "created_at": "2024-07-23 00:00:00 +0530",
+ "created_at": "2024-07-23 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -3085,7 +13078,8 @@
]
},
"capabilities": [
- "function_calling"
+ "function_calling",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -3096,6 +13090,66 @@
}
},
"metadata": {
+ "provider_name": "Meta",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/meta.llama3-1-70b-instruct-v1:0",
+ "inference_types": [
+ "ON_DEMAND",
+ "INFERENCE_PROFILE"
+ ],
+ "converse": {},
+ "source": "models.dev",
+ "provider_id": "amazon-bedrock",
+ "open_weights": true,
+ "attachment": false,
+ "temperature": true,
+ "last_updated": "2024-07-23",
+ "cost": {
+ "input": 0.72,
+ "output": 0.72
+ },
+ "limit": {
+ "context": 128000,
+ "output": 4096
+ },
+ "knowledge": "2023-12"
+ }
+ },
+ {
+ "id": "meta.llama3-1-70b-instruct-v1:0:128k",
+ "name": "Llama 3.1 70B Instruct",
+ "provider": "bedrock",
+ "family": "llama",
+ "created_at": "2024-07-23 00:00:00 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.72,
+ "output_per_million": 0.72
+ }
+ }
+ },
+ "metadata": {
+ "provider_name": "Meta",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/meta.llama3-1-70b-instruct-v1:0:128k",
+ "inference_types": [
+ "PROVISIONED"
+ ],
+ "converse": {},
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -3118,7 +13172,7 @@
"name": "Llama 3.1 8B Instruct",
"provider": "bedrock",
"family": "llama",
- "created_at": "2024-07-23 00:00:00 +0530",
+ "created_at": "2024-07-23 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -3131,7 +13185,8 @@
]
},
"capabilities": [
- "function_calling"
+ "function_calling",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -3142,6 +13197,66 @@
}
},
"metadata": {
+ "provider_name": "Meta",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/meta.llama3-1-8b-instruct-v1:0",
+ "inference_types": [
+ "ON_DEMAND",
+ "INFERENCE_PROFILE"
+ ],
+ "converse": {},
+ "source": "models.dev",
+ "provider_id": "amazon-bedrock",
+ "open_weights": true,
+ "attachment": false,
+ "temperature": true,
+ "last_updated": "2024-07-23",
+ "cost": {
+ "input": 0.22,
+ "output": 0.22
+ },
+ "limit": {
+ "context": 128000,
+ "output": 4096
+ },
+ "knowledge": "2023-12"
+ }
+ },
+ {
+ "id": "meta.llama3-1-8b-instruct-v1:0:128k",
+ "name": "Llama 3.1 8B Instruct",
+ "provider": "bedrock",
+ "family": "llama",
+ "created_at": "2024-07-23 00:00:00 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
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+ "output_per_million": 0.22
+ }
+ }
+ },
+ "metadata": {
+ "provider_name": "Meta",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/meta.llama3-1-8b-instruct-v1:0:128k",
+ "inference_types": [
+ "PROVISIONED"
+ ],
+ "converse": {},
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -3164,7 +13279,7 @@
"name": "Llama 3.2 11B Instruct",
"provider": "bedrock",
"family": "llama",
- "created_at": "2024-09-25 00:00:00 +0530",
+ "created_at": "2024-09-25 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -3207,12 +13322,67 @@
"knowledge": "2023-12"
}
},
+ {
+ "id": "meta.llama3-2-11b-instruct-v1:0:128k",
+ "name": "Llama 3.2 11B Instruct",
+ "provider": "bedrock",
+ "family": "llama",
+ "created_at": "2024-09-25 00:00:00 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "vision",
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.16,
+ "output_per_million": 0.16
+ }
+ }
+ },
+ "metadata": {
+ "provider_name": "Meta",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/meta.llama3-2-11b-instruct-v1:0:128k",
+ "inference_types": [
+ "PROVISIONED"
+ ],
+ "converse": {},
+ "source": "models.dev",
+ "provider_id": "amazon-bedrock",
+ "open_weights": true,
+ "attachment": true,
+ "temperature": true,
+ "last_updated": "2024-09-25",
+ "cost": {
+ "input": 0.16,
+ "output": 0.16
+ },
+ "limit": {
+ "context": 128000,
+ "output": 4096
+ },
+ "knowledge": "2023-12"
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{
"id": "meta.llama3-2-1b-instruct-v1:0",
"name": "Llama 3.2 1B Instruct",
"provider": "bedrock",
"family": "llama",
- "created_at": "2024-09-25 00:00:00 +0530",
+ "created_at": "2024-09-25 00:00:00 UTC",
"context_window": 131000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -3253,12 +13423,65 @@
"knowledge": "2023-12"
}
},
+ {
+ "id": "meta.llama3-2-1b-instruct-v1:0:128k",
+ "name": "Llama 3.2 1B Instruct",
+ "provider": "bedrock",
+ "family": "llama",
+ "created_at": "2024-09-25 00:00:00 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "output": [
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+ "capabilities": [
+ "function_calling",
+ "streaming"
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+ "pricing": {
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+ "output_per_million": 0.1
+ }
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+ "metadata": {
+ "provider_name": "Meta",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/meta.llama3-2-1b-instruct-v1:0:128k",
+ "inference_types": [
+ "PROVISIONED"
+ ],
+ "converse": {},
+ "source": "models.dev",
+ "provider_id": "amazon-bedrock",
+ "open_weights": true,
+ "attachment": false,
+ "temperature": true,
+ "last_updated": "2024-09-25",
+ "cost": {
+ "input": 0.1,
+ "output": 0.1
+ },
+ "limit": {
+ "context": 131000,
+ "output": 4096
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+ "knowledge": "2023-12"
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{
"id": "meta.llama3-2-3b-instruct-v1:0",
"name": "Llama 3.2 3B Instruct",
"provider": "bedrock",
"family": "llama",
- "created_at": "2024-09-25 00:00:00 +0530",
+ "created_at": "2024-09-25 00:00:00 UTC",
"context_window": 131000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -3299,12 +13522,65 @@
"knowledge": "2023-12"
}
},
+ {
+ "id": "meta.llama3-2-3b-instruct-v1:0:128k",
+ "name": "Llama 3.2 3B Instruct",
+ "provider": "bedrock",
+ "family": "llama",
+ "created_at": "2024-09-25 00:00:00 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "capabilities": [
+ "function_calling",
+ "streaming"
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+ "output_per_million": 0.15
+ }
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+ "metadata": {
+ "provider_name": "Meta",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/meta.llama3-2-3b-instruct-v1:0:128k",
+ "inference_types": [
+ "PROVISIONED"
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+ "converse": {},
+ "source": "models.dev",
+ "provider_id": "amazon-bedrock",
+ "open_weights": true,
+ "attachment": false,
+ "temperature": true,
+ "last_updated": "2024-09-25",
+ "cost": {
+ "input": 0.15,
+ "output": 0.15
+ },
+ "limit": {
+ "context": 131000,
+ "output": 4096
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+ "knowledge": "2023-12"
+ }
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{
"id": "meta.llama3-2-90b-instruct-v1:0",
"name": "Llama 3.2 90B Instruct",
"provider": "bedrock",
"family": "llama",
- "created_at": "2024-09-25 00:00:00 +0530",
+ "created_at": "2024-09-25 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -3347,12 +13623,67 @@
"knowledge": "2023-12"
}
},
+ {
+ "id": "meta.llama3-2-90b-instruct-v1:0:128k",
+ "name": "Llama 3.2 90B Instruct",
+ "provider": "bedrock",
+ "family": "llama",
+ "created_at": "2024-09-25 00:00:00 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
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+ "image"
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+ "output": [
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+ "capabilities": [
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+ "vision",
+ "streaming"
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+ "output_per_million": 0.72
+ }
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+ },
+ "metadata": {
+ "provider_name": "Meta",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/meta.llama3-2-90b-instruct-v1:0:128k",
+ "inference_types": [
+ "PROVISIONED"
+ ],
+ "converse": {},
+ "source": "models.dev",
+ "provider_id": "amazon-bedrock",
+ "open_weights": true,
+ "attachment": true,
+ "temperature": true,
+ "last_updated": "2024-09-25",
+ "cost": {
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+ "output": 0.72
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+ "limit": {
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+ "output": 4096
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+ "knowledge": "2023-12"
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{
"id": "meta.llama3-3-70b-instruct-v1:0",
"name": "Llama 3.3 70B Instruct",
"provider": "bedrock",
"family": "llama",
- "created_at": "2024-12-06 00:00:00 +0530",
+ "created_at": "2024-12-06 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -3393,12 +13724,125 @@
"knowledge": "2023-12"
}
},
+ {
+ "id": "meta.llama3-3-70b-instruct-v1:0:128k",
+ "name": "Llama 3.3 70B Instruct",
+ "provider": "bedrock",
+ "family": "llama",
+ "created_at": "2024-12-06 00:00:00 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "output": [
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+ "capabilities": [
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+ "streaming"
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+ "text_tokens": {
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+ "output_per_million": 0.72
+ }
+ }
+ },
+ "metadata": {
+ "provider_name": "Meta",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/meta.llama3-3-70b-instruct-v1:0:128k",
+ "inference_types": [],
+ "converse": {},
+ "source": "models.dev",
+ "provider_id": "amazon-bedrock",
+ "open_weights": true,
+ "attachment": false,
+ "temperature": true,
+ "last_updated": "2024-12-06",
+ "cost": {
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+ "output": 0.72
+ },
+ "limit": {
+ "context": 128000,
+ "output": 4096
+ },
+ "knowledge": "2023-12"
+ }
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+ {
+ "id": "meta.llama3-70b-instruct-v1:0",
+ "name": "Llama 3 70B Instruct",
+ "provider": "bedrock",
+ "family": "meta",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
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+ "output": [
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+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Meta",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/meta.llama3-70b-instruct-v1:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {}
+ }
+ },
+ {
+ "id": "meta.llama3-8b-instruct-v1:0",
+ "name": "Llama 3 8B Instruct",
+ "provider": "bedrock",
+ "family": "meta",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "output": [
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+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Meta",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/meta.llama3-8b-instruct-v1:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {}
+ }
+ },
{
"id": "meta.llama4-maverick-17b-instruct-v1:0",
"name": "Llama 4 Maverick 17B Instruct",
"provider": "bedrock",
"family": "llama",
- "created_at": "2025-04-05 00:00:00 +0530",
+ "created_at": "2025-04-05 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 16384,
"knowledge_cutoff": null,
@@ -3446,7 +13890,7 @@
"name": "Llama 4 Scout 17B Instruct",
"provider": "bedrock",
"family": "llama",
- "created_at": "2025-04-05 00:00:00 +0530",
+ "created_at": "2025-04-05 00:00:00 UTC",
"context_window": 3500000,
"max_output_tokens": 16384,
"knowledge_cutoff": null,
@@ -3494,7 +13938,7 @@
"name": "MiniMax M2",
"provider": "bedrock",
"family": "minimax",
- "created_at": "2025-10-27 00:00:00 +0530",
+ "created_at": "2025-10-27 00:00:00 UTC",
"context_window": 204608,
"max_output_tokens": 128000,
"knowledge_cutoff": null,
@@ -3508,7 +13952,8 @@
},
"capabilities": [
"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -3519,6 +13964,24 @@
}
},
"metadata": {
+ "provider_name": "MiniMax",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/minimax.minimax-m2",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
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+ "maxTokensDefault": null,
+ "maxTokensMaximum": 409600,
+ "reasoningSupported": {
+ "embedded": true
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+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -3540,7 +14003,7 @@
"name": "MiniMax M2.1",
"provider": "bedrock",
"family": "minimax",
- "created_at": "2025-12-23 00:00:00 +0530",
+ "created_at": "2025-12-23 00:00:00 UTC",
"context_window": 204800,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -3554,7 +14017,8 @@
},
"capabilities": [
"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -3565,6 +14029,24 @@
}
},
"metadata": {
+ "provider_name": "MiniMax",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/minimax.minimax-m2.1",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "{\"reasoningConfig\":{\"enabled\":{\"type\":\"boolean\",\"default\":false}}}",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 196608,
+ "reasoningSupported": {
+ "embedded": true
+ },
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -3586,7 +14068,7 @@
"name": "MiniMax M2.5",
"provider": "bedrock",
"family": "minimax",
- "created_at": "2026-03-18 00:00:00 +0530",
+ "created_at": "2026-03-18 00:00:00 UTC",
"context_window": 196608,
"max_output_tokens": 98304,
"knowledge_cutoff": null,
@@ -3600,7 +14082,8 @@
},
"capabilities": [
"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -3611,6 +14094,24 @@
}
},
"metadata": {
+ "provider_name": "MiniMax",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/minimax.minimax-m2.5",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "{\"reasoningConfig\":{\"enabled\":{\"type\":\"boolean\",\"default\":false}}}",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 196608,
+ "reasoningSupported": {
+ "embedded": true
+ },
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -3632,7 +14133,7 @@
"name": "Devstral 2 123B",
"provider": "bedrock",
"family": "devstral",
- "created_at": "2026-02-17 00:00:00 +0530",
+ "created_at": "2026-02-17 00:00:00 UTC",
"context_window": 256000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -3645,7 +14146,8 @@
]
},
"capabilities": [
- "function_calling"
+ "function_calling",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -3656,6 +14158,22 @@
}
},
"metadata": {
+ "provider_name": "Mistral AI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/mistral.devstral-2-123b",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "{}",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 262144,
+ "reasoningSupported": null,
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -3677,7 +14195,7 @@
"name": "Magistral Small 1.2",
"provider": "bedrock",
"family": "magistral",
- "created_at": "2025-12-02 00:00:00 +0530",
+ "created_at": "2025-12-02 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 40000,
"knowledge_cutoff": null,
@@ -3694,7 +14212,8 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -3705,6 +14224,29 @@
}
},
"metadata": {
+ "provider_name": "Mistral AI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/mistral.magistral-small-2509",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "{\"reasoningConfig\":{\"enabled\":{\"type\":\"boolean\",\"default\":false}}}",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 131072,
+ "reasoningSupported": {
+ "embedded": true
+ },
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [
+ "png",
+ "jpeg",
+ "gif",
+ "webp"
+ ],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -3726,7 +14268,7 @@
"name": "Ministral 14B 3.0",
"provider": "bedrock",
"family": "ministral",
- "created_at": "2024-12-01 00:00:00 +0530",
+ "created_at": "2024-12-01 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -3740,7 +14282,8 @@
},
"capabilities": [
"function_calling",
- "structured_output"
+ "structured_output",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -3751,6 +14294,27 @@
}
},
"metadata": {
+ "provider_name": "Mistral AI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/mistral.ministral-3-14b-instruct",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "{}",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 262144,
+ "reasoningSupported": null,
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [
+ "png",
+ "jpeg",
+ "gif",
+ "webp"
+ ],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": false,
@@ -3772,7 +14336,7 @@
"name": "Ministral 3 3B",
"provider": "bedrock",
"family": "ministral",
- "created_at": "2025-12-02 00:00:00 +0530",
+ "created_at": "2025-12-02 00:00:00 UTC",
"context_window": 256000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -3788,7 +14352,8 @@
"capabilities": [
"function_calling",
"structured_output",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -3799,6 +14364,27 @@
}
},
"metadata": {
+ "provider_name": "Mistral AI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/mistral.ministral-3-3b-instruct",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "{}",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 262144,
+ "reasoningSupported": null,
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [
+ "png",
+ "jpeg",
+ "gif",
+ "webp"
+ ],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -3820,7 +14406,7 @@
"name": "Ministral 3 8B",
"provider": "bedrock",
"family": "ministral",
- "created_at": "2024-12-01 00:00:00 +0530",
+ "created_at": "2024-12-01 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -3834,7 +14420,8 @@
},
"capabilities": [
"function_calling",
- "structured_output"
+ "structured_output",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -3845,6 +14432,27 @@
}
},
"metadata": {
+ "provider_name": "Mistral AI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/mistral.ministral-3-8b-instruct",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "{}",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 262144,
+ "reasoningSupported": null,
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [
+ "png",
+ "jpeg",
+ "gif",
+ "webp"
+ ],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": false,
@@ -3861,12 +14469,105 @@
}
}
},
+ {
+ "id": "mistral.mistral-7b-instruct-v0:2",
+ "name": "Mistral 7B Instruct",
+ "provider": "bedrock",
+ "family": "mistral ai",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "text"
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+ "output": [
+ "text"
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+ },
+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Mistral AI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/mistral.mistral-7b-instruct-v0:2",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {}
+ }
+ },
+ {
+ "id": "mistral.mistral-large-2402-v1:0",
+ "name": "Mistral Large (24.02)",
+ "provider": "bedrock",
+ "family": "mistral ai",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Mistral AI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/mistral.mistral-large-2402-v1:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {}
+ }
+ },
+ {
+ "id": "mistral.mistral-large-2407-v1:0",
+ "name": "Mistral Large (24.07)",
+ "provider": "bedrock",
+ "family": "mistral ai",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "capabilities": [
+ "streaming",
+ "function_calling"
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+ "pricing": {},
+ "metadata": {
+ "provider_name": "Mistral AI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/mistral.mistral-large-2407-v1:0",
+ "inference_types": [
+ "ON_DEMAND"
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+ "converse": {}
+ }
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{
"id": "mistral.mistral-large-3-675b-instruct",
"name": "Mistral Large 3",
"provider": "bedrock",
"family": "mistral",
- "created_at": "2025-12-02 00:00:00 +0530",
+ "created_at": "2025-12-02 00:00:00 UTC",
"context_window": 256000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -3882,7 +14583,8 @@
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+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -3893,6 +14595,27 @@
}
},
"metadata": {
+ "provider_name": "Mistral AI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/mistral.mistral-large-3-675b-instruct",
+ "inference_types": [
+ "ON_DEMAND"
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+ "userImageTypesSupported": [
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+ "gif",
+ "webp"
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+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -3909,12 +14632,43 @@
}
}
},
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+ "name": "Mixtral 8x7B Instruct",
+ "provider": "bedrock",
+ "family": "mistral ai",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "capabilities": [
+ "streaming",
+ "function_calling"
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+ "pricing": {},
+ "metadata": {
+ "provider_name": "Mistral AI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/mistral.mixtral-8x7b-instruct-v0:1",
+ "inference_types": [
+ "ON_DEMAND"
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{
"id": "mistral.pixtral-large-2502-v1:0",
"name": "Pixtral Large (25.02)",
"provider": "bedrock",
"family": "mistral",
- "created_at": "2025-04-08 00:00:00 +0530",
+ "created_at": "2025-04-08 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -3961,7 +14715,7 @@
"name": "Voxtral Mini 3B 2507",
"provider": "bedrock",
"family": "mistral",
- "created_at": "2024-12-01 00:00:00 +0530",
+ "created_at": "2024-12-01 00:00:00 UTC",
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"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -3976,7 +14730,8 @@
},
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+ "structured_output",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -3987,6 +14742,22 @@
}
},
"metadata": {
+ "provider_name": "Mistral AI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/mistral.voxtral-mini-3b-2507",
+ "inference_types": [
+ "ON_DEMAND"
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+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
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"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": false,
@@ -4008,7 +14779,7 @@
"name": "Voxtral Small 24B 2507",
"provider": "bedrock",
"family": "mistral",
- "created_at": "2025-07-01 00:00:00 +0530",
+ "created_at": "2025-07-01 00:00:00 UTC",
"context_window": 32000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -4023,7 +14794,8 @@
},
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+ "structured_output",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -4034,6 +14806,22 @@
}
},
"metadata": {
+ "provider_name": "Mistral AI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/mistral.voxtral-small-24b-2507",
+ "inference_types": [
+ "ON_DEMAND"
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+ "stopSequencesDefault": [],
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+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
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"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -4055,7 +14843,7 @@
"name": "Kimi K2 Thinking",
"provider": "bedrock",
"family": "kimi-thinking",
- "created_at": "2025-12-02 00:00:00 +0530",
+ "created_at": "2025-12-02 00:00:00 UTC",
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"knowledge_cutoff": null,
@@ -4070,7 +14858,8 @@
"capabilities": [
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"structured_output",
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+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -4081,6 +14870,24 @@
}
},
"metadata": {
+ "provider_name": "Moonshot AI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/moonshot.kimi-k2-thinking",
+ "inference_types": [
+ "ON_DEMAND"
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+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
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"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -4103,7 +14910,7 @@
"name": "Kimi K2.5",
"provider": "bedrock",
"family": "kimi",
- "created_at": "2026-02-06 00:00:00 +0530",
+ "created_at": "2026-02-06 00:00:00 UTC",
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"max_output_tokens": 256000,
"knowledge_cutoff": null,
@@ -4119,7 +14926,8 @@
"capabilities": [
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- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -4130,6 +14938,29 @@
}
},
"metadata": {
+ "provider_name": "Moonshot AI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/moonshotai.kimi-k2.5",
+ "inference_types": [
+ "ON_DEMAND"
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+ "converse": {
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+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [
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+ "png",
+ "gif",
+ "webp"
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+ "userVideoTypesSupported": []
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"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -4152,7 +14983,7 @@
"name": "NVIDIA Nemotron Nano 12B v2 VL BF16",
"provider": "bedrock",
"family": "nemotron",
- "created_at": "2024-12-01 00:00:00 +0530",
+ "created_at": "2024-12-01 00:00:00 UTC",
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@@ -4168,7 +14999,8 @@
"capabilities": [
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- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -4179,6 +15011,27 @@
}
},
"metadata": {
+ "provider_name": "NVIDIA",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/nvidia.nemotron-nano-12b-v2",
+ "inference_types": [
+ "ON_DEMAND"
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+ "gif",
+ "webp"
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+ "userVideoTypesSupported": []
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"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": false,
@@ -4200,7 +15053,7 @@
"name": "NVIDIA Nemotron Nano 3 30B",
"provider": "bedrock",
"family": "nemotron",
- "created_at": "2025-12-23 00:00:00 +0530",
+ "created_at": "2025-12-23 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -4214,7 +15067,8 @@
},
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- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -4225,6 +15079,24 @@
}
},
"metadata": {
+ "provider_name": "NVIDIA",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/nvidia.nemotron-nano-3-30b",
+ "inference_types": [
+ "ON_DEMAND"
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+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
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"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -4246,7 +15118,7 @@
"name": "NVIDIA Nemotron Nano 9B v2",
"provider": "bedrock",
"family": "nemotron",
- "created_at": "2024-12-01 00:00:00 +0530",
+ "created_at": "2024-12-01 00:00:00 UTC",
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"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -4260,7 +15132,8 @@
},
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- "structured_output"
+ "structured_output",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -4271,6 +15144,22 @@
}
},
"metadata": {
+ "provider_name": "NVIDIA",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/nvidia.nemotron-nano-9b-v2",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
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+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": false,
@@ -4292,7 +15181,7 @@
"name": "NVIDIA Nemotron 3 Super 120B A12B",
"provider": "bedrock",
"family": "nemotron",
- "created_at": "2026-03-11 00:00:00 +0530",
+ "created_at": "2026-03-11 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -4306,7 +15195,8 @@
},
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"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -4317,6 +15207,22 @@
}
},
"metadata": {
+ "provider_name": "NVIDIA",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/nvidia.nemotron-super-3-120b",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
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+ "maxTokensDefault": null,
+ "maxTokensMaximum": 262144,
+ "reasoningSupported": null,
+ "stopSequencesDefault": [],
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+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -4338,7 +15244,7 @@
"name": "gpt-oss-120b",
"provider": "bedrock",
"family": "gpt-oss",
- "created_at": "2024-12-01 00:00:00 +0530",
+ "created_at": "2024-12-01 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -4352,7 +15258,8 @@
},
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- "structured_output"
+ "structured_output",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -4363,6 +15270,24 @@
}
},
"metadata": {
+ "provider_name": "OpenAI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/openai.gpt-oss-120b-1:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": null,
+ "maxTokensDefault": 4096,
+ "maxTokensMaximum": 128000,
+ "reasoningSupported": {
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+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": false,
@@ -4384,7 +15309,7 @@
"name": "gpt-oss-20b",
"provider": "bedrock",
"family": "gpt-oss",
- "created_at": "2024-12-01 00:00:00 +0530",
+ "created_at": "2024-12-01 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -4398,7 +15323,8 @@
},
"capabilities": [
"function_calling",
- "structured_output"
+ "structured_output",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -4409,6 +15335,24 @@
}
},
"metadata": {
+ "provider_name": "OpenAI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/openai.gpt-oss-20b-1:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": null,
+ "maxTokensDefault": 4096,
+ "maxTokensMaximum": 128000,
+ "reasoningSupported": {
+ "embedded": false
+ },
+ "stopSequencesDefault": null,
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": false,
@@ -4430,7 +15374,7 @@
"name": "GPT OSS Safeguard 120B",
"provider": "bedrock",
"family": "gpt-oss",
- "created_at": "2024-12-01 00:00:00 +0530",
+ "created_at": "2024-12-01 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -4444,7 +15388,9 @@
},
"capabilities": [
"function_calling",
- "structured_output"
+ "structured_output",
+ "streaming",
+ "reasoning"
],
"pricing": {
"text_tokens": {
@@ -4455,6 +15401,24 @@
}
},
"metadata": {
+ "provider_name": "OpenAI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/openai.gpt-oss-safeguard-120b",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "{\"reasoningConfig\":{\"enabled\":{\"type\":\"boolean\",\"default\":false}}}",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 131072,
+ "reasoningSupported": {
+ "embedded": true
+ },
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": false,
@@ -4476,7 +15440,7 @@
"name": "GPT OSS Safeguard 20B",
"provider": "bedrock",
"family": "gpt-oss",
- "created_at": "2024-12-01 00:00:00 +0530",
+ "created_at": "2024-12-01 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -4490,7 +15454,9 @@
},
"capabilities": [
"function_calling",
- "structured_output"
+ "structured_output",
+ "streaming",
+ "reasoning"
],
"pricing": {
"text_tokens": {
@@ -4501,6 +15467,24 @@
}
},
"metadata": {
+ "provider_name": "OpenAI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/openai.gpt-oss-safeguard-20b",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "{\"reasoningConfig\":{\"enabled\":{\"type\":\"boolean\",\"default\":false}}}",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 131072,
+ "reasoningSupported": {
+ "embedded": true
+ },
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": false,
@@ -4522,7 +15506,7 @@
"name": "Qwen3 235B A22B 2507",
"provider": "bedrock",
"family": "qwen",
- "created_at": "2025-09-18 00:00:00 +0530",
+ "created_at": "2025-09-18 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -4536,7 +15520,8 @@
},
"capabilities": [
"function_calling",
- "structured_output"
+ "structured_output",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -4547,6 +15532,22 @@
}
},
"metadata": {
+ "provider_name": "Qwen",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/qwen.qwen3-235b-a22b-2507-v1:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 262144,
+ "reasoningSupported": null,
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -4569,7 +15570,7 @@
"name": "Qwen3 32B (dense)",
"provider": "bedrock",
"family": "qwen",
- "created_at": "2025-09-18 00:00:00 +0530",
+ "created_at": "2025-09-18 00:00:00 UTC",
"context_window": 16384,
"max_output_tokens": 16384,
"knowledge_cutoff": null,
@@ -4584,7 +15585,8 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -4595,6 +15597,24 @@
}
},
"metadata": {
+ "provider_name": "Qwen",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/qwen.qwen3-32b-v1:0",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "{\"reasoningConfig\":{\"enabled\":{\"type\":\"boolean\",\"default\":true}}}",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 32768,
+ "reasoningSupported": {
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+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -4617,7 +15637,7 @@
"name": "Qwen3 Coder 30B A3B Instruct",
"provider": "bedrock",
"family": "qwen",
- "created_at": "2025-09-18 00:00:00 +0530",
+ "created_at": "2025-09-18 00:00:00 UTC",
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"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -4631,7 +15651,8 @@
},
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"function_calling",
- "structured_output"
+ "structured_output",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -4642,6 +15663,22 @@
}
},
"metadata": {
+ "provider_name": "Qwen",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/qwen.qwen3-coder-30b-a3b-v1:0",
+ "inference_types": [
+ "ON_DEMAND"
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+ "converse": {
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+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": false,
@@ -4664,7 +15701,7 @@
"name": "Qwen3 Coder 480B A35B Instruct",
"provider": "bedrock",
"family": "qwen",
- "created_at": "2025-09-18 00:00:00 +0530",
+ "created_at": "2025-09-18 00:00:00 UTC",
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@@ -4678,7 +15715,8 @@
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- "structured_output"
+ "structured_output",
+ "streaming"
],
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"text_tokens": {
@@ -4689,6 +15727,22 @@
}
},
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+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/qwen.qwen3-coder-480b-a35b-v1:0",
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"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -4711,7 +15765,7 @@
"name": "Qwen3 Coder Next",
"provider": "bedrock",
"family": "qwen",
- "created_at": "2026-02-06 00:00:00 +0530",
+ "created_at": "2026-02-06 00:00:00 UTC",
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@@ -4758,7 +15812,7 @@
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"provider": "bedrock",
"family": "qwen",
- "created_at": "2025-09-18 00:00:00 +0530",
+ "created_at": "2025-09-18 00:00:00 UTC",
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@@ -4772,7 +15826,8 @@
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+ "structured_output",
+ "streaming"
],
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@@ -4783,6 +15838,24 @@
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@@ -4804,7 +15877,7 @@
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"provider": "bedrock",
"family": "qwen",
- "created_at": "2025-10-04 00:00:00 +0530",
+ "created_at": "2025-10-04 00:00:00 UTC",
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"knowledge_cutoff": null,
@@ -4820,7 +15893,8 @@
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"structured_output",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
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@@ -4831,6 +15905,29 @@
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"metadata": {
+ "provider_name": "Qwen",
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+ "ON_DEMAND"
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"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": false,
@@ -4847,12 +15944,444 @@
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+ "name": "Nova Pro",
+ "provider": "bedrock",
+ "family": "nova-pro",
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+ "context_window": 300000,
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+ "pdf",
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+ "jpeg",
+ "png",
+ "gif",
+ "webp"
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+ "userVideoTypesSupported": [
+ "mkv",
+ "mov",
+ "mp4",
+ "webm",
+ "flv",
+ "mpeg",
+ "mpg",
+ "wmv",
+ "three_gp"
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+ "attachment": true,
+ "temperature": true,
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{
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"name": "Claude Haiku 4.5 (US)",
"provider": "bedrock",
"family": "claude-haiku",
- "created_at": "2025-10-15 00:00:00 +0530",
+ "created_at": "2025-10-15 00:00:00 UTC",
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"knowledge_cutoff": "2025-02-28",
@@ -4870,18 +16399,45 @@
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"output_per_million": 5,
- "cached_input_per_million": 0.1
+ "cache_read_input_per_million": 0.1,
+ "cache_write_input_per_million": 1.25
}
}
},
"metadata": {
+ "provider_name": "Anthropic",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-haiku-4-5-20251001-v1:0",
+ "inference_types": [
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+ "webp"
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"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": false,
@@ -4906,7 +16462,7 @@
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"family": "claude-opus",
- "created_at": "2025-08-05 00:00:00 +0530",
+ "created_at": "2025-08-05 00:00:00 UTC",
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@@ -4923,18 +16479,45 @@
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+ "vision",
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- "cached_input_per_million": 1.5
+ "cache_read_input_per_million": 1.5,
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}
}
},
"metadata": {
+ "provider_name": "Anthropic",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-opus-4-1-20250805-v1:0",
+ "inference_types": [
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"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": false,
@@ -4959,10 +16542,10 @@
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"family": "claude-opus",
- "created_at": "2025-05-22 00:00:00 +0530",
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- "knowledge_cutoff": null,
+ "knowledge_cutoff": "2025-03-31",
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@@ -4976,18 +16559,26 @@
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+ "vision",
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- "cached_input_per_million": 1.5
+ "cache_read_input_per_million": 1.5,
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}
}
},
"metadata": {
+ "provider_name": "Anthropic",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-opus-4-20250514-v1:0",
+ "inference_types": [
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+ "converse": {},
"source": "models.dev",
"provider_id": "amazon-bedrock",
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@@ -5004,7 +16595,7 @@
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},
- "knowledge": "2024-04"
+ "knowledge": "2025-03-31"
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},
{
@@ -5012,7 +16603,7 @@
"name": "Claude Opus 4.5 (US)",
"provider": "bedrock",
"family": "claude-opus",
- "created_at": "2025-11-24 00:00:00 +0530",
+ "created_at": "2025-11-24 00:00:00 UTC",
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"knowledge_cutoff": "2025-03-31",
@@ -5030,18 +16621,45 @@
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+ "cache_write_input_per_million": 6.25
}
}
},
"metadata": {
+ "provider_name": "Anthropic",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-opus-4-5-20251101-v1:0",
+ "inference_types": [
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+ "userDocumentTypesSupported": [
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+ "userImageTypesSupported": [
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"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": false,
@@ -5066,10 +16684,10 @@
"name": "Claude Opus 4.6 (US)",
"provider": "bedrock",
"family": "claude-opus",
- "created_at": "2026-02-05 00:00:00 +0530",
+ "created_at": "2026-02-05 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 128000,
- "knowledge_cutoff": null,
+ "knowledge_cutoff": "2025-05-31",
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@@ -5084,24 +16702,51 @@
"function_calling",
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+ "vision",
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@@ -5112,7 +16757,88 @@
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@@ -5120,10 +16846,10 @@
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@@ -5137,18 +16863,45 @@
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@@ -5165,7 +16918,7 @@
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@@ -5191,18 +16944,45 @@
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@@ -5227,10 +17007,10 @@
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@@ -5244,24 +17024,52 @@
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@@ -5272,7 +17080,1113 @@
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+ "family": "palmyra",
+ "created_at": "2025-04-28 00:00:00 UTC",
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+ {
+ "id": "us.writer.palmyra-x5-v1:0",
+ "name": "Palmyra X5",
+ "provider": "bedrock",
+ "family": "palmyra",
+ "created_at": "2025-04-28 00:00:00 UTC",
+ "context_window": 1040000,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "capabilities": [
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+ "reasoning",
+ "streaming"
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+ "pricing": {
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+ "output_per_million": 6
+ }
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+ "metadata": {
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+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/writer.palmyra-x5-v1:0",
+ "inference_types": [
+ "INFERENCE_PROFILE"
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+ "converse": {},
+ "source": "models.dev",
+ "provider_id": "amazon-bedrock",
+ "open_weights": false,
+ "attachment": false,
+ "temperature": true,
+ "last_updated": "2025-04-28",
+ "cost": {
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+ "output": 6
+ },
+ "limit": {
+ "context": 1040000,
+ "output": 8192
+ }
+ }
+ },
+ {
+ "id": "writer.palmyra-vision-7b",
+ "name": "Writer Palmyra Vision 7B",
+ "provider": "bedrock",
+ "family": "Writer Palmyra Vision",
+ "created_at": null,
+ "context_window": null,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
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+ "image"
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+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "provider_name": "Writer",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/writer.palmyra-vision-7b",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
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+ "maxTokensDefault": null,
+ "maxTokensMaximum": 4096,
+ "reasoningSupported": null,
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [
+ "jpeg",
+ "png",
+ "gif",
+ "webp"
+ ],
+ "userVideoTypesSupported": []
+ }
}
},
{
@@ -5280,7 +18194,7 @@
"name": "Palmyra X4",
"provider": "bedrock",
"family": "palmyra",
- "created_at": "2025-04-28 00:00:00 +0530",
+ "created_at": "2025-04-28 00:00:00 UTC",
"context_window": 122880,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -5326,7 +18240,7 @@
"name": "Palmyra X5",
"provider": "bedrock",
"family": "palmyra",
- "created_at": "2025-04-28 00:00:00 +0530",
+ "created_at": "2025-04-28 00:00:00 UTC",
"context_window": 1040000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -5372,7 +18286,7 @@
"name": "GLM-4.7",
"provider": "bedrock",
"family": "glm",
- "created_at": "2025-12-22 00:00:00 +0530",
+ "created_at": "2025-12-22 00:00:00 UTC",
"context_window": 204800,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -5386,7 +18300,8 @@
},
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"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -5397,6 +18312,24 @@
}
},
"metadata": {
+ "provider_name": "Z.AI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/zai.glm-4.7",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "{\"reasoningConfig\":{\"enabled\":{\"type\":\"boolean\",\"default\":false}}}",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 202752,
+ "reasoningSupported": {
+ "embedded": false
+ },
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -5422,7 +18355,7 @@
"name": "GLM-4.7-Flash",
"provider": "bedrock",
"family": "glm-flash",
- "created_at": "2026-01-19 00:00:00 +0530",
+ "created_at": "2026-01-19 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -5436,7 +18369,8 @@
},
"capabilities": [
"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -5447,6 +18381,24 @@
}
},
"metadata": {
+ "provider_name": "Z.AI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/zai.glm-4.7-flash",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "{\"reasoningConfig\":{\"enabled\":{\"type\":\"boolean\",\"default\":false}}}",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 202752,
+ "reasoningSupported": {
+ "embedded": false
+ },
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -5469,7 +18421,7 @@
"name": "GLM-5",
"provider": "bedrock",
"family": "glm",
- "created_at": "2026-03-18 00:00:00 +0530",
+ "created_at": "2026-03-18 00:00:00 UTC",
"context_window": 202752,
"max_output_tokens": 101376,
"knowledge_cutoff": null,
@@ -5483,7 +18435,8 @@
},
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"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -5494,6 +18447,24 @@
}
},
"metadata": {
+ "provider_name": "Z.AI",
+ "model_arn": "arn:aws:bedrock:us-west-2::foundation-model/zai.glm-5",
+ "inference_types": [
+ "ON_DEMAND"
+ ],
+ "converse": {
+ "additionalRequestFieldsSchema": "{\"reasoningConfig\":{\"enabled\":{\"type\":\"boolean\",\"default\":false}}}",
+ "maxTokensDefault": null,
+ "maxTokensMaximum": 202752,
+ "reasoningSupported": {
+ "embedded": false
+ },
+ "stopSequencesDefault": [],
+ "systemRoleSupported": true,
+ "userDocumentTypesSupported": [],
+ "userImageTypesSupported": [],
+ "userVideoTypesSupported": []
+ },
"source": "models.dev",
"provider_id": "amazon-bedrock",
"open_weights": true,
@@ -5518,9 +18489,9 @@
"name": "DeepSeek Chat",
"provider": "deepseek",
"family": "deepseek",
- "created_at": "2025-12-01 00:00:00 +0530",
- "context_window": 131072,
- "max_output_tokens": 8192,
+ "created_at": "2025-12-01 00:00:00 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 384000,
"knowledge_cutoff": null,
"modalities": {
"input": [
@@ -5536,9 +18507,9 @@
"pricing": {
"text_tokens": {
"standard": {
- "input_per_million": 0.28,
- "output_per_million": 0.42,
- "cached_input_per_million": 0.028
+ "input_per_million": 0.14,
+ "output_per_million": 0.28,
+ "cache_read_input_per_million": 0.028
}
}
},
@@ -5550,13 +18521,13 @@
"temperature": true,
"last_updated": "2026-02-28",
"cost": {
- "input": 0.28,
- "output": 0.42,
+ "input": 0.14,
+ "output": 0.28,
"cache_read": 0.028
},
"limit": {
- "context": 131072,
- "output": 8192
+ "context": 1000000,
+ "output": 384000
},
"knowledge": "2025-09"
}
@@ -5566,9 +18537,9 @@
"name": "DeepSeek Reasoner",
"provider": "deepseek",
"family": "deepseek-thinking",
- "created_at": "2025-12-01 00:00:00 +0530",
- "context_window": 128000,
- "max_output_tokens": 64000,
+ "created_at": "2025-12-01 00:00:00 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 384000,
"knowledge_cutoff": null,
"modalities": {
"input": [
@@ -5585,9 +18556,9 @@
"pricing": {
"text_tokens": {
"standard": {
- "input_per_million": 0.28,
- "output_per_million": 0.42,
- "cached_input_per_million": 0.028
+ "input_per_million": 0.14,
+ "output_per_million": 0.28,
+ "cache_read_input_per_million": 0.028
}
}
},
@@ -5602,23 +18573,249 @@
"field": "reasoning_content"
},
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- "input": 0.28,
- "output": 0.42,
+ "input": 0.14,
+ "output": 0.28,
"cache_read": 0.028
},
"limit": {
- "context": 128000,
- "output": 64000
+ "context": 1000000,
+ "output": 384000
},
"knowledge": "2025-09"
}
},
+ {
+ "id": "deepseek-v4-flash",
+ "name": "DeepSeek V4 Flash",
+ "provider": "deepseek",
+ "family": "deepseek-flash",
+ "created_at": "2026-04-24 00:00:00 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 384000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "reasoning"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.14,
+ "output_per_million": 0.28,
+ "cache_read_input_per_million": 0.028
+ }
+ }
+ },
+ "metadata": {
+ "source": "models.dev",
+ "provider_id": "deepseek",
+ "open_weights": true,
+ "attachment": false,
+ "temperature": true,
+ "last_updated": "2026-04-24",
+ "interleaved": {
+ "field": "reasoning_content"
+ },
+ "cost": {
+ "input": 0.14,
+ "output": 0.28,
+ "cache_read": 0.028
+ },
+ "limit": {
+ "context": 1000000,
+ "output": 384000
+ },
+ "knowledge": "2025-05"
+ }
+ },
+ {
+ "id": "deepseek-v4-pro",
+ "name": "DeepSeek V4 Pro",
+ "provider": "deepseek",
+ "family": "deepseek-thinking",
+ "created_at": "2026-04-24 00:00:00 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 384000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "reasoning"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 1.74,
+ "output_per_million": 3.48,
+ "cache_read_input_per_million": 0.145
+ }
+ }
+ },
+ "metadata": {
+ "source": "models.dev",
+ "provider_id": "deepseek",
+ "open_weights": true,
+ "attachment": false,
+ "temperature": true,
+ "last_updated": "2026-04-24",
+ "interleaved": {
+ "field": "reasoning_content"
+ },
+ "cost": {
+ "input": 1.74,
+ "output": 3.48,
+ "cache_read": 0.145
+ },
+ "limit": {
+ "context": 1000000,
+ "output": 384000
+ },
+ "knowledge": "2025-05"
+ }
+ },
+ {
+ "id": "aqa",
+ "name": "Model that performs Attributed Question Answering.",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 7168,
+ "max_output_tokens": 1024,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [],
+ "pricing": {},
+ "metadata": {
+ "version": "001",
+ "description": "Model trained to return answers to questions that are grounded in provided sources, along with estimating answerable probability.",
+ "supported_generation_methods": [
+ "generateAnswer"
+ ]
+ }
+ },
+ {
+ "id": "deep-research-max-preview-04-2026",
+ "name": "Deep Research Max Preview (Apr-21-2026)",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 131072,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "deepthink-exp-05-20",
+ "description": "Preview release (April 21st, 2026) of Deep Research Max",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens"
+ ]
+ }
+ },
+ {
+ "id": "deep-research-preview-04-2026",
+ "name": "Deep Research Preview (Apr-21-2026)",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 131072,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "deepthink-exp-05-20",
+ "description": "Preview release (April 21th, 2026) of Deep Research",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens"
+ ]
+ }
+ },
+ {
+ "id": "deep-research-pro-preview-12-2025",
+ "name": "Deep Research Pro Preview (Dec-12-2025)",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 131072,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "deepthink-exp-05-20",
+ "description": "Preview release (December 12th, 2025) of Deep Research Pro",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens"
+ ]
+ }
+ },
{
"id": "gemini-1.5-flash",
"name": "Gemini 1.5 Flash",
"provider": "gemini",
"family": "gemini-flash",
- "created_at": "2024-05-14 00:00:00 +0530",
+ "created_at": "2024-05-14 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -5642,7 +18839,7 @@
"standard": {
"input_per_million": 0.075,
"output_per_million": 0.3,
- "cached_input_per_million": 0.01875
+ "cache_read_input_per_million": 0.01875
}
}
},
@@ -5670,7 +18867,7 @@
"name": "Gemini 1.5 Flash-8B",
"provider": "gemini",
"family": "gemini-flash",
- "created_at": "2024-10-03 00:00:00 +0530",
+ "created_at": "2024-10-03 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -5694,7 +18891,7 @@
"standard": {
"input_per_million": 0.0375,
"output_per_million": 0.15,
- "cached_input_per_million": 0.01
+ "cache_read_input_per_million": 0.01
}
}
},
@@ -5722,7 +18919,7 @@
"name": "Gemini 1.5 Pro",
"provider": "gemini",
"family": "gemini-pro",
- "created_at": "2024-02-15 00:00:00 +0530",
+ "created_at": "2024-02-15 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -5746,7 +18943,7 @@
"standard": {
"input_per_million": 1.25,
"output_per_million": 5,
- "cached_input_per_million": 0.3125
+ "cache_read_input_per_million": 0.3125
}
}
},
@@ -5774,7 +18971,7 @@
"name": "Gemini 2.0 Flash",
"provider": "gemini",
"family": "gemini-flash",
- "created_at": "2024-12-11 00:00:00 +0530",
+ "created_at": "2024-12-11 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -5800,11 +18997,19 @@
"standard": {
"input_per_million": 0.1,
"output_per_million": 0.4,
- "cached_input_per_million": 0.025
+ "cache_read_input_per_million": 0.025
}
}
},
"metadata": {
+ "version": "2.0",
+ "description": "Gemini 2.0 Flash",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "createCachedContent",
+ "batchGenerateContent"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": false,
@@ -5823,12 +19028,49 @@
"knowledge": "2024-06"
}
},
+ {
+ "id": "gemini-2.0-flash-001",
+ "name": "Gemini 2.0 Flash 001",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 1048576,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.1,
+ "output_per_million": 0.4
+ }
+ }
+ },
+ "metadata": {
+ "version": "2.0",
+ "description": "Stable version of Gemini 2.0 Flash, our fast and versatile multimodal model for scaling across diverse tasks, released in January of 2025.",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "createCachedContent",
+ "batchGenerateContent"
+ ]
+ }
+ },
{
"id": "gemini-2.0-flash-lite",
"name": "Gemini 2.0 Flash Lite",
"provider": "gemini",
"family": "gemini-flash-lite",
- "created_at": "2024-12-11 00:00:00 +0530",
+ "created_at": "2024-12-11 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -5858,6 +19100,14 @@
}
},
"metadata": {
+ "version": "2.0",
+ "description": "Gemini 2.0 Flash-Lite",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "createCachedContent",
+ "batchGenerateContent"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": false,
@@ -5875,12 +19125,82 @@
"knowledge": "2024-06"
}
},
+ {
+ "id": "gemini-2.0-flash-lite-001",
+ "name": "Gemini 2.0 Flash-Lite 001",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 1048576,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "2.0",
+ "description": "Stable version of Gemini 2.0 Flash-Lite",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "createCachedContent",
+ "batchGenerateContent"
+ ]
+ }
+ },
+ {
+ "id": "gemini-2.5-computer-use-preview-10-2025",
+ "name": "Gemini 2.5 Computer Use Preview 10-2025",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 131072,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "Gemini 2.5 Computer Use Preview 10-2025",
+ "description": "Gemini 2.5 Computer Use Preview 10-2025",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens"
+ ]
+ }
+ },
{
"id": "gemini-2.5-flash",
"name": "Gemini 2.5 Flash",
"provider": "gemini",
"family": "gemini-flash",
- "created_at": "2025-03-20 00:00:00 +0530",
+ "created_at": "2025-03-20 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -5907,7 +19227,7 @@
"standard": {
"input_per_million": 0.3,
"output_per_million": 2.5,
- "cached_input_per_million": 0.075
+ "cache_read_input_per_million": 0.03
}
},
"audio_tokens": {
@@ -5917,6 +19237,14 @@
}
},
"metadata": {
+ "version": "001",
+ "description": "Stable version of Gemini 2.5 Flash, our mid-size multimodal model that supports up to 1 million tokens, released in June of 2025.",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "createCachedContent",
+ "batchGenerateContent"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": false,
@@ -5926,7 +19254,7 @@
"cost": {
"input": 0.3,
"output": 2.5,
- "cache_read": 0.075,
+ "cache_read": 0.03,
"input_audio": 1
},
"limit": {
@@ -5941,7 +19269,7 @@
"name": "Gemini 2.5 Flash Image",
"provider": "gemini",
"family": "gemini-flash",
- "created_at": "2025-08-26 00:00:00 +0530",
+ "created_at": "2025-08-26 00:00:00 UTC",
"context_window": 32768,
"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -5957,18 +19285,27 @@
},
"capabilities": [
"reasoning",
- "vision"
+ "vision",
+ "function_calling",
+ "structured_output"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.3,
"output_per_million": 30,
- "cached_input_per_million": 0.075
+ "cache_read_input_per_million": 0.075
}
}
},
"metadata": {
+ "version": "2.0",
+ "description": "Gemini 2.5 Flash Preview Image",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "batchGenerateContent"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": false,
@@ -5992,7 +19329,7 @@
"name": "Gemini 2.5 Flash Image (Preview)",
"provider": "gemini",
"family": "gemini-flash",
- "created_at": "2025-08-26 00:00:00 +0530",
+ "created_at": "2025-08-26 00:00:00 UTC",
"context_window": 32768,
"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -6015,7 +19352,7 @@
"standard": {
"input_per_million": 0.3,
"output_per_million": 30,
- "cached_input_per_million": 0.075
+ "cache_read_input_per_million": 0.075
}
}
},
@@ -6043,7 +19380,7 @@
"name": "Gemini 2.5 Flash Lite",
"provider": "gemini",
"family": "gemini-flash-lite",
- "created_at": "2025-06-17 00:00:00 +0530",
+ "created_at": "2025-06-17 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -6070,11 +19407,19 @@
"standard": {
"input_per_million": 0.1,
"output_per_million": 0.4,
- "cached_input_per_million": 0.025
+ "cache_read_input_per_million": 0.025
}
}
},
"metadata": {
+ "version": "001",
+ "description": "Stable version of Gemini 2.5 Flash-Lite, released in July of 2025",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "createCachedContent",
+ "batchGenerateContent"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": false,
@@ -6098,7 +19443,7 @@
"name": "Gemini 2.5 Flash Lite Preview 06-17",
"provider": "gemini",
"family": "gemini-flash-lite",
- "created_at": "2025-06-17 00:00:00 +0530",
+ "created_at": "2025-06-17 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -6124,7 +19469,7 @@
"standard": {
"input_per_million": 0.1,
"output_per_million": 0.4,
- "cached_input_per_million": 0.025
+ "cache_read_input_per_million": 0.025
}
},
"audio_tokens": {
@@ -6158,7 +19503,7 @@
"name": "Gemini 2.5 Flash Lite Preview 09-25",
"provider": "gemini",
"family": "gemini-flash-lite",
- "created_at": "2025-09-25 00:00:00 +0530",
+ "created_at": "2025-09-25 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -6185,7 +19530,7 @@
"standard": {
"input_per_million": 0.1,
"output_per_million": 0.4,
- "cached_input_per_million": 0.025
+ "cache_read_input_per_million": 0.025
}
}
},
@@ -6208,12 +19553,117 @@
"knowledge": "2025-01"
}
},
+ {
+ "id": "gemini-2.5-flash-native-audio-latest",
+ "name": "Gemini 2.5 Flash Native Audio Latest",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 131072,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "Gemini 2.5 Flash Native Audio Latest",
+ "description": "Latest release of Gemini 2.5 Flash Native Audio",
+ "supported_generation_methods": [
+ "countTokens",
+ "bidiGenerateContent"
+ ]
+ }
+ },
+ {
+ "id": "gemini-2.5-flash-native-audio-preview-09-2025",
+ "name": "Gemini 2.5 Flash Native Audio Preview 09-2025",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 131072,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "gemini-2.5-flash-preview-native-audio-dialog-2025-05-19",
+ "description": "Gemini 2.5 Flash Native Audio Preview 09-2025",
+ "supported_generation_methods": [
+ "countTokens",
+ "bidiGenerateContent"
+ ]
+ }
+ },
+ {
+ "id": "gemini-2.5-flash-native-audio-preview-12-2025",
+ "name": "Gemini 2.5 Flash Native Audio Preview 12-2025",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 131072,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "12-2025",
+ "description": "Gemini 2.5 Flash Native Audio Preview 12-2025",
+ "supported_generation_methods": [
+ "countTokens",
+ "bidiGenerateContent"
+ ]
+ }
+ },
{
"id": "gemini-2.5-flash-preview-04-17",
"name": "Gemini 2.5 Flash Preview 04-17",
"provider": "gemini",
"family": "gemini-flash",
- "created_at": "2025-04-17 00:00:00 +0530",
+ "created_at": "2025-04-17 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -6239,7 +19689,7 @@
"standard": {
"input_per_million": 0.15,
"output_per_million": 0.6,
- "cached_input_per_million": 0.0375
+ "cache_read_input_per_million": 0.0375
}
}
},
@@ -6267,7 +19717,7 @@
"name": "Gemini 2.5 Flash Preview 05-20",
"provider": "gemini",
"family": "gemini-flash",
- "created_at": "2025-05-20 00:00:00 +0530",
+ "created_at": "2025-05-20 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -6294,7 +19744,7 @@
"standard": {
"input_per_million": 0.15,
"output_per_million": 0.6,
- "cached_input_per_million": 0.0375
+ "cache_read_input_per_million": 0.0375
}
}
},
@@ -6322,7 +19772,7 @@
"name": "Gemini 2.5 Flash Preview 09-25",
"provider": "gemini",
"family": "gemini-flash",
- "created_at": "2025-09-25 00:00:00 +0530",
+ "created_at": "2025-09-25 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -6349,7 +19799,7 @@
"standard": {
"input_per_million": 0.3,
"output_per_million": 2.5,
- "cached_input_per_million": 0.075
+ "cache_read_input_per_million": 0.075
}
},
"audio_tokens": {
@@ -6383,7 +19833,7 @@
"name": "Gemini 2.5 Flash Preview TTS",
"provider": "gemini",
"family": "gemini-flash",
- "created_at": "2025-05-01 00:00:00 +0530",
+ "created_at": "2025-05-01 00:00:00 UTC",
"context_window": 8000,
"max_output_tokens": 16000,
"knowledge_cutoff": null,
@@ -6395,7 +19845,11 @@
"audio"
]
},
- "capabilities": [],
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
"pricing": {
"text_tokens": {
"standard": {
@@ -6405,6 +19859,12 @@
}
},
"metadata": {
+ "version": "gemini-2.5-flash-exp-tts-2025-05-19",
+ "description": "Gemini 2.5 Flash Preview TTS",
+ "supported_generation_methods": [
+ "countTokens",
+ "generateContent"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": false,
@@ -6427,7 +19887,7 @@
"name": "Gemini 2.5 Pro",
"provider": "gemini",
"family": "gemini-pro",
- "created_at": "2025-03-20 00:00:00 +0530",
+ "created_at": "2025-03-20 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -6454,11 +19914,19 @@
"standard": {
"input_per_million": 1.25,
"output_per_million": 10,
- "cached_input_per_million": 0.31
+ "cache_read_input_per_million": 0.125
}
}
},
"metadata": {
+ "version": "2.5",
+ "description": "Stable release (June 17th, 2025) of Gemini 2.5 Pro",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "createCachedContent",
+ "batchGenerateContent"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": false,
@@ -6468,7 +19936,12 @@
"cost": {
"input": 1.25,
"output": 10,
- "cache_read": 0.31
+ "cache_read": 0.125,
+ "context_over_200k": {
+ "input": 2.5,
+ "output": 15,
+ "cache_read": 0.25
+ }
},
"limit": {
"context": 1048576,
@@ -6482,7 +19955,7 @@
"name": "Gemini 2.5 Pro Preview 05-06",
"provider": "gemini",
"family": "gemini-pro",
- "created_at": "2025-05-06 00:00:00 +0530",
+ "created_at": "2025-05-06 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -6509,7 +19982,7 @@
"standard": {
"input_per_million": 1.25,
"output_per_million": 10,
- "cached_input_per_million": 0.31
+ "cache_read_input_per_million": 0.31
}
}
},
@@ -6537,7 +20010,7 @@
"name": "Gemini 2.5 Pro Preview 06-05",
"provider": "gemini",
"family": "gemini-pro",
- "created_at": "2025-06-05 00:00:00 +0530",
+ "created_at": "2025-06-05 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -6564,7 +20037,7 @@
"standard": {
"input_per_million": 1.25,
"output_per_million": 10,
- "cached_input_per_million": 0.31
+ "cache_read_input_per_million": 0.31
}
}
},
@@ -6592,7 +20065,7 @@
"name": "Gemini 2.5 Pro Preview TTS",
"provider": "gemini",
"family": "gemini-flash",
- "created_at": "2025-05-01 00:00:00 +0530",
+ "created_at": "2025-05-01 00:00:00 UTC",
"context_window": 8000,
"max_output_tokens": 16000,
"knowledge_cutoff": null,
@@ -6604,7 +20077,11 @@
"audio"
]
},
- "capabilities": [],
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
"pricing": {
"text_tokens": {
"standard": {
@@ -6614,6 +20091,13 @@
}
},
"metadata": {
+ "version": "gemini-2.5-pro-preview-tts-2025-05-19",
+ "description": "Gemini 2.5 Pro Preview TTS",
+ "supported_generation_methods": [
+ "countTokens",
+ "generateContent",
+ "batchGenerateContent"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": false,
@@ -6636,7 +20120,7 @@
"name": "Gemini 3 Flash Preview",
"provider": "gemini",
"family": "gemini-flash",
- "created_at": "2025-12-17 00:00:00 +0530",
+ "created_at": "2025-12-17 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -6663,11 +20147,19 @@
"standard": {
"input_per_million": 0.5,
"output_per_million": 3,
- "cached_input_per_million": 0.05
+ "cache_read_input_per_million": 0.05
}
}
},
"metadata": {
+ "version": "3-flash-preview-12-2025",
+ "description": "Gemini 3 Flash Preview",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "createCachedContent",
+ "batchGenerateContent"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": false,
@@ -6691,12 +20183,48 @@
"knowledge": "2025-01"
}
},
+ {
+ "id": "gemini-3-pro-image-preview",
+ "name": "Nano Banana Pro",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 131072,
+ "max_output_tokens": 32768,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "3.0",
+ "description": "Gemini 3 Pro Image Preview",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "batchGenerateContent"
+ ]
+ }
+ },
{
"id": "gemini-3-pro-preview",
"name": "Gemini 3 Pro Preview",
"provider": "gemini",
"family": "gemini-pro",
- "created_at": "2025-11-18 00:00:00 +0530",
+ "created_at": "2025-11-18 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 64000,
"knowledge_cutoff": null,
@@ -6723,11 +20251,19 @@
"standard": {
"input_per_million": 2,
"output_per_million": 12,
- "cached_input_per_million": 0.2
+ "cache_read_input_per_million": 0.2
}
}
},
"metadata": {
+ "version": "3-pro-preview-11-2025",
+ "description": "Gemini 3 Pro Preview",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "createCachedContent",
+ "batchGenerateContent"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": false,
@@ -6756,7 +20292,7 @@
"name": "Gemini 3.1 Flash Image (Preview)",
"provider": "gemini",
"family": "gemini-flash",
- "created_at": "2026-02-26 00:00:00 +0530",
+ "created_at": "2026-02-26 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -6773,7 +20309,9 @@
},
"capabilities": [
"reasoning",
- "vision"
+ "vision",
+ "function_calling",
+ "structured_output"
],
"pricing": {
"text_tokens": {
@@ -6784,6 +20322,13 @@
}
},
"metadata": {
+ "version": "3.0",
+ "description": "Gemini 3.1 Flash Image Preview.",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "batchGenerateContent"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": false,
@@ -6806,7 +20351,7 @@
"name": "Gemini 3.1 Flash Lite Preview",
"provider": "gemini",
"family": "gemini-flash-lite",
- "created_at": "2026-03-03 00:00:00 +0530",
+ "created_at": "2026-03-03 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -6833,11 +20378,20 @@
"standard": {
"input_per_million": 0.25,
"output_per_million": 1.5,
- "cached_input_per_million": 0.025
+ "cache_read_input_per_million": 0.025,
+ "cache_write_input_per_million": 1
}
}
},
"metadata": {
+ "version": "3.1-flash-lite-preview-03-2026",
+ "description": "Gemini 3.1 Flash Lite Preview",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "createCachedContent",
+ "batchGenerateContent"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": false,
@@ -6857,12 +20411,82 @@
"knowledge": "2025-01"
}
},
+ {
+ "id": "gemini-3.1-flash-live-preview",
+ "name": "Gemini 3.1 Flash Live Preview",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 131072,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "3.1-flash-live-03-2026",
+ "description": "Gemini 3.1 Flash Live Preview",
+ "supported_generation_methods": [
+ "bidiGenerateContent"
+ ]
+ }
+ },
+ {
+ "id": "gemini-3.1-flash-tts-preview",
+ "name": "Gemini 3.1 Flash TTS Preview",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 8192,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "3.1-flash-tts-preview",
+ "description": "Gemini 3.1 Flash TTS Preview",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "batchGenerateContent"
+ ]
+ }
+ },
{
"id": "gemini-3.1-pro-preview",
"name": "Gemini 3.1 Pro Preview",
"provider": "gemini",
"family": "gemini-pro",
- "created_at": "2026-02-19 00:00:00 +0530",
+ "created_at": "2026-02-19 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -6889,11 +20513,19 @@
"standard": {
"input_per_million": 2,
"output_per_million": 12,
- "cached_input_per_million": 0.2
+ "cache_read_input_per_million": 0.2
}
}
},
"metadata": {
+ "version": "3.1-pro-preview-01-2026",
+ "description": "Gemini 3.1 Pro Preview",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "createCachedContent",
+ "batchGenerateContent"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": false,
@@ -6922,7 +20554,7 @@
"name": "Gemini 3.1 Pro Preview Custom Tools",
"provider": "gemini",
"family": "gemini-pro",
- "created_at": "2026-02-19 00:00:00 +0530",
+ "created_at": "2026-02-19 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -6949,11 +20581,19 @@
"standard": {
"input_per_million": 2,
"output_per_million": 12,
- "cached_input_per_million": 0.2
+ "cache_read_input_per_million": 0.2
}
}
},
"metadata": {
+ "version": "3.1-pro-preview-01-2026",
+ "description": "Gemini 3.1 Pro Preview optimized for custom tool usage",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "createCachedContent",
+ "batchGenerateContent"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": false,
@@ -6982,7 +20622,7 @@
"name": "Gemini Embedding 001",
"provider": "gemini",
"family": "gemini",
- "created_at": "2025-05-20 00:00:00 +0530",
+ "created_at": "2025-05-20 00:00:00 UTC",
"context_window": 2048,
"max_output_tokens": 3072,
"knowledge_cutoff": null,
@@ -6991,7 +20631,7 @@
"text"
],
"output": [
- "text"
+ "embeddings"
]
},
"capabilities": [],
@@ -7003,6 +20643,14 @@
}
},
"metadata": {
+ "version": "001",
+ "description": "Obtain a distributed representation of a text.",
+ "supported_generation_methods": [
+ "embedContent",
+ "countTextTokens",
+ "countTokens",
+ "asyncBatchEmbedContent"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": false,
@@ -7020,12 +20668,72 @@
"knowledge": "2025-05"
}
},
+ {
+ "id": "gemini-embedding-2",
+ "name": "Gemini Embedding 2",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 8192,
+ "max_output_tokens": 1,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
+ "pricing": {},
+ "metadata": {
+ "version": "2",
+ "description": "Obtain a distributed representation of multimodal content.",
+ "supported_generation_methods": [
+ "embedContent",
+ "countTextTokens",
+ "countTokens",
+ "asyncBatchEmbedContent"
+ ]
+ }
+ },
+ {
+ "id": "gemini-embedding-2-preview",
+ "name": "Gemini Embedding 2 Preview",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 8192,
+ "max_output_tokens": 1,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
+ "pricing": {},
+ "metadata": {
+ "version": "2",
+ "description": "Obtain a distributed representation of multimodal content.",
+ "supported_generation_methods": [
+ "embedContent",
+ "countTextTokens",
+ "countTokens",
+ "asyncBatchEmbedContent"
+ ]
+ }
+ },
{
"id": "gemini-flash-latest",
"name": "Gemini Flash Latest",
"provider": "gemini",
"family": "gemini-flash",
- "created_at": "2025-09-25 00:00:00 +0530",
+ "created_at": "2025-09-25 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -7052,7 +20760,7 @@
"standard": {
"input_per_million": 0.3,
"output_per_million": 2.5,
- "cached_input_per_million": 0.075
+ "cache_read_input_per_million": 0.075
}
},
"audio_tokens": {
@@ -7062,6 +20770,14 @@
}
},
"metadata": {
+ "version": "Gemini Flash Latest",
+ "description": "Latest release of Gemini Flash",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "createCachedContent",
+ "batchGenerateContent"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": false,
@@ -7086,7 +20802,7 @@
"name": "Gemini Flash-Lite Latest",
"provider": "gemini",
"family": "gemini-flash-lite",
- "created_at": "2025-09-25 00:00:00 +0530",
+ "created_at": "2025-09-25 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -7113,11 +20829,19 @@
"standard": {
"input_per_million": 0.1,
"output_per_million": 0.4,
- "cached_input_per_million": 0.025
+ "cache_read_input_per_million": 0.025
}
}
},
"metadata": {
+ "version": "Gemini Flash-Lite Latest",
+ "description": "Latest release of Gemini Flash-Lite",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "createCachedContent",
+ "batchGenerateContent"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": false,
@@ -7141,7 +20865,7 @@
"name": "Gemini Live 2.5 Flash",
"provider": "gemini",
"family": "gemini-flash",
- "created_at": "2025-09-01 00:00:00 +0530",
+ "created_at": "2025-09-01 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 8000,
"knowledge_cutoff": null,
@@ -7201,7 +20925,7 @@
"name": "Gemini Live 2.5 Flash Preview Native Audio",
"provider": "gemini",
"family": "gemini-flash",
- "created_at": "2025-06-17 00:00:00 +0530",
+ "created_at": "2025-06-17 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -7255,12 +20979,121 @@
"knowledge": "2025-01"
}
},
+ {
+ "id": "gemini-pro-latest",
+ "name": "Gemini Pro Latest",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 1048576,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "Gemini Pro Latest",
+ "description": "Latest release of Gemini Pro",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "createCachedContent",
+ "batchGenerateContent"
+ ]
+ }
+ },
+ {
+ "id": "gemini-robotics-er-1.5-preview",
+ "name": "Gemini Robotics-ER 1.5 Preview",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 1048576,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "1.5-preview",
+ "description": "Gemini Robotics-ER 1.5 Preview",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens"
+ ]
+ }
+ },
+ {
+ "id": "gemini-robotics-er-1.6-preview",
+ "name": "Gemini Robotics-ER 1.6 Preview",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 131072,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "1.6-preview",
+ "description": "Gemini Robotics-ER 1.6 Preview",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "createCachedContent",
+ "batchGenerateContent"
+ ]
+ }
+ },
{
"id": "gemma-3-12b-it",
"name": "Gemma 3 12B",
"provider": "gemini",
"family": "gemma",
- "created_at": "2025-03-13 00:00:00 +0530",
+ "created_at": "2025-03-13 00:00:00 UTC",
"context_window": 32768,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -7301,7 +21134,7 @@
"name": "Gemma 3 27B",
"provider": "gemini",
"family": "gemma",
- "created_at": "2025-03-12 00:00:00 +0530",
+ "created_at": "2025-03-12 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -7343,7 +21176,7 @@
"name": "Gemma 3 4B",
"provider": "gemini",
"family": "gemma",
- "created_at": "2025-03-13 00:00:00 +0530",
+ "created_at": "2025-03-13 00:00:00 UTC",
"context_window": 32768,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -7383,7 +21216,7 @@
"name": "Gemma 3n 2B",
"provider": "gemini",
"family": "gemma",
- "created_at": "2025-07-09 00:00:00 +0530",
+ "created_at": "2025-07-09 00:00:00 UTC",
"context_window": 8192,
"max_output_tokens": 2000,
"knowledge_cutoff": null,
@@ -7420,7 +21253,7 @@
"name": "Gemma 3n 4B",
"provider": "gemini",
"family": "gemma",
- "created_at": "2025-05-20 00:00:00 +0530",
+ "created_at": "2025-05-20 00:00:00 UTC",
"context_window": 8192,
"max_output_tokens": 2000,
"knowledge_cutoff": null,
@@ -7453,11 +21286,11 @@
}
},
{
- "id": "gemma-4-26b-it",
+ "id": "gemma-4-26b-a4b-it",
"name": "Gemma 4 26B",
"provider": "gemini",
"family": "gemma",
- "created_at": "2026-04-02 00:00:00 +0530",
+ "created_at": "2026-04-02 00:00:00 UTC",
"context_window": 256000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -7476,8 +21309,21 @@
"reasoning",
"vision"
],
- "pricing": {},
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
"metadata": {
+ "version": "001",
+ "description": "Gemma 4 26B A4B IT",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": true,
@@ -7495,7 +21341,7 @@
"name": "Gemma 4 31B",
"provider": "gemini",
"family": "gemma",
- "created_at": "2026-04-02 00:00:00 +0530",
+ "created_at": "2026-04-02 00:00:00 UTC",
"context_window": 256000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -7514,8 +21360,21 @@
"reasoning",
"vision"
],
- "pricing": {},
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
"metadata": {
+ "version": "001",
+ "description": "Gemma 4 31B IT",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens"
+ ],
"source": "models.dev",
"provider_id": "google",
"open_weights": true,
@@ -7528,12 +21387,472 @@
}
}
},
+ {
+ "id": "imagen-4.0-fast-generate-001",
+ "name": "Imagen 4 Fast",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 480,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.03,
+ "output_per_million": 0.03
+ }
+ }
+ },
+ "metadata": {
+ "version": "001",
+ "description": "Vertex served Imagen 4.0 Fast model",
+ "supported_generation_methods": [
+ "predict"
+ ]
+ }
+ },
+ {
+ "id": "imagen-4.0-generate-001",
+ "name": "Imagen 4",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 480,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.03,
+ "output_per_million": 0.03
+ }
+ }
+ },
+ "metadata": {
+ "version": "001",
+ "description": "Vertex served Imagen 4.0 model",
+ "supported_generation_methods": [
+ "predict"
+ ]
+ }
+ },
+ {
+ "id": "imagen-4.0-ultra-generate-001",
+ "name": "Imagen 4 Ultra",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 480,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.03,
+ "output_per_million": 0.03
+ }
+ }
+ },
+ "metadata": {
+ "version": "001",
+ "description": "Vertex served Imagen 4.0 ultra model",
+ "supported_generation_methods": [
+ "predict"
+ ]
+ }
+ },
+ {
+ "id": "lyria-3-clip-preview",
+ "name": "Lyria 3 Clip Preview",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 1048576,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "lyria-3-clip-preview",
+ "description": "Lyria 3 30s model Preview",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens"
+ ]
+ }
+ },
+ {
+ "id": "lyria-3-pro-preview",
+ "name": "Lyria 3 Pro Preview",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 1048576,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "lyria-3-pro-preview",
+ "description": "Lyria 3 Pro Preview",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens"
+ ]
+ }
+ },
+ {
+ "id": "nano-banana-pro-preview",
+ "name": "Nano Banana Pro",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 131072,
+ "max_output_tokens": 32768,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "3.0",
+ "description": "Gemini 3 Pro Image Preview",
+ "supported_generation_methods": [
+ "generateContent",
+ "countTokens",
+ "batchGenerateContent"
+ ]
+ }
+ },
+ {
+ "id": "veo-2.0-generate-001",
+ "name": "Veo 2",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 480,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "2.0",
+ "description": "Vertex served Veo 2 model. Access to this model requires billing to be enabled on the associated Google Cloud Platform account. Please visit https://console.cloud.google.com/billing to enable it.",
+ "supported_generation_methods": [
+ "predictLongRunning"
+ ]
+ }
+ },
+ {
+ "id": "veo-3.0-fast-generate-001",
+ "name": "Veo 3 fast",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 480,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "3.0",
+ "description": "Veo 3 fast",
+ "supported_generation_methods": [
+ "predictLongRunning"
+ ]
+ }
+ },
+ {
+ "id": "veo-3.0-generate-001",
+ "name": "Veo 3",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 480,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "3.0",
+ "description": "Veo 3",
+ "supported_generation_methods": [
+ "predictLongRunning"
+ ]
+ }
+ },
+ {
+ "id": "veo-3.1-fast-generate-preview",
+ "name": "Veo 3.1 fast",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 480,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "3.1",
+ "description": "Veo 3.1 fast",
+ "supported_generation_methods": [
+ "predictLongRunning"
+ ]
+ }
+ },
+ {
+ "id": "veo-3.1-generate-preview",
+ "name": "Veo 3.1",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 480,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "3.1",
+ "description": "Veo 3.1",
+ "supported_generation_methods": [
+ "predictLongRunning"
+ ]
+ }
+ },
+ {
+ "id": "veo-3.1-lite-generate-preview",
+ "name": "Veo 3.1 lite",
+ "provider": "gemini",
+ "family": null,
+ "created_at": null,
+ "context_window": 480,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "version": "3.1",
+ "description": "Veo 3.1 lite",
+ "supported_generation_methods": [
+ "predictLongRunning"
+ ]
+ }
+ },
+ {
+ "id": "codestral-2508",
+ "name": "Codestral",
+ "provider": "mistral",
+ "family": "codestral",
+ "created_at": "2025-08-29 23:00:00 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "batch",
+ "predicted_outputs"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "codestral-embed",
+ "name": "Codestral",
+ "provider": "mistral",
+ "family": "codestral",
+ "created_at": "2025-05-20 23:00:00 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "embeddings"
+ ]
+ },
+ "capabilities": [
+ "predicted_outputs"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "codestral-embed-2505",
+ "name": "Codestral",
+ "provider": "mistral",
+ "family": "codestral",
+ "created_at": "2025-05-20 23:00:00 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "embeddings"
+ ]
+ },
+ "capabilities": [
+ "predicted_outputs"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
{
"id": "codestral-latest",
"name": "Codestral (latest)",
"provider": "mistral",
"family": "codestral",
- "created_at": "2024-05-29 00:00:00 +0530",
+ "created_at": "2024-05-29 00:00:00 UTC",
"context_window": 256000,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -7546,7 +21865,11 @@
]
},
"capabilities": [
- "function_calling"
+ "function_calling",
+ "streaming",
+ "structured_output",
+ "batch",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -7557,6 +21880,8 @@
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": true,
@@ -7579,7 +21904,7 @@
"name": "Devstral 2",
"provider": "mistral",
"family": "devstral",
- "created_at": "2025-12-09 00:00:00 +0530",
+ "created_at": "2025-12-09 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 262144,
"knowledge_cutoff": null,
@@ -7592,7 +21917,11 @@
]
},
"capabilities": [
- "function_calling"
+ "function_calling",
+ "streaming",
+ "structured_output",
+ "batch",
+ "fine_tuning"
],
"pricing": {
"text_tokens": {
@@ -7603,6 +21932,8 @@
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": true,
@@ -7620,12 +21951,42 @@
"knowledge": "2025-12"
}
},
+ {
+ "id": "devstral-latest",
+ "name": "Devstral Latest",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "batch",
+ "fine_tuning"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
{
"id": "devstral-medium-2507",
"name": "Devstral Medium",
"provider": "mistral",
"family": "devstral",
- "created_at": "2025-07-10 00:00:00 +0530",
+ "created_at": "2025-07-10 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 128000,
"knowledge_cutoff": null,
@@ -7638,7 +21999,11 @@
]
},
"capabilities": [
- "function_calling"
+ "function_calling",
+ "streaming",
+ "structured_output",
+ "batch",
+ "fine_tuning"
],
"pricing": {
"text_tokens": {
@@ -7649,6 +22014,8 @@
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": true,
@@ -7671,7 +22038,7 @@
"name": "Devstral 2 (latest)",
"provider": "mistral",
"family": "devstral",
- "created_at": "2025-12-02 00:00:00 +0530",
+ "created_at": "2025-12-02 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 262144,
"knowledge_cutoff": null,
@@ -7684,7 +22051,11 @@
]
},
"capabilities": [
- "function_calling"
+ "function_calling",
+ "streaming",
+ "structured_output",
+ "batch",
+ "fine_tuning"
],
"pricing": {
"text_tokens": {
@@ -7695,6 +22066,8 @@
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": true,
@@ -7717,7 +22090,7 @@
"name": "Devstral Small 2505",
"provider": "mistral",
"family": "devstral",
- "created_at": "2025-05-07 00:00:00 +0530",
+ "created_at": "2025-05-07 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 128000,
"knowledge_cutoff": null,
@@ -7763,7 +22136,7 @@
"name": "Devstral Small",
"provider": "mistral",
"family": "devstral",
- "created_at": "2025-07-10 00:00:00 +0530",
+ "created_at": "2025-07-10 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 128000,
"knowledge_cutoff": null,
@@ -7776,7 +22149,11 @@
]
},
"capabilities": [
- "function_calling"
+ "function_calling",
+ "streaming",
+ "structured_output",
+ "batch",
+ "fine_tuning"
],
"pricing": {
"text_tokens": {
@@ -7787,6 +22164,8 @@
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": true,
@@ -7809,7 +22188,7 @@
"name": "Devstral Small 2",
"provider": "mistral",
"family": "devstral",
- "created_at": "2025-12-09 00:00:00 +0530",
+ "created_at": "2025-12-09 00:00:00 UTC",
"context_window": 256000,
"max_output_tokens": 256000,
"knowledge_cutoff": null,
@@ -7845,12 +22224,71 @@
"knowledge": "2025-12"
}
},
+ {
+ "id": "labs-leanstral-2603",
+ "name": "Labs Leanstral 2603",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "batch"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "magistral-medium-2509",
+ "name": "Magistral Medium 2509",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "reasoning",
+ "batch"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
{
"id": "magistral-medium-latest",
"name": "Magistral Medium (latest)",
"provider": "mistral",
"family": "magistral-medium",
- "created_at": "2025-03-17 00:00:00 +0530",
+ "created_at": "2025-03-17 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 16384,
"knowledge_cutoff": null,
@@ -7864,7 +22302,10 @@
},
"capabilities": [
"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "structured_output",
+ "batch"
],
"pricing": {
"text_tokens": {
@@ -7875,6 +22316,8 @@
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": true,
@@ -7897,7 +22340,7 @@
"name": "Magistral Small",
"provider": "mistral",
"family": "magistral-small",
- "created_at": "2025-03-17 00:00:00 +0530",
+ "created_at": "2025-03-17 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 128000,
"knowledge_cutoff": null,
@@ -7939,12 +22382,162 @@
"knowledge": "2025-06"
}
},
+ {
+ "id": "magistral-small-2509",
+ "name": "Magistral Small 2509",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "reasoning",
+ "batch"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "magistral-small-latest",
+ "name": "Magistral Small Latest",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "reasoning",
+ "batch"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "ministral-14b-2512",
+ "name": "Ministral 14b 2512",
+ "provider": "mistral",
+ "family": "ministral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "batch",
+ "distillation"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "ministral-14b-latest",
+ "name": "Ministral 14b Latest",
+ "provider": "mistral",
+ "family": "ministral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "batch",
+ "distillation"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "ministral-3b-2512",
+ "name": "Ministral 3B",
+ "provider": "mistral",
+ "family": "ministral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "batch",
+ "distillation"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
{
"id": "ministral-3b-latest",
"name": "Ministral 3B (latest)",
"provider": "mistral",
"family": "ministral",
- "created_at": "2024-10-01 00:00:00 +0530",
+ "created_at": "2024-10-01 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 128000,
"knowledge_cutoff": null,
@@ -7957,7 +22550,11 @@
]
},
"capabilities": [
- "function_calling"
+ "function_calling",
+ "streaming",
+ "structured_output",
+ "batch",
+ "distillation"
],
"pricing": {
"text_tokens": {
@@ -7968,6 +22565,8 @@
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": true,
@@ -7985,12 +22584,42 @@
"knowledge": "2024-10"
}
},
+ {
+ "id": "ministral-8b-2512",
+ "name": "Ministral 8B",
+ "provider": "mistral",
+ "family": "ministral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "batch",
+ "distillation"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
{
"id": "ministral-8b-latest",
"name": "Ministral 8B (latest)",
"provider": "mistral",
"family": "ministral",
- "created_at": "2024-10-01 00:00:00 +0530",
+ "created_at": "2024-10-01 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 128000,
"knowledge_cutoff": null,
@@ -8003,7 +22632,11 @@
]
},
"capabilities": [
- "function_calling"
+ "function_calling",
+ "streaming",
+ "structured_output",
+ "batch",
+ "distillation"
],
"pricing": {
"text_tokens": {
@@ -8014,6 +22647,8 @@
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": true,
@@ -8036,7 +22671,7 @@
"name": "Mistral Embed",
"provider": "mistral",
"family": "mistral-embed",
- "created_at": "2023-12-11 00:00:00 +0530",
+ "created_at": "2023-12-11 00:00:00 UTC",
"context_window": 8000,
"max_output_tokens": 3072,
"knowledge_cutoff": null,
@@ -8057,6 +22692,8 @@
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": false,
@@ -8073,12 +22710,36 @@
}
}
},
+ {
+ "id": "mistral-embed-2312",
+ "name": "Mistral Embed",
+ "provider": "mistral",
+ "family": "mistral-embed",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "embeddings"
+ ]
+ },
+ "capabilities": [],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
{
"id": "mistral-large-2411",
"name": "Mistral Large 2.1",
"provider": "mistral",
"family": "mistral-large",
- "created_at": "2024-11-01 00:00:00 +0530",
+ "created_at": "2024-11-01 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 16384,
"knowledge_cutoff": null,
@@ -8091,7 +22752,11 @@
]
},
"capabilities": [
- "function_calling"
+ "function_calling",
+ "streaming",
+ "structured_output",
+ "batch",
+ "fine_tuning"
],
"pricing": {
"text_tokens": {
@@ -8102,6 +22767,8 @@
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": true,
@@ -8124,7 +22791,7 @@
"name": "Mistral Large 3",
"provider": "mistral",
"family": "mistral-large",
- "created_at": "2024-11-01 00:00:00 +0530",
+ "created_at": "2024-11-01 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 262144,
"knowledge_cutoff": null,
@@ -8139,7 +22806,11 @@
},
"capabilities": [
"function_calling",
- "vision"
+ "vision",
+ "streaming",
+ "structured_output",
+ "batch",
+ "fine_tuning"
],
"pricing": {
"text_tokens": {
@@ -8150,6 +22821,8 @@
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": true,
@@ -8172,7 +22845,7 @@
"name": "Mistral Large (latest)",
"provider": "mistral",
"family": "mistral-large",
- "created_at": "2024-11-01 00:00:00 +0530",
+ "created_at": "2024-11-01 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 262144,
"knowledge_cutoff": null,
@@ -8187,7 +22860,11 @@
},
"capabilities": [
"function_calling",
- "vision"
+ "vision",
+ "streaming",
+ "structured_output",
+ "batch",
+ "fine_tuning"
],
"pricing": {
"text_tokens": {
@@ -8198,6 +22875,8 @@
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": true,
@@ -8215,12 +22894,75 @@
"knowledge": "2024-11"
}
},
+ {
+ "id": "mistral-large-pixtral-2411",
+ "name": "Mistral Large",
+ "provider": "mistral",
+ "family": "mistral-large",
+ "created_at": "2024-11-12 00:00:00 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "vision",
+ "batch",
+ "fine_tuning"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "mistral-medium",
+ "name": "Mistral Medium",
+ "provider": "mistral",
+ "family": "mistral-medium",
+ "created_at": "2025-05-05 23:00:00 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "vision",
+ "batch",
+ "fine_tuning"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
{
"id": "mistral-medium-2505",
"name": "Mistral Medium 3",
"provider": "mistral",
"family": "mistral-medium",
- "created_at": "2025-05-07 00:00:00 +0530",
+ "created_at": "2025-05-07 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -8235,7 +22977,11 @@
},
"capabilities": [
"function_calling",
- "vision"
+ "vision",
+ "streaming",
+ "structured_output",
+ "batch",
+ "fine_tuning"
],
"pricing": {
"text_tokens": {
@@ -8246,6 +22992,8 @@
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": false,
@@ -8268,7 +23016,7 @@
"name": "Mistral Medium 3.1",
"provider": "mistral",
"family": "mistral-medium",
- "created_at": "2025-08-12 00:00:00 +0530",
+ "created_at": "2025-08-12 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 262144,
"knowledge_cutoff": null,
@@ -8283,7 +23031,11 @@
},
"capabilities": [
"function_calling",
- "vision"
+ "vision",
+ "streaming",
+ "structured_output",
+ "batch",
+ "fine_tuning"
],
"pricing": {
"text_tokens": {
@@ -8294,6 +23046,8 @@
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": false,
@@ -8312,13 +23066,13 @@
}
},
{
- "id": "mistral-medium-latest",
- "name": "Mistral Medium (latest)",
+ "id": "mistral-medium-2604",
+ "name": "Mistral Medium 3.5",
"provider": "mistral",
"family": "mistral-medium",
- "created_at": "2025-05-07 00:00:00 +0530",
- "context_window": 128000,
- "max_output_tokens": 16384,
+ "created_at": "2026-04-29 00:00:00 UTC",
+ "context_window": 262144,
+ "max_output_tokens": 262144,
"knowledge_cutoff": null,
"modalities": {
"input": [
@@ -8331,32 +23085,294 @@
},
"capabilities": [
"function_calling",
- "vision"
+ "structured_output",
+ "reasoning",
+ "vision",
+ "streaming",
+ "batch",
+ "fine_tuning"
],
"pricing": {
"text_tokens": {
"standard": {
- "input_per_million": 0.4,
- "output_per_million": 2
+ "input_per_million": 1.5,
+ "output_per_million": 7.5
}
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": true,
- "attachment": false,
+ "attachment": true,
"temperature": true,
- "last_updated": "2025-05-10",
+ "last_updated": "2026-04-29",
"cost": {
- "input": 0.4,
- "output": 2
+ "input": 1.5,
+ "output": 7.5
},
"limit": {
- "context": 128000,
- "output": 16384
+ "context": 262144,
+ "output": 262144
+ }
+ }
+ },
+ {
+ "id": "mistral-medium-3",
+ "name": "Mistral Medium",
+ "provider": "mistral",
+ "family": "mistral-medium",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "vision",
+ "batch",
+ "fine_tuning"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "mistral-medium-3-5",
+ "name": "Mistral Medium",
+ "provider": "mistral",
+ "family": "mistral-medium",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "vision",
+ "batch",
+ "fine_tuning"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "mistral-medium-3.5",
+ "name": "Mistral Medium",
+ "provider": "mistral",
+ "family": "mistral-medium",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "vision",
+ "batch",
+ "fine_tuning"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "mistral-medium-c21211-r0-75",
+ "name": "Mistral Medium",
+ "provider": "mistral",
+ "family": "mistral-medium",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "vision",
+ "batch",
+ "fine_tuning"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "mistral-medium-latest",
+ "name": "Mistral Medium (latest)",
+ "provider": "mistral",
+ "family": "mistral-medium",
+ "created_at": "2026-04-29 00:00:00 UTC",
+ "context_window": 262144,
+ "max_output_tokens": 262144,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "reasoning",
+ "vision",
+ "streaming",
+ "batch",
+ "fine_tuning"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 1.5,
+ "output_per_million": 7.5
+ }
+ }
+ },
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
+ "source": "models.dev",
+ "provider_id": "mistral",
+ "open_weights": true,
+ "attachment": true,
+ "temperature": true,
+ "last_updated": "2026-04-29",
+ "cost": {
+ "input": 1.5,
+ "output": 7.5
},
- "knowledge": "2025-05"
+ "limit": {
+ "context": 262144,
+ "output": 262144
+ }
+ }
+ },
+ {
+ "id": "mistral-moderation-2411",
+ "name": "Mistral Moderation",
+ "provider": "mistral",
+ "family": "mistral-moderation",
+ "created_at": "2024-11-26 00:00:00 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "moderation"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "mistral-moderation-2603",
+ "name": "Mistral Moderation",
+ "provider": "mistral",
+ "family": "mistral-moderation",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "moderation"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "mistral-moderation-latest",
+ "name": "Mistral Moderation",
+ "provider": "mistral",
+ "family": "mistral-moderation",
+ "created_at": "2024-11-26 00:00:00 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "moderation"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
}
},
{
@@ -8364,7 +23380,7 @@
"name": "Mistral Nemo",
"provider": "mistral",
"family": "mistral-nemo",
- "created_at": "2024-07-01 00:00:00 +0530",
+ "created_at": "2024-07-01 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 128000,
"knowledge_cutoff": null,
@@ -8405,12 +23421,90 @@
"knowledge": "2024-07"
}
},
+ {
+ "id": "mistral-ocr-2505",
+ "name": "Mistral Ocr 2505",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": "2025-05-22 23:00:00 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "vision"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "mistral-ocr-2512",
+ "name": "Mistral Ocr 2512",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "vision"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "mistral-ocr-latest",
+ "name": "Mistral Ocr Latest",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": "2025-05-22 23:00:00 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "vision"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
{
"id": "mistral-small-2506",
"name": "Mistral Small 3.2",
"provider": "mistral",
"family": "mistral-small",
- "created_at": "2025-06-20 00:00:00 +0530",
+ "created_at": "2025-06-20 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 16384,
"knowledge_cutoff": null,
@@ -8425,7 +23519,11 @@
},
"capabilities": [
"function_calling",
- "vision"
+ "vision",
+ "streaming",
+ "structured_output",
+ "batch",
+ "fine_tuning"
],
"pricing": {
"text_tokens": {
@@ -8436,6 +23534,8 @@
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": true,
@@ -8458,7 +23558,7 @@
"name": "Mistral Small 4",
"provider": "mistral",
"family": "mistral-small",
- "created_at": "2026-03-16 00:00:00 +0530",
+ "created_at": "2026-03-16 00:00:00 UTC",
"context_window": 256000,
"max_output_tokens": 256000,
"knowledge_cutoff": null,
@@ -8474,7 +23574,11 @@
"capabilities": [
"function_calling",
"reasoning",
- "vision"
+ "vision",
+ "streaming",
+ "structured_output",
+ "batch",
+ "fine_tuning"
],
"pricing": {
"text_tokens": {
@@ -8485,6 +23589,8 @@
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": true,
@@ -8507,7 +23613,7 @@
"name": "Mistral Small (latest)",
"provider": "mistral",
"family": "mistral-small",
- "created_at": "2026-03-16 00:00:00 +0530",
+ "created_at": "2026-03-16 00:00:00 UTC",
"context_window": 256000,
"max_output_tokens": 256000,
"knowledge_cutoff": null,
@@ -8523,7 +23629,11 @@
"capabilities": [
"function_calling",
"reasoning",
- "vision"
+ "vision",
+ "streaming",
+ "structured_output",
+ "batch",
+ "fine_tuning"
],
"pricing": {
"text_tokens": {
@@ -8534,6 +23644,8 @@
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": true,
@@ -8551,12 +23663,157 @@
"knowledge": "2025-06"
}
},
+ {
+ "id": "mistral-tiny-2407",
+ "name": "Mistral Tiny 2407",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": "2024-07-17 23:00:00 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "batch"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "mistral-tiny-latest",
+ "name": "Mistral Tiny Latest",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": "2024-07-17 23:00:00 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "batch"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "mistral-vibe-cli-fast",
+ "name": "Mistral Vibe Cli Fast",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "batch"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "mistral-vibe-cli-latest",
+ "name": "Mistral Vibe Cli Latest",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "batch"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "mistral-vibe-cli-with-tools",
+ "name": "Mistral Vibe Cli With Tools",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "batch"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
{
"id": "open-mistral-7b",
"name": "Mistral 7B",
"provider": "mistral",
"family": "mistral",
- "created_at": "2023-09-27 00:00:00 +0530",
+ "created_at": "2023-09-27 00:00:00 UTC",
"context_window": 8000,
"max_output_tokens": 8000,
"knowledge_cutoff": null,
@@ -8597,12 +23854,70 @@
"knowledge": "2023-12"
}
},
+ {
+ "id": "open-mistral-nemo",
+ "name": "Open Mistral Nemo",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": "2024-07-17 23:00:00 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "batch"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "open-mistral-nemo-2407",
+ "name": "Open Mistral Nemo 2407",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": "2024-07-17 23:00:00 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "batch"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
{
"id": "open-mixtral-8x22b",
"name": "Mixtral 8x22B",
"provider": "mistral",
"family": "mixtral",
- "created_at": "2024-04-17 00:00:00 +0530",
+ "created_at": "2024-04-17 00:00:00 UTC",
"context_window": 64000,
"max_output_tokens": 64000,
"knowledge_cutoff": null,
@@ -8648,7 +23963,7 @@
"name": "Mixtral 8x7B",
"provider": "mistral",
"family": "mixtral",
- "created_at": "2023-12-11 00:00:00 +0530",
+ "created_at": "2023-12-11 00:00:00 UTC",
"context_window": 32000,
"max_output_tokens": 32000,
"knowledge_cutoff": null,
@@ -8694,7 +24009,7 @@
"name": "Pixtral 12B",
"provider": "mistral",
"family": "pixtral",
- "created_at": "2024-09-01 00:00:00 +0530",
+ "created_at": "2024-09-01 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 128000,
"knowledge_cutoff": null,
@@ -8737,12 +24052,43 @@
"knowledge": "2024-09"
}
},
+ {
+ "id": "pixtral-large-2411",
+ "name": "Pixtral Large",
+ "provider": "mistral",
+ "family": "pixtral",
+ "created_at": "2024-11-12 00:00:00 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "vision",
+ "batch"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
{
"id": "pixtral-large-latest",
"name": "Pixtral Large (latest)",
"provider": "mistral",
"family": "pixtral",
- "created_at": "2024-11-01 00:00:00 +0530",
+ "created_at": "2024-11-01 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 128000,
"knowledge_cutoff": null,
@@ -8757,7 +24103,10 @@
},
"capabilities": [
"function_calling",
- "vision"
+ "vision",
+ "streaming",
+ "structured_output",
+ "batch"
],
"pricing": {
"text_tokens": {
@@ -8768,6 +24117,8 @@
}
},
"metadata": {
+ "object": "model",
+ "owned_by": "mistralai",
"source": "models.dev",
"provider_id": "mistral",
"open_weights": true,
@@ -8786,13 +24137,13 @@
}
},
{
- "id": "babbage-002",
- "name": "Babbage 002",
- "provider": "openai",
- "family": "babbage",
- "created_at": "2023-08-21 21:46:55 +0530",
- "context_window": 4096,
- "max_output_tokens": 16384,
+ "id": "voxtral-mini-2507",
+ "name": "Voxtral Mini 2507",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
"knowledge_cutoff": null,
"modalities": {
"input": [
@@ -8805,6 +24156,286 @@
"capabilities": [
"streaming"
],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "voxtral-mini-2602",
+ "name": "Voxtral Mini 2602",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "voxtral-mini-latest",
+ "name": "Voxtral Mini Latest",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "voxtral-mini-realtime-2602",
+ "name": "Voxtral Mini Realtime 2602",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "voxtral-mini-realtime-latest",
+ "name": "Voxtral Mini Realtime Latest",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "voxtral-mini-transcribe-2507",
+ "name": "Voxtral Mini Transcribe 2507",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "transcription"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "voxtral-mini-transcribe-realtime-2602",
+ "name": "Voxtral Mini Transcribe Realtime 2602",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "transcription"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "voxtral-mini-tts-2603",
+ "name": "Voxtral Mini Tts 2603",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "voxtral-mini-tts-latest",
+ "name": "Voxtral Mini Tts Latest",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "voxtral-small-2507",
+ "name": "Voxtral Small 2507",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "voxtral-small-latest",
+ "name": "Voxtral Small Latest",
+ "provider": "mistral",
+ "family": "mistral",
+ "created_at": null,
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {},
+ "metadata": {
+ "object": "model",
+ "owned_by": "mistralai"
+ }
+ },
+ {
+ "id": "babbage-002",
+ "name": "babbage-002",
+ "provider": "openai",
+ "family": null,
+ "created_at": "2023-08-21 16:16:55 UTC",
+ "context_window": 4096,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [],
"pricing": {
"text_tokens": {
"standard": {
@@ -8818,12 +24449,39 @@
"owned_by": "system"
}
},
+ {
+ "id": "chat-latest",
+ "name": "chat-latest",
+ "provider": "openai",
+ "family": null,
+ "created_at": "2026-05-02 06:50:02 UTC",
+ "context_window": 4096,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.5,
+ "output_per_million": 1.5
+ }
+ }
+ },
+ "metadata": {
+ "object": "model",
+ "owned_by": "system"
+ }
+ },
{
"id": "chatgpt-image-latest",
"name": "chatgpt-image-latest",
"provider": "openai",
"family": "gpt-image",
- "created_at": "2025-12-16 00:00:00 +0530",
+ "created_at": "2025-12-16 00:00:00 UTC",
"context_window": 0,
"max_output_tokens": 0,
"knowledge_cutoff": null,
@@ -8838,10 +24496,16 @@
]
},
"capabilities": [
- "vision",
- "streaming"
+ "vision"
],
- "pricing": {},
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.5,
+ "output_per_million": 1.5
+ }
+ }
+ },
"metadata": {
"object": "model",
"owned_by": "system",
@@ -8858,75 +24522,20 @@
}
}
},
- {
- "id": "codex-mini-latest",
- "name": "Codex Mini",
- "provider": "openai",
- "family": "gpt-codex-mini",
- "created_at": "2025-05-16 00:00:00 +0530",
- "context_window": 200000,
- "max_output_tokens": 100000,
- "knowledge_cutoff": null,
- "modalities": {
- "input": [
- "text"
- ],
- "output": [
- "text"
- ]
- },
- "capabilities": [
- "function_calling",
- "reasoning"
- ],
- "pricing": {
- "text_tokens": {
- "standard": {
- "input_per_million": 1.5,
- "output_per_million": 6,
- "cached_input_per_million": 0.375
- }
- }
- },
- "metadata": {
- "source": "models.dev",
- "provider_id": "openai",
- "open_weights": false,
- "attachment": true,
- "temperature": false,
- "last_updated": "2025-05-16",
- "cost": {
- "input": 1.5,
- "output": 6,
- "cache_read": 0.375
- },
- "limit": {
- "context": 200000,
- "output": 100000
- },
- "knowledge": "2024-04"
- }
- },
{
"id": "computer-use-preview",
- "name": "Computer Use Preview",
+ "name": "computer-use-preview",
"provider": "openai",
- "family": "other",
- "created_at": "2024-12-20 06:17:57 +0530",
+ "family": null,
+ "created_at": "2024-12-20 00:47:57 UTC",
"context_window": 4096,
"max_output_tokens": 16384,
"knowledge_cutoff": null,
"modalities": {
- "input": [
- "text"
- ],
- "output": [
- "text"
- ]
+ "input": [],
+ "output": []
},
- "capabilities": [
- "streaming"
- ],
+ "capabilities": [],
"pricing": {
"text_tokens": {
"standard": {
@@ -8942,24 +24551,18 @@
},
{
"id": "computer-use-preview-2025-03-11",
- "name": "Computer Use Preview 20250311",
+ "name": "computer-use-preview-2025-03-11",
"provider": "openai",
- "family": "other",
- "created_at": "2025-03-08 01:20:21 +0530",
+ "family": null,
+ "created_at": "2025-03-07 19:50:21 UTC",
"context_window": 4096,
"max_output_tokens": 16384,
"knowledge_cutoff": null,
"modalities": {
- "input": [
- "text"
- ],
- "output": [
- "text"
- ]
+ "input": [],
+ "output": []
},
- "capabilities": [
- "streaming"
- ],
+ "capabilities": [],
"pricing": {
"text_tokens": {
"standard": {
@@ -8975,25 +24578,18 @@
},
{
"id": "dall-e-2",
- "name": "DALL-E-2",
+ "name": "dall-e-2",
"provider": "openai",
- "family": "dall_e",
- "created_at": "2023-11-01 05:52:57 +0530",
+ "family": null,
+ "created_at": "2023-11-01 00:22:57 UTC",
"context_window": 4096,
"max_output_tokens": 16384,
"knowledge_cutoff": null,
"modalities": {
- "input": [
- "text"
- ],
- "output": [
- "text",
- "image"
- ]
+ "input": [],
+ "output": []
},
- "capabilities": [
- "streaming"
- ],
+ "capabilities": [],
"pricing": {
"text_tokens": {
"standard": {
@@ -9009,25 +24605,18 @@
},
{
"id": "dall-e-3",
- "name": "DALL-E-3",
+ "name": "dall-e-3",
"provider": "openai",
- "family": "dall_e",
- "created_at": "2023-11-01 02:16:29 +0530",
+ "family": null,
+ "created_at": "2023-10-31 20:46:29 UTC",
"context_window": 4096,
"max_output_tokens": 16384,
"knowledge_cutoff": null,
"modalities": {
- "input": [
- "text"
- ],
- "output": [
- "text",
- "image"
- ]
+ "input": [],
+ "output": []
},
- "capabilities": [
- "streaming"
- ],
+ "capabilities": [],
"pricing": {
"text_tokens": {
"standard": {
@@ -9043,24 +24632,18 @@
},
{
"id": "davinci-002",
- "name": "Davinci 002",
+ "name": "davinci-002",
"provider": "openai",
- "family": "davinci",
- "created_at": "2023-08-21 21:41:41 +0530",
+ "family": null,
+ "created_at": "2023-08-21 16:11:41 UTC",
"context_window": 4096,
"max_output_tokens": 16384,
"knowledge_cutoff": null,
"modalities": {
- "input": [
- "text"
- ],
- "output": [
- "text"
- ]
+ "input": [],
+ "output": []
},
- "capabilities": [
- "streaming"
- ],
+ "capabilities": [],
"pricing": {
"text_tokens": {
"standard": {
@@ -9079,7 +24662,7 @@
"name": "GPT-3.5-turbo",
"provider": "openai",
"family": "gpt",
- "created_at": "2023-03-01 00:00:00 +0530",
+ "created_at": "2023-03-01 00:00:00 UTC",
"context_window": 16385,
"max_output_tokens": 4096,
"knowledge_cutoff": "2021-09-01",
@@ -9091,15 +24674,13 @@
"text"
]
},
- "capabilities": [
- "streaming"
- ],
+ "capabilities": [],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.5,
"output_per_million": 1.5,
- "cached_input_per_million": 1.25
+ "cache_read_input_per_million": 1.25
}
}
},
@@ -9126,24 +24707,18 @@
},
{
"id": "gpt-3.5-turbo-0125",
- "name": "GPT-3.5 Turbo 0125",
+ "name": "gpt-3.5-turbo-0125",
"provider": "openai",
- "family": "gpt35_turbo",
- "created_at": "2024-01-24 03:49:18 +0530",
+ "family": null,
+ "created_at": "2024-01-23 22:19:18 UTC",
"context_window": 16385,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
"modalities": {
- "input": [
- "text"
- ],
- "output": [
- "text"
- ]
+ "input": [],
+ "output": []
},
- "capabilities": [
- "streaming"
- ],
+ "capabilities": [],
"pricing": {
"text_tokens": {
"standard": {
@@ -9159,24 +24734,18 @@
},
{
"id": "gpt-3.5-turbo-1106",
- "name": "GPT-3.5 Turbo 1106",
+ "name": "gpt-3.5-turbo-1106",
"provider": "openai",
- "family": "gpt35_turbo",
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@@ -9192,24 +24761,18 @@
},
{
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- "name": "GPT-3.5 Turbo 16k",
+ "name": "gpt-3.5-turbo-16k",
"provider": "openai",
- "family": "gpt35_turbo",
- "created_at": "2023-05-11 04:05:02 +0530",
+ "family": null,
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@@ -9225,24 +24788,18 @@
},
{
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- "name": "GPT-3.5 Turbo Instruct",
+ "name": "gpt-3.5-turbo-instruct",
"provider": "openai",
- "family": "gpt35_turbo",
- "created_at": "2023-08-24 23:53:47 +0530",
+ "family": null,
+ "created_at": "2023-08-24 18:23:47 UTC",
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@@ -9258,24 +24815,18 @@
},
{
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+ "name": "gpt-3.5-turbo-instruct-0914",
"provider": "openai",
- "family": "gpt35_turbo",
- "created_at": "2023-09-08 03:04:32 +0530",
+ "family": null,
+ "created_at": "2023-09-07 21:34:32 UTC",
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@@ -9294,7 +24845,7 @@
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"family": "gpt",
- "created_at": "2023-11-06 00:00:00 +0530",
+ "created_at": "2023-11-06 00:00:00 UTC",
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@@ -9308,7 +24859,7 @@
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@@ -9340,24 +24891,18 @@
},
{
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- "name": "GPT-4 0613",
+ "name": "gpt-4-0613",
"provider": "openai",
- "family": "other",
- "created_at": "2023-06-12 22:24:56 +0530",
+ "family": null,
+ "created_at": "2023-06-12 16:54:56 UTC",
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@@ -9376,7 +24921,7 @@
"name": "GPT-4 Turbo",
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"family": "gpt",
- "created_at": "2023-11-06 00:00:00 +0530",
+ "created_at": "2023-11-06 00:00:00 UTC",
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@@ -9391,8 +24936,7 @@
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@@ -9424,26 +24968,20 @@
},
{
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- "name": "GPT-4 Turbo 20240409",
+ "name": "gpt-4-turbo-2024-04-09",
"provider": "openai",
- "family": "gpt4_turbo",
- "created_at": "2024-04-09 00:11:17 +0530",
+ "family": null,
+ "created_at": "2024-04-08 18:41:17 UTC",
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@@ -9463,7 +25001,7 @@
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+ "created_at": "2025-04-14 00:00:00 UTC",
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@@ -9480,15 +25018,14 @@
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}
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@@ -9515,34 +25052,28 @@
},
{
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- "name": "GPT-4.1 20250414",
+ "name": "gpt-4.1-2025-04-14",
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- "family": "gpt41",
- "created_at": "2025-04-11 01:39:06 +0530",
+ "family": null,
+ "created_at": "2025-04-10 20:09:06 UTC",
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@@ -9556,7 +25087,7 @@
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+ "created_at": "2025-04-14 00:00:00 UTC",
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@@ -9573,15 +25104,14 @@
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@@ -9608,34 +25138,28 @@
},
{
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+ "name": "gpt-4.1-mini-2025-04-14",
"provider": "openai",
- "family": "gpt41_mini",
- "created_at": "2025-04-11 02:09:07 +0530",
+ "family": null,
+ "created_at": "2025-04-10 20:39:07 UTC",
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@@ -9649,7 +25173,7 @@
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"family": "gpt-nano",
- "created_at": "2025-04-14 00:00:00 +0530",
+ "created_at": "2025-04-14 00:00:00 UTC",
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@@ -9665,15 +25189,14 @@
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@@ -9700,27 +25223,21 @@
},
{
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+ "name": "gpt-4.1-nano-2025-04-14",
"provider": "openai",
- "family": "gpt41_nano",
- "created_at": "2025-04-11 03:07:05 +0530",
+ "family": null,
+ "created_at": "2025-04-10 21:37:05 UTC",
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@@ -9740,7 +25257,7 @@
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+ "created_at": "2024-05-13 00:00:00 UTC",
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@@ -9757,15 +25274,14 @@
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@@ -9795,7 +25311,7 @@
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"family": "gpt",
- "created_at": "2024-05-13 00:00:00 +0530",
+ "created_at": "2024-05-13 00:00:00 UTC",
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@@ -9811,8 +25327,7 @@
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@@ -9847,7 +25362,7 @@
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+ "created_at": "2024-08-06 00:00:00 UTC",
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@@ -9863,15 +25378,14 @@
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@@ -9901,7 +25415,7 @@
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+ "created_at": "2024-11-20 00:00:00 UTC",
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@@ -9917,15 +25431,14 @@
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}
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},
@@ -9952,28 +25465,18 @@
},
{
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- "name": "GPT-4o-Audio Preview",
+ "name": "gpt-4o-audio-preview",
"provider": "openai",
- "family": "gpt4o_audio",
- "created_at": "2024-09-27 23:37:23 +0530",
+ "family": null,
+ "created_at": "2024-09-27 18:07:23 UTC",
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- "audio"
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+ "input": [],
+ "output": []
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- "transcription"
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@@ -9989,28 +25492,18 @@
},
{
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+ "name": "gpt-4o-audio-preview-2024-12-17",
"provider": "openai",
- "family": "gpt4o_audio",
- "created_at": "2024-12-13 01:40:39 +0530",
+ "family": null,
+ "created_at": "2024-12-12 20:10:39 UTC",
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+ "input": [],
+ "output": []
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- "transcription"
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@@ -10026,28 +25519,18 @@
},
{
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- "name": "GPT-4o-Audio Preview 20250603",
+ "name": "gpt-4o-audio-preview-2025-06-03",
"provider": "openai",
- "family": "gpt4o_audio",
- "created_at": "2025-06-03 05:24:58 +0530",
+ "family": null,
+ "created_at": "2025-06-02 23:54:58 UTC",
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- "audio"
- ],
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+ "input": [],
+ "output": []
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- "transcription"
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@@ -10066,7 +25549,7 @@
"name": "GPT-4o mini",
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"family": "gpt-mini",
- "created_at": "2024-07-18 00:00:00 +0530",
+ "created_at": "2024-07-18 00:00:00 UTC",
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@@ -10083,15 +25566,14 @@
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},
@@ -10118,27 +25600,21 @@
},
{
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- "name": "GPT-4o-Mini 20240718",
+ "name": "gpt-4o-mini-2024-07-18",
"provider": "openai",
- "family": "gpt4o_mini",
- "created_at": "2024-07-17 05:01:57 +0530",
+ "family": null,
+ "created_at": "2024-07-16 23:31:57 UTC",
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- "image",
- "pdf"
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+ "input": [],
+ "output": []
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+ "structured_output",
+ "vision"
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@@ -10155,28 +25631,18 @@
},
{
"id": "gpt-4o-mini-audio-preview",
- "name": "GPT-4o-Mini Audio Preview",
+ "name": "gpt-4o-mini-audio-preview",
"provider": "openai",
- "family": "gpt4o_mini_audio",
- "created_at": "2024-12-17 03:47:04 +0530",
+ "family": null,
+ "created_at": "2024-12-16 22:17:04 UTC",
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- ],
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+ "input": [],
+ "output": []
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- "transcription"
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+ "capabilities": [],
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@@ -10192,28 +25658,18 @@
},
{
"id": "gpt-4o-mini-audio-preview-2024-12-17",
- "name": "GPT-4o-Mini Audio Preview 20241217",
+ "name": "gpt-4o-mini-audio-preview-2024-12-17",
"provider": "openai",
- "family": "gpt4o_mini_audio",
- "created_at": "2024-12-14 00:22:00 +0530",
+ "family": null,
+ "created_at": "2024-12-13 18:52:00 UTC",
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+ "input": [],
+ "output": []
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- "transcription"
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@@ -10229,24 +25685,18 @@
},
{
"id": "gpt-4o-mini-realtime-preview",
- "name": "GPT-4o-Mini Realtime Preview",
+ "name": "gpt-4o-mini-realtime-preview",
"provider": "openai",
- "family": "gpt4o_mini_realtime",
- "created_at": "2024-12-17 03:46:20 +0530",
+ "family": null,
+ "created_at": "2024-12-16 22:16:20 UTC",
"context_window": 128000,
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+ "max_output_tokens": 16384,
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+ "input": [],
+ "output": []
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@@ -10262,24 +25712,18 @@
},
{
"id": "gpt-4o-mini-realtime-preview-2024-12-17",
- "name": "GPT-4o-Mini Realtime Preview 20241217",
+ "name": "gpt-4o-mini-realtime-preview-2024-12-17",
"provider": "openai",
- "family": "gpt4o_mini_realtime",
- "created_at": "2024-12-13 23:26:41 +0530",
+ "family": null,
+ "created_at": "2024-12-13 17:56:41 UTC",
"context_window": 128000,
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+ "max_output_tokens": 16384,
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+ "input": [],
+ "output": []
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@@ -10295,24 +25739,18 @@
},
{
"id": "gpt-4o-mini-search-preview",
- "name": "GPT-4o-Mini Search Preview",
+ "name": "gpt-4o-mini-search-preview",
"provider": "openai",
- "family": "other",
- "created_at": "2025-03-08 05:16:01 +0530",
+ "family": null,
+ "created_at": "2025-03-07 23:46:01 UTC",
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"knowledge_cutoff": null,
"modalities": {
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- "text"
- ],
- "output": [
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+ "input": [],
+ "output": []
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@@ -10328,24 +25766,18 @@
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@@ -10361,25 +25793,18 @@
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@@ -10429,25 +25847,18 @@
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@@ -10463,26 +25874,18 @@
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@@ -10498,26 +25901,18 @@
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@@ -10533,26 +25928,18 @@
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@@ -10568,24 +25955,18 @@
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@@ -10601,24 +25982,18 @@
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+ "name": "gpt-4o-realtime-preview-2024-12-17",
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@@ -10634,24 +26009,18 @@
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+ "name": "gpt-4o-realtime-preview-2025-06-03",
"provider": "openai",
- "family": "gpt4o_realtime",
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@@ -10667,25 +26036,19 @@
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{
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+ "name": "gpt-4o-search-preview",
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@@ -10702,25 +26065,19 @@
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+ "name": "gpt-4o-search-preview-2025-03-11",
"provider": "openai",
- "family": "gpt4o_search",
- "created_at": "2026-02-24 09:30:21 +0530",
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@@ -10737,25 +26094,18 @@
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@@ -10771,25 +26121,18 @@
},
{
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+ "name": "gpt-4o-transcribe-diarize",
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- "family": "gpt4o_transcribe",
- "created_at": "2025-06-25 02:31:27 +0530",
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@@ -10808,7 +26151,7 @@
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+ "created_at": "2025-08-07 00:00:00 UTC",
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@@ -10825,15 +26168,14 @@
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@@ -10861,27 +26203,21 @@
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+ "name": "gpt-5-2025-08-07",
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+ "family": null,
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@@ -10889,7 +26225,7 @@
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@@ -10903,7 +26239,7 @@
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+ "created_at": "2025-08-07 00:00:00 UTC",
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@@ -10920,7 +26256,6 @@
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@@ -10957,7 +26292,7 @@
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+ "created_at": "2025-09-15 00:00:00 UTC",
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@@ -10974,15 +26309,14 @@
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@@ -11013,7 +26347,7 @@
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+ "created_at": "2025-08-07 00:00:00 UTC",
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@@ -11030,15 +26364,14 @@
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@@ -11066,35 +26399,29 @@
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+ "name": "gpt-5-mini-2025-08-07",
"provider": "openai",
- "family": "gpt5",
- "created_at": "2025-08-06 02:01:07 +0530",
+ "family": null,
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@@ -11108,7 +26435,7 @@
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+ "created_at": "2025-08-07 00:00:00 UTC",
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@@ -11125,15 +26452,14 @@
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@@ -11161,35 +26487,29 @@
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+ "name": "gpt-5-nano-2025-08-07",
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- "family": "gpt5",
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@@ -11203,7 +26523,7 @@
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+ "created_at": "2025-10-06 00:00:00 UTC",
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@@ -11220,8 +26540,7 @@
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@@ -11254,27 +26573,21 @@
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{
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+ "name": "gpt-5-pro-2025-10-06",
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- "family": "gpt5",
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+ "family": null,
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@@ -11282,7 +26595,7 @@
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@@ -11293,27 +26606,21 @@
},
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+ "name": "gpt-5-search-api",
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- "family": "gpt5",
- "created_at": "2025-10-03 23:33:49 +0530",
+ "family": null,
+ "created_at": "2025-10-03 18:03:49 UTC",
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@@ -11321,7 +26628,7 @@
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@@ -11332,27 +26639,21 @@
},
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+ "name": "gpt-5-search-api-2025-10-14",
"provider": "openai",
- "family": "gpt5",
- "created_at": "2025-10-10 02:36:00 +0530",
+ "family": null,
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@@ -11360,7 +26661,7 @@
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@@ -11374,7 +26675,7 @@
"name": "GPT-5.1",
"provider": "openai",
"family": "gpt",
- "created_at": "2025-11-13 00:00:00 +0530",
+ "created_at": "2025-11-13 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2024-09-30",
@@ -11391,15 +26692,14 @@
"function_calling",
"structured_output",
"reasoning",
- "vision",
- "streaming"
+ "vision"
],
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"output_per_million": 10,
- "cached_input_per_million": 0.13
+ "cache_read_input_per_million": 0.13
}
}
},
@@ -11427,27 +26727,21 @@
},
{
"id": "gpt-5.1-2025-11-13",
- "name": "GPT-5.1 20251113",
+ "name": "gpt-5.1-2025-11-13",
"provider": "openai",
- "family": "gpt5",
- "created_at": "2025-11-11 00:15:53 +0530",
+ "family": null,
+ "created_at": "2025-11-10 18:45:53 UTC",
"context_window": 128000,
"max_output_tokens": 400000,
"knowledge_cutoff": null,
"modalities": {
- "input": [
- "text",
- "image",
- "pdf"
- ],
- "output": [
- "text"
- ]
+ "input": [],
+ "output": []
},
"capabilities": [
- "streaming",
"function_calling",
"structured_output",
+ "vision",
"reasoning"
],
"pricing": {
@@ -11455,7 +26749,7 @@
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+ "cache_read_input_per_million": 0.125
}
}
},
@@ -11469,7 +26763,7 @@
"name": "GPT-5.1 Chat",
"provider": "openai",
"family": "gpt-codex",
- "created_at": "2025-11-13 00:00:00 +0530",
+ "created_at": "2025-11-13 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 16384,
"knowledge_cutoff": "2024-09-30",
@@ -11486,15 +26780,14 @@
"function_calling",
"structured_output",
"reasoning",
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+ "vision"
],
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"output_per_million": 10,
- "cached_input_per_million": 0.125
+ "cache_read_input_per_million": 0.125
}
}
},
@@ -11524,7 +26817,7 @@
"name": "GPT-5.1 Codex",
"provider": "openai",
"family": "gpt-codex",
- "created_at": "2025-11-13 00:00:00 +0530",
+ "created_at": "2025-11-13 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2024-09-30",
@@ -11541,15 +26834,14 @@
"function_calling",
"structured_output",
"reasoning",
- "vision",
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+ "vision"
],
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"output_per_million": 10,
- "cached_input_per_million": 0.125
+ "cache_read_input_per_million": 0.125
}
}
},
@@ -11580,7 +26872,7 @@
"name": "GPT-5.1 Codex Max",
"provider": "openai",
"family": "gpt-codex",
- "created_at": "2025-11-13 00:00:00 +0530",
+ "created_at": "2025-11-13 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2024-09-30",
@@ -11597,15 +26889,14 @@
"function_calling",
"structured_output",
"reasoning",
- "vision",
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+ "vision"
],
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"output_per_million": 10,
- "cached_input_per_million": 0.125
+ "cache_read_input_per_million": 0.125
}
}
},
@@ -11636,7 +26927,7 @@
"name": "GPT-5.1 Codex mini",
"provider": "openai",
"family": "gpt-codex",
- "created_at": "2025-11-13 00:00:00 +0530",
+ "created_at": "2025-11-13 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2024-09-30",
@@ -11653,15 +26944,14 @@
"function_calling",
"structured_output",
"reasoning",
- "vision",
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+ "vision"
],
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- "cached_input_per_million": 0.025
+ "cache_read_input_per_million": 0.025
}
}
},
@@ -11692,7 +26982,7 @@
"name": "GPT-5.2",
"provider": "openai",
"family": "gpt",
- "created_at": "2025-12-11 00:00:00 +0530",
+ "created_at": "2025-12-11 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2025-08-31",
@@ -11709,15 +26999,14 @@
"function_calling",
"structured_output",
"reasoning",
- "vision",
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+ "vision"
],
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"output_per_million": 14,
- "cached_input_per_million": 0.175
+ "cache_read_input_per_million": 0.175
}
}
},
@@ -11745,27 +27034,21 @@
},
{
"id": "gpt-5.2-2025-12-11",
- "name": "GPT-5.2 20251211",
+ "name": "gpt-5.2-2025-12-11",
"provider": "openai",
- "family": "gpt5",
- "created_at": "2025-12-10 02:13:48 +0530",
+ "family": null,
+ "created_at": "2025-12-09 20:43:48 UTC",
"context_window": 128000,
"max_output_tokens": 400000,
"knowledge_cutoff": null,
"modalities": {
- "input": [
- "text",
- "image",
- "pdf"
- ],
- "output": [
- "text"
- ]
+ "input": [],
+ "output": []
},
"capabilities": [
- "streaming",
"function_calling",
"structured_output",
+ "vision",
"reasoning"
],
"pricing": {
@@ -11773,7 +27056,7 @@
"standard": {
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- "cached_input_per_million": 0.125
+ "cache_read_input_per_million": 0.125
}
}
},
@@ -11787,7 +27070,7 @@
"name": "GPT-5.2 Chat",
"provider": "openai",
"family": "gpt-codex",
- "created_at": "2025-12-11 00:00:00 +0530",
+ "created_at": "2025-12-11 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 16384,
"knowledge_cutoff": "2025-08-31",
@@ -11804,15 +27087,14 @@
"function_calling",
"structured_output",
"reasoning",
- "vision",
- "streaming"
+ "vision"
],
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"output_per_million": 14,
- "cached_input_per_million": 0.175
+ "cache_read_input_per_million": 0.175
}
}
},
@@ -11842,7 +27124,7 @@
"name": "GPT-5.2 Codex",
"provider": "openai",
"family": "gpt-codex",
- "created_at": "2025-12-11 00:00:00 +0530",
+ "created_at": "2025-12-11 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2025-08-31",
@@ -11860,15 +27142,14 @@
"function_calling",
"structured_output",
"reasoning",
- "vision",
- "streaming"
+ "vision"
],
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"output_per_million": 14,
- "cached_input_per_million": 0.175
+ "cache_read_input_per_million": 0.175
}
}
},
@@ -11899,7 +27180,7 @@
"name": "GPT-5.2 Pro",
"provider": "openai",
"family": "gpt-pro",
- "created_at": "2025-12-11 00:00:00 +0530",
+ "created_at": "2025-12-11 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2025-08-31",
@@ -11916,7 +27197,6 @@
"function_calling",
"reasoning",
"vision",
- "streaming",
"structured_output"
],
"pricing": {
@@ -11950,27 +27230,21 @@
},
{
"id": "gpt-5.2-pro-2025-12-11",
- "name": "GPT-5.2 Pro 20251211",
+ "name": "gpt-5.2-pro-2025-12-11",
"provider": "openai",
- "family": "gpt5",
- "created_at": "2025-12-10 10:49:19 +0530",
+ "family": null,
+ "created_at": "2025-12-10 05:19:19 UTC",
"context_window": 128000,
"max_output_tokens": 400000,
"knowledge_cutoff": null,
"modalities": {
- "input": [
- "text",
- "image",
- "pdf"
- ],
- "output": [
- "text"
- ]
+ "input": [],
+ "output": []
},
"capabilities": [
- "streaming",
"function_calling",
"structured_output",
+ "vision",
"reasoning"
],
"pricing": {
@@ -11978,7 +27252,7 @@
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"output_per_million": 10.0,
- "cached_input_per_million": 0.125
+ "cache_read_input_per_million": 0.125
}
}
},
@@ -11992,7 +27266,7 @@
"name": "GPT-5.3 Chat (latest)",
"provider": "openai",
"family": "gpt",
- "created_at": "2026-03-03 00:00:00 +0530",
+ "created_at": "2026-03-03 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 16384,
"knowledge_cutoff": "2025-08-31",
@@ -12009,7 +27283,6 @@
"function_calling",
"structured_output",
"vision",
- "streaming",
"reasoning"
],
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@@ -12017,7 +27290,7 @@
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- "cached_input_per_million": 0.175
+ "cache_read_input_per_million": 0.175
}
}
},
@@ -12047,7 +27320,7 @@
"name": "GPT-5.3 Codex",
"provider": "openai",
"family": "gpt-codex",
- "created_at": "2026-02-05 00:00:00 +0530",
+ "created_at": "2026-02-05 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2025-08-31",
@@ -12065,15 +27338,14 @@
"function_calling",
"structured_output",
"reasoning",
- "vision",
- "streaming"
+ "vision"
],
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"output_per_million": 14,
- "cached_input_per_million": 0.175
+ "cache_read_input_per_million": 0.175
}
}
},
@@ -12104,7 +27376,7 @@
"name": "GPT-5.3 Codex Spark",
"provider": "openai",
"family": "gpt-codex-spark",
- "created_at": "2026-02-05 00:00:00 +0530",
+ "created_at": "2026-02-05 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 32000,
"knowledge_cutoff": "2025-08-31",
@@ -12129,7 +27401,7 @@
"standard": {
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"output_per_million": 14,
- "cached_input_per_million": 0.175
+ "cache_read_input_per_million": 0.175
}
}
},
@@ -12158,7 +27430,7 @@
"name": "GPT-5.4",
"provider": "openai",
"family": "gpt",
- "created_at": "2026-03-05 00:00:00 +0530",
+ "created_at": "2026-03-05 00:00:00 UTC",
"context_window": 1050000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2025-08-31",
@@ -12176,15 +27448,14 @@
"function_calling",
"structured_output",
"reasoning",
- "vision",
- "streaming"
+ "vision"
],
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"output_per_million": 15,
- "cached_input_per_million": 0.25
+ "cache_read_input_per_million": 0.25
}
}
},
@@ -12217,27 +27488,21 @@
},
{
"id": "gpt-5.4-2026-03-05",
- "name": "GPT-5.4 20260305",
+ "name": "gpt-5.4-2026-03-05",
"provider": "openai",
- "family": "gpt5",
- "created_at": "2026-03-05 01:24:22 +0530",
+ "family": null,
+ "created_at": "2026-03-04 19:54:22 UTC",
"context_window": 128000,
"max_output_tokens": 400000,
"knowledge_cutoff": null,
"modalities": {
- "input": [
- "text",
- "image",
- "pdf"
- ],
- "output": [
- "text"
- ]
+ "input": [],
+ "output": []
},
"capabilities": [
- "streaming",
"function_calling",
"structured_output",
+ "vision",
"reasoning"
],
"pricing": {
@@ -12245,7 +27510,7 @@
"standard": {
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"output_per_million": 10.0,
- "cached_input_per_million": 0.125
+ "cache_read_input_per_million": 0.125
}
}
},
@@ -12259,7 +27524,7 @@
"name": "GPT-5.4 mini",
"provider": "openai",
"family": "gpt-mini",
- "created_at": "2026-03-17 00:00:00 +0530",
+ "created_at": "2026-03-17 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2025-08-31",
@@ -12276,15 +27541,14 @@
"function_calling",
"structured_output",
"reasoning",
- "vision",
- "streaming"
+ "vision"
],
"pricing": {
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"output_per_million": 4.5,
- "cached_input_per_million": 0.075
+ "cache_read_input_per_million": 0.075
}
}
},
@@ -12312,35 +27576,29 @@
},
{
"id": "gpt-5.4-mini-2026-03-17",
- "name": "GPT-5.4 Mini 20260317",
+ "name": "gpt-5.4-mini-2026-03-17",
"provider": "openai",
- "family": "gpt5",
- "created_at": "2026-03-14 06:47:56 +0530",
+ "family": null,
+ "created_at": "2026-03-14 01:17:56 UTC",
"context_window": 128000,
"max_output_tokens": 400000,
"knowledge_cutoff": null,
"modalities": {
- "input": [
- "text",
- "image",
- "pdf"
- ],
- "output": [
- "text"
- ]
+ "input": [],
+ "output": []
},
"capabilities": [
- "streaming",
"function_calling",
"structured_output",
+ "vision",
"reasoning"
],
"pricing": {
"text_tokens": {
"standard": {
- "input_per_million": 1.25,
- "output_per_million": 10.0,
- "cached_input_per_million": 0.125
+ "input_per_million": 0.25,
+ "output_per_million": 2.0,
+ "cache_read_input_per_million": 0.025
}
}
},
@@ -12354,7 +27612,7 @@
"name": "GPT-5.4 nano",
"provider": "openai",
"family": "gpt-nano",
- "created_at": "2026-03-17 00:00:00 +0530",
+ "created_at": "2026-03-17 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2025-08-31",
@@ -12371,15 +27629,14 @@
"function_calling",
"structured_output",
"reasoning",
- "vision",
- "streaming"
+ "vision"
],
"pricing": {
"text_tokens": {
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"output_per_million": 1.25,
- "cached_input_per_million": 0.02
+ "cache_read_input_per_million": 0.02
}
}
},
@@ -12407,35 +27664,29 @@
},
{
"id": "gpt-5.4-nano-2026-03-17",
- "name": "GPT-5.4 Nano 20260317",
+ "name": "gpt-5.4-nano-2026-03-17",
"provider": "openai",
- "family": "gpt5",
- "created_at": "2026-03-14 06:43:57 +0530",
+ "family": null,
+ "created_at": "2026-03-14 01:13:57 UTC",
"context_window": 128000,
"max_output_tokens": 400000,
"knowledge_cutoff": null,
"modalities": {
- "input": [
- "text",
- "image",
- "pdf"
- ],
- "output": [
- "text"
- ]
+ "input": [],
+ "output": []
},
"capabilities": [
- "streaming",
"function_calling",
"structured_output",
+ "vision",
"reasoning"
],
"pricing": {
"text_tokens": {
"standard": {
- "input_per_million": 1.25,
- "output_per_million": 10.0,
- "cached_input_per_million": 0.125
+ "input_per_million": 0.05,
+ "output_per_million": 0.4,
+ "cache_read_input_per_million": 0.005
}
}
},
@@ -12449,7 +27700,7 @@
"name": "GPT-5.4 Pro",
"provider": "openai",
"family": "gpt-pro",
- "created_at": "2026-03-05 00:00:00 +0530",
+ "created_at": "2026-03-05 00:00:00 UTC",
"context_window": 1050000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2025-08-31",
@@ -12466,7 +27717,6 @@
"function_calling",
"reasoning",
"vision",
- "streaming",
"structured_output"
],
"pricing": {
@@ -12504,13 +27754,46 @@
},
{
"id": "gpt-5.4-pro-2026-03-05",
- "name": "GPT-5.4 Pro 20260305",
+ "name": "gpt-5.4-pro-2026-03-05",
"provider": "openai",
- "family": "gpt5",
- "created_at": "2026-03-05 02:57:37 +0530",
+ "family": null,
+ "created_at": "2026-03-04 21:27:37 UTC",
"context_window": 128000,
"max_output_tokens": 400000,
"knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision",
+ "reasoning"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 1.25,
+ "output_per_million": 10.0,
+ "cache_read_input_per_million": 0.125
+ }
+ }
+ },
+ "metadata": {
+ "object": "model",
+ "owned_by": "system"
+ }
+ },
+ {
+ "id": "gpt-5.5",
+ "name": "GPT-5.5",
+ "provider": "openai",
+ "family": "gpt",
+ "created_at": "2026-04-23 00:00:00 UTC",
+ "context_window": 1050000,
+ "max_output_tokens": 128000,
+ "knowledge_cutoff": "2025-12-01",
"modalities": {
"input": [
"text",
@@ -12522,9 +27805,64 @@
]
},
"capabilities": [
- "streaming",
"function_calling",
"structured_output",
+ "reasoning",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 5,
+ "output_per_million": 30,
+ "cache_read_input_per_million": 0.5
+ }
+ }
+ },
+ "metadata": {
+ "object": "model",
+ "owned_by": "system",
+ "source": "models.dev",
+ "provider_id": "openai",
+ "open_weights": false,
+ "attachment": true,
+ "temperature": false,
+ "last_updated": "2026-04-23",
+ "cost": {
+ "input": 5,
+ "output": 30,
+ "cache_read": 0.5,
+ "context_over_200k": {
+ "input": 10,
+ "output": 45,
+ "cache_read": 1
+ }
+ },
+ "limit": {
+ "context": 1050000,
+ "input": 922000,
+ "output": 128000
+ },
+ "knowledge": "2025-12-01"
+ }
+ },
+ {
+ "id": "gpt-5.5-2026-04-23",
+ "name": "gpt-5.5-2026-04-23",
+ "provider": "openai",
+ "family": null,
+ "created_at": "2026-04-22 06:27:21 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 400000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [],
+ "output": []
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision",
"reasoning"
],
"pricing": {
@@ -12532,7 +27870,98 @@
"standard": {
"input_per_million": 1.25,
"output_per_million": 10.0,
- "cached_input_per_million": 0.125
+ "cache_read_input_per_million": 0.125
+ }
+ }
+ },
+ "metadata": {
+ "object": "model",
+ "owned_by": "system"
+ }
+ },
+ {
+ "id": "gpt-5.5-pro",
+ "name": "GPT-5.5 Pro",
+ "provider": "openai",
+ "family": "gpt-pro",
+ "created_at": "2026-04-23 00:00:00 UTC",
+ "context_window": 1050000,
+ "max_output_tokens": 128000,
+ "knowledge_cutoff": "2025-12-01",
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "pdf"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "reasoning",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 30,
+ "output_per_million": 180
+ }
+ }
+ },
+ "metadata": {
+ "object": "model",
+ "owned_by": "system",
+ "source": "models.dev",
+ "provider_id": "openai",
+ "open_weights": false,
+ "attachment": true,
+ "temperature": false,
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@@ -12718,26 +28107,18 @@
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@@ -12795,7 +28189,7 @@
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@@ -12871,25 +28291,73 @@
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@@ -12905,24 +28373,18 @@
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@@ -12971,24 +28427,18 @@
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@@ -13004,24 +28454,18 @@
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@@ -13037,24 +28481,18 @@
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@@ -13073,7 +28511,7 @@
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@@ -13091,15 +28529,14 @@
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@@ -13126,27 +28563,21 @@
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@@ -13167,7 +28598,7 @@
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@@ -13188,7 +28619,7 @@
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@@ -13264,7 +28695,7 @@
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@@ -13281,8 +28712,7 @@
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@@ -13314,27 +28744,21 @@
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@@ -13355,7 +28779,7 @@
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@@ -13373,15 +28797,14 @@
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@@ -13408,23 +28831,18 @@
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@@ -13445,7 +28863,7 @@
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@@ -13461,15 +28879,14 @@
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@@ -13496,23 +28913,18 @@
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@@ -13533,7 +28945,7 @@
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@@ -13548,15 +28960,14 @@
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@@ -13583,23 +28994,18 @@
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- "created_at": "2025-04-08 23:01:46 +0530",
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@@ -13910,25 +29293,20 @@
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@@ -14284,25 +29612,18 @@
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@@ -14316,12 +29637,1068 @@
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+ "metadata": {
+ "description": "A large LLM created by combining two fine-tuned Llama 70B models into one 120B model. Combines Xwin and Euryale. Credits to - [@chargoddard](https://huggingface.co/chargoddard) for developing the framework used to merge...",
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+ "top_logprobs",
+ "top_p"
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+ }
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+ "provider": "openrouter",
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+ "created_at": "2025-12-02 17:31:12 UTC",
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+ "architecture": {
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+ "name": "Amazon: Nova Lite 1.0",
+ "provider": "openrouter",
+ "family": "amazon",
+ "created_at": "2024-12-05 22:22:43 UTC",
+ "context_window": 300000,
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+ "output_per_million": 0.24
+ }
+ }
+ },
+ "metadata": {
+ "description": "Amazon Nova Lite 1.0 is a very low-cost multimodal model from Amazon that focused on fast processing of image, video, and text inputs to generate text output. Amazon Nova Lite...",
+ "architecture": {
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+ ]
+ }
+ },
+ {
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+ "name": "Amazon: Nova Micro 1.0",
+ "provider": "openrouter",
+ "family": "amazon",
+ "created_at": "2024-12-05 22:20:37 UTC",
+ "context_window": 128000,
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+ "output_per_million": 0.14
+ }
+ }
+ },
+ "metadata": {
+ "description": "Amazon Nova Micro 1.0 is a text-only model that delivers the lowest latency responses in the Amazon Nova family of models at a very low cost. With a context length...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
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+ "text"
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+ "tokenizer": "Nova",
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+ "temperature",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "amazon/nova-premier-v1",
+ "name": "Amazon: Nova Premier 1.0",
+ "provider": "openrouter",
+ "family": "amazon",
+ "created_at": "2025-10-31 22:38:52 UTC",
+ "context_window": 1000000,
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+ "output_per_million": 12.5,
+ "cache_read_input_per_million": 0.625
+ }
+ }
+ },
+ "metadata": {
+ "description": "Amazon Nova Premier is the most capable of Amazon’s multimodal models for complex reasoning tasks and for use as the best teacher for distilling custom models.",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
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+ "temperature",
+ "tools",
+ "top_k",
+ "top_p"
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+ }
+ },
+ {
+ "id": "amazon/nova-pro-v1",
+ "name": "Amazon: Nova Pro 1.0",
+ "provider": "openrouter",
+ "family": "amazon",
+ "created_at": "2024-12-05 22:05:03 UTC",
+ "context_window": 300000,
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+ "knowledge_cutoff": null,
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+ "input_per_million": 0.7999999999999999,
+ "output_per_million": 3.1999999999999997
+ }
+ }
+ },
+ "metadata": {
+ "description": "Amazon Nova Pro 1.0 is a capable multimodal model from Amazon focused on providing a combination of accuracy, speed, and cost for a wide range of tasks. As of December...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
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+ "max_completion_tokens": 5120,
+ "is_moderated": true
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+ "supported_parameters": [
+ "max_tokens",
+ "stop",
+ "temperature",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "anthracite-org/magnum-v4-72b",
+ "name": "Magnum v4 72B",
+ "provider": "openrouter",
+ "family": "anthracite-org",
+ "created_at": "2024-10-22 00:00:00 UTC",
+ "context_window": 16384,
+ "max_output_tokens": 2048,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
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+ "output": [
+ "text"
+ ]
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+ "capabilities": [
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+ "structured_output",
+ "predicted_outputs"
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+ "pricing": {
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+ "standard": {
+ "input_per_million": 3.0,
+ "output_per_million": 5.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "This is a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet(https://openrouter.ai/anthropic/claude-3.5-sonnet) and Opus(https://openrouter.ai/anthropic/claude-3-opus).\n\nThe model is fine-tuned on top of [Qwen2.5 72B](https://openrouter.ai/qwen/qwen-2.5-72b-instruct).",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen",
+ "instruct_type": "chatml"
+ },
+ "top_provider": {
+ "context_length": 16384,
+ "max_completion_tokens": 2048,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "temperature",
+ "top_a",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "anthropic/claude-3-haiku",
+ "name": "Anthropic: Claude 3 Haiku",
+ "provider": "openrouter",
+ "family": "anthropic",
+ "created_at": "2024-03-13 00:00:00 UTC",
+ "context_window": 200000,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.25,
+ "output_per_million": 1.25,
+ "cache_read_input_per_million": 0.03
+ }
+ }
+ },
+ "metadata": {
+ "description": "Claude 3 Haiku is Anthropic's fastest and most compact model for\nnear-instant responsiveness. Quick and accurate targeted performance.\n\nSee the launch announcement and benchmark results [here](https://www.anthropic.com/news/claude-3-haiku)\n\n#multimodal",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Claude",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 200000,
+ "max_completion_tokens": 4096,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
{
"id": "anthropic/claude-3.5-haiku",
"name": "Claude Haiku 3.5",
"provider": "openrouter",
"family": "claude-haiku",
- "created_at": "2024-10-22 00:00:00 +0530",
+ "created_at": "2024-10-22 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 8192,
"knowledge_cutoff": "2024-07-31",
@@ -14337,18 +30714,48 @@
},
"capabilities": [
"function_calling",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.8,
"output_per_million": 4,
- "cached_input_per_million": 0.08
+ "cache_read_input_per_million": 0.08,
+ "cache_write_input_per_million": 1
}
}
},
"metadata": {
+ "description": "Claude 3.5 Haiku features offers enhanced capabilities in speed, coding accuracy, and tool use. Engineered to excel in real-time applications, it delivers quick response times that are essential for dynamic...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Claude",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 200000,
+ "max_completion_tokens": 8192,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -14373,7 +30780,7 @@
"name": "Claude Sonnet 3.7",
"provider": "openrouter",
"family": "claude-sonnet",
- "created_at": "2025-02-19 00:00:00 +0530",
+ "created_at": "2025-02-19 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 128000,
"knowledge_cutoff": null,
@@ -14390,18 +30797,50 @@
"capabilities": [
"function_calling",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 15,
"output_per_million": 75,
- "cached_input_per_million": 1.5
+ "cache_read_input_per_million": 1.5,
+ "cache_write_input_per_million": 18.75
}
}
},
"metadata": {
+ "description": "Claude 3.7 Sonnet is an advanced large language model with improved reasoning, coding, and problem-solving capabilities. It introduces a hybrid reasoning approach, allowing users to choose between rapid responses and...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Claude",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 200000,
+ "max_completion_tokens": 64000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -14421,12 +30860,77 @@
"knowledge": "2024-01"
}
},
+ {
+ "id": "anthropic/claude-3.7-sonnet:thinking",
+ "name": "Anthropic: Claude 3.7 Sonnet (thinking)",
+ "provider": "openrouter",
+ "family": "anthropic",
+ "created_at": "2025-02-24 18:35:10 UTC",
+ "context_window": 200000,
+ "max_output_tokens": 64000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 3.0,
+ "output_per_million": 15.0,
+ "cache_read_input_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "description": "Claude 3.7 Sonnet is an advanced large language model with improved reasoning, coding, and problem-solving capabilities. It introduces a hybrid reasoning approach, allowing users to choose between rapid responses and...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Claude",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 200000,
+ "max_completion_tokens": 64000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
{
"id": "anthropic/claude-haiku-4.5",
"name": "Claude Haiku 4.5",
"provider": "openrouter",
"family": "claude-haiku",
- "created_at": "2025-10-15 00:00:00 +0530",
+ "created_at": "2025-10-15 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-02-28",
@@ -14444,18 +30948,52 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 1,
"output_per_million": 5,
- "cached_input_per_million": 0.1
+ "cache_read_input_per_million": 0.1,
+ "cache_write_input_per_million": 1.25
}
}
},
"metadata": {
+ "description": "Claude Haiku 4.5 is Anthropic’s fastest and most efficient model, delivering near-frontier intelligence at a fraction of the cost and latency of larger Claude models. Matching Claude Sonnet 4’s performance...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "image",
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Claude",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 200000,
+ "max_completion_tokens": 64000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -14480,7 +31018,7 @@
"name": "Claude Opus 4",
"provider": "openrouter",
"family": "claude-opus",
- "created_at": "2025-05-22 00:00:00 +0530",
+ "created_at": "2025-05-22 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 32000,
"knowledge_cutoff": "2025-03-31",
@@ -14497,18 +31035,51 @@
"capabilities": [
"function_calling",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 15,
"output_per_million": 75,
- "cached_input_per_million": 1.5
+ "cache_read_input_per_million": 1.5,
+ "cache_write_input_per_million": 18.75
}
}
},
"metadata": {
+ "description": "Claude Opus 4 is benchmarked as the world’s best coding model, at time of release, bringing sustained performance on complex, long-running tasks and agent workflows. It sets new benchmarks in...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Claude",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 200000,
+ "max_completion_tokens": 32000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -14533,7 +31104,7 @@
"name": "Claude Opus 4.1",
"provider": "openrouter",
"family": "claude-opus",
- "created_at": "2025-08-05 00:00:00 +0530",
+ "created_at": "2025-08-05 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 32000,
"knowledge_cutoff": "2025-03-31",
@@ -14551,18 +31122,53 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 15,
"output_per_million": 75,
- "cached_input_per_million": 1.5
+ "cache_read_input_per_million": 1.5,
+ "cache_write_input_per_million": 18.75
}
}
},
"metadata": {
+ "description": "Claude Opus 4.1 is an updated version of Anthropic’s flagship model, offering improved performance in coding, reasoning, and agentic tasks. It achieves 74.5% on SWE-bench Verified and shows notable gains...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Claude",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 200000,
+ "max_completion_tokens": 32000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -14587,7 +31193,7 @@
"name": "Claude Opus 4.5",
"provider": "openrouter",
"family": "claude-opus",
- "created_at": "2025-11-24 00:00:00 +0530",
+ "created_at": "2025-11-24 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 32000,
"knowledge_cutoff": "2025-05-30",
@@ -14605,18 +31211,53 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 5,
"output_per_million": 25,
- "cached_input_per_million": 0.5
+ "cache_read_input_per_million": 0.5,
+ "cache_write_input_per_million": 6.25
}
}
},
"metadata": {
+ "description": "Claude Opus 4.5 is Anthropic’s frontier reasoning model optimized for complex software engineering, agentic workflows, and long-horizon computer use. It offers strong multimodal capabilities, competitive performance across real-world coding and...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "file",
+ "image",
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Claude",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 200000,
+ "max_completion_tokens": 64000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "verbosity"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -14641,10 +31282,10 @@
"name": "Claude Opus 4.6",
"provider": "openrouter",
"family": "claude-opus",
- "created_at": "2026-02-05 00:00:00 +0530",
+ "created_at": "2026-02-05 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 128000,
- "knowledge_cutoff": "2025-05-30",
+ "knowledge_cutoff": "2025-05-31",
"modalities": {
"input": [
"text",
@@ -14659,18 +31300,54 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 5,
"output_per_million": 25,
- "cached_input_per_million": 0.5
+ "cache_read_input_per_million": 0.5,
+ "cache_write_input_per_million": 6.25
}
}
},
"metadata": {
+ "description": "Opus 4.6 is Anthropic’s strongest model for coding and long-running professional tasks. It is built for agents that operate across entire workflows rather than single prompts, making it especially effective...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Claude",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1000000,
+ "max_completion_tokens": 128000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_completion_tokens",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p",
+ "verbosity"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -14693,7 +31370,166 @@
"context": 1000000,
"output": 128000
},
- "knowledge": "2025-05-30"
+ "knowledge": "2025-05-31"
+ }
+ },
+ {
+ "id": "anthropic/claude-opus-4.6-fast",
+ "name": "Anthropic: Claude Opus 4.6 (Fast)",
+ "provider": "openrouter",
+ "family": "anthropic",
+ "created_at": "2026-04-07 20:07:52 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 128000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 30.0,
+ "output_per_million": 150.0,
+ "cache_read_input_per_million": 3.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "Fast-mode variant of [Opus 4.6](/anthropic/claude-opus-4.6) - identical capabilities with higher output speed at premium 6x pricing.\n\nLearn more in Anthropic's docs: https://platform.claude.com/docs/en/build-with-claude/fast-mode",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Claude",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1000000,
+ "max_completion_tokens": 128000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p",
+ "verbosity"
+ ]
+ }
+ },
+ {
+ "id": "anthropic/claude-opus-4.7",
+ "name": "Claude Opus 4.7",
+ "provider": "openrouter",
+ "family": "claude-opus",
+ "created_at": "2026-04-16 00:00:00 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 128000,
+ "knowledge_cutoff": "2026-01-31",
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "pdf"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "reasoning",
+ "vision",
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 5,
+ "output_per_million": 25,
+ "cache_read_input_per_million": 0.5,
+ "cache_write_input_per_million": 6.25
+ }
+ }
+ },
+ "metadata": {
+ "description": "Opus 4.7 is the next generation of Anthropic's Opus family, built for long-running, asynchronous agents. Building on the coding and agentic strengths of Opus 4.6, it delivers stronger performance on...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Claude",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1000000,
+ "max_completion_tokens": 128000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "stop",
+ "structured_outputs",
+ "tool_choice",
+ "tools",
+ "verbosity"
+ ],
+ "source": "models.dev",
+ "provider_id": "openrouter",
+ "open_weights": false,
+ "attachment": true,
+ "temperature": false,
+ "last_updated": "2026-04-16",
+ "cost": {
+ "input": 5,
+ "output": 25,
+ "cache_read": 0.5,
+ "cache_write": 6.25,
+ "context_over_200k": {
+ "input": 10,
+ "output": 37.5,
+ "cache_read": 1,
+ "cache_write": 12.5
+ }
+ },
+ "limit": {
+ "context": 1000000,
+ "output": 128000
+ },
+ "knowledge": "2026-01-31"
}
},
{
@@ -14701,7 +31537,7 @@
"name": "Claude Sonnet 4",
"provider": "openrouter",
"family": "claude-sonnet",
- "created_at": "2025-05-22 00:00:00 +0530",
+ "created_at": "2025-05-22 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-03-31",
@@ -14718,18 +31554,51 @@
"capabilities": [
"function_calling",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
"metadata": {
+ "description": "Claude Sonnet 4 significantly enhances the capabilities of its predecessor, Sonnet 3.7, excelling in both coding and reasoning tasks with improved precision and controllability. Achieving state-of-the-art performance on SWE-bench (72.7%),...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Claude",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1000000,
+ "max_completion_tokens": 64000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -14760,7 +31629,7 @@
"name": "Claude Sonnet 4.5",
"provider": "openrouter",
"family": "claude-sonnet",
- "created_at": "2025-09-29 00:00:00 +0530",
+ "created_at": "2025-09-29 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 64000,
"knowledge_cutoff": "2025-07-31",
@@ -14778,18 +31647,53 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
"metadata": {
+ "description": "Claude Sonnet 4.5 is Anthropic’s most advanced Sonnet model to date, optimized for real-world agents and coding workflows. It delivers state-of-the-art performance on coding benchmarks such as SWE-bench Verified, with...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Claude",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1000000,
+ "max_completion_tokens": 64000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -14820,10 +31724,10 @@
"name": "Claude Sonnet 4.6",
"provider": "openrouter",
"family": "claude-sonnet",
- "created_at": "2026-02-17 00:00:00 +0530",
+ "created_at": "2026-02-17 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 128000,
- "knowledge_cutoff": null,
+ "knowledge_cutoff": "2025-08-31",
"modalities": {
"input": [
"text",
@@ -14837,18 +31741,54 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.3
+ "cache_read_input_per_million": 0.3,
+ "cache_write_input_per_million": 3.75
}
}
},
"metadata": {
+ "description": "Sonnet 4.6 is Anthropic's most capable Sonnet-class model yet, with frontier performance across coding, agents, and professional work. It excels at iterative development, complex codebase navigation, end-to-end project management with...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Claude",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1000000,
+ "max_completion_tokens": 128000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_completion_tokens",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p",
+ "verbosity"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -14870,7 +31810,256 @@
"limit": {
"context": 1000000,
"output": 128000
+ },
+ "knowledge": "2025-08-31"
+ }
+ },
+ {
+ "id": "arcee-ai/coder-large",
+ "name": "Arcee AI: Coder Large",
+ "provider": "openrouter",
+ "family": "arcee-ai",
+ "created_at": "2025-05-05 20:57:43 UTC",
+ "context_window": 32768,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.5,
+ "output_per_million": 0.7999999999999999
+ }
}
+ },
+ "metadata": {
+ "description": "Coder‑Large is a 32 B‑parameter offspring of Qwen 2.5‑Instruct that has been further trained on permissively‑licensed GitHub, CodeSearchNet and synthetic bug‑fix corpora. It supports a 32k context window, enabling multi‑file...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 32768,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "stop",
+ "temperature",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "arcee-ai/maestro-reasoning",
+ "name": "Arcee AI: Maestro Reasoning",
+ "provider": "openrouter",
+ "family": "arcee-ai",
+ "created_at": "2025-05-05 21:41:09 UTC",
+ "context_window": 131072,
+ "max_output_tokens": 32000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.8999999999999999,
+ "output_per_million": 3.3000000000000003
+ }
+ }
+ },
+ "metadata": {
+ "description": "Maestro Reasoning is Arcee's flagship analysis model: a 32 B‑parameter derivative of Qwen 2.5‑32 B tuned with DPO and chain‑of‑thought RL for step‑by‑step logic. Compared to the earlier 7 B...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 32000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "stop",
+ "temperature",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "arcee-ai/spotlight",
+ "name": "Arcee AI: Spotlight",
+ "provider": "openrouter",
+ "family": "arcee-ai",
+ "created_at": "2025-05-05 21:45:52 UTC",
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}
},
{
@@ -14878,7 +32067,7 @@
"name": "Trinity Large Preview",
"provider": "openrouter",
"family": "trinity",
- "created_at": "2026-01-28 00:00:00 +0530",
+ "created_at": "2026-01-28 00:00:00 UTC",
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@@ -14918,7 +32107,7 @@
"name": "Trinity Large Thinking",
"provider": "openrouter",
"family": "trinity",
- "created_at": "2026-04-01 00:00:00 +0530",
+ "created_at": "2026-04-01 00:00:00 UTC",
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@@ -14932,7 +32121,10 @@
},
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- "reasoning"
+ "reasoning",
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+ "structured_output",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -14943,6 +32135,42 @@
}
},
"metadata": {
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"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -14959,12 +32187,563 @@
}
}
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+ "description": "Trinity Mini is a 26B-parameter (3B active) sparse mixture-of-experts language model featuring 128 experts with 8 active per token. Engineered for efficient reasoning over long contexts (131k) with robust function...",
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+ "description": "Virtuoso‑Large is Arcee's top‑tier general‑purpose LLM at 72 B parameters, tuned to tackle cross‑domain reasoning, creative writing and enterprise QA. Unlike many 70 B peers, it retains the 128 k...",
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+ "metadata": {
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+ "architecture": {
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+ "name": "Baidu: ERNIE 4.5 VL 28B A3B",
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+ }
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+ "metadata": {
+ "description": "A powerful multimodal Mixture-of-Experts chat model featuring 28B total parameters with 3B activated per token, delivering exceptional text and vision understanding through its innovative heterogeneous MoE structure with modality-isolated routing....",
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+ "name": "Baidu: ERNIE 4.5 VL 424B A47B ",
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+ }
+ },
+ {
+ "id": "baidu/qianfan-ocr-fast:free",
+ "name": "Baidu: Qianfan-OCR-Fast (free)",
+ "provider": "openrouter",
+ "family": "baidu",
+ "created_at": "2026-04-20 17:51:12 UTC",
+ "context_window": 65536,
+ "max_output_tokens": 28672,
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+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {},
+ "metadata": {
+ "description": "Qianfan-OCR-Fast is a domain-specific multimodal large model purpose-built for OCR. By leveraging specialized OCR training data while preserving versatile multimodal intelligence, it provides a powerful performance upgrade over Qianfan-OCR.",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
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+ }
+ },
{
"id": "black-forest-labs/flux.2-flex",
"name": "FLUX.2 Flex",
"provider": "openrouter",
"family": "flux",
- "created_at": "2025-11-25 00:00:00 +0530",
+ "created_at": "2025-11-25 00:00:00 UTC",
"context_window": 67344,
"max_output_tokens": 67344,
"knowledge_cutoff": null,
@@ -15004,7 +32783,7 @@
"name": "FLUX.2 Klein 4B",
"provider": "openrouter",
"family": "flux",
- "created_at": "2026-01-14 00:00:00 +0530",
+ "created_at": "2026-01-14 00:00:00 UTC",
"context_window": 40960,
"max_output_tokens": 40960,
"knowledge_cutoff": null,
@@ -15044,7 +32823,7 @@
"name": "FLUX.2 Max",
"provider": "openrouter",
"family": "flux",
- "created_at": "2025-12-16 00:00:00 +0530",
+ "created_at": "2025-12-16 00:00:00 UTC",
"context_window": 46864,
"max_output_tokens": 46864,
"knowledge_cutoff": null,
@@ -15084,7 +32863,7 @@
"name": "FLUX.2 Pro",
"provider": "openrouter",
"family": "flux",
- "created_at": "2025-11-25 00:00:00 +0530",
+ "created_at": "2025-11-25 00:00:00 UTC",
"context_window": 46864,
"max_output_tokens": 46864,
"knowledge_cutoff": null,
@@ -15119,12 +32898,284 @@
"knowledge": "2025-06"
}
},
+ {
+ "id": "bytedance-seed/seed-1.6",
+ "name": "ByteDance Seed: Seed 1.6",
+ "provider": "openrouter",
+ "family": "bytedance-seed",
+ "created_at": "2025-12-23 15:49:57 UTC",
+ "context_window": 262144,
+ "max_output_tokens": 32768,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "image",
+ "text",
+ "video"
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+ "output": [
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+ "capabilities": [
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+ "function_calling",
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+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.25,
+ "output_per_million": 2.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "Seed 1.6 is a general-purpose model released by the ByteDance Seed team. It incorporates multimodal capabilities and adaptive deep thinking with a 256K context window.",
+ "architecture": {
+ "modality": "text+image+video->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "video"
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+ "output_modalities": [
+ "text"
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+ "tokenizer": "Other",
+ "instruct_type": null
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+ "top_provider": {
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+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "bytedance-seed/seed-1.6-flash",
+ "name": "ByteDance Seed: Seed 1.6 Flash",
+ "provider": "openrouter",
+ "family": "bytedance-seed",
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+ }
+ },
{
"id": "bytedance-seed/seedream-4.5",
"name": "Seedream 4.5",
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"family": "seed",
- "created_at": "2025-12-23 00:00:00 +0530",
+ "created_at": "2025-12-23 00:00:00 UTC",
"context_window": 4096,
"max_output_tokens": 4096,
"knowledge_cutoff": null,
@@ -15159,12 +33210,77 @@
"knowledge": "2025-06"
}
},
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+ "name": "ByteDance: UI-TARS 7B ",
+ "provider": "openrouter",
+ "family": "bytedance",
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+ "cache_read_input_per_million": 0.09999999999999999
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+ "architecture": {
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+ "input_modalities": [
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+ "top_p"
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+ }
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{
"id": "cognitivecomputations/dolphin-mistral-24b-venice-edition:free",
"name": "Uncensored (free)",
"provider": "openrouter",
"family": "mistral",
- "created_at": "2025-07-09 00:00:00 +0530",
+ "created_at": "2025-07-09 00:00:00 UTC",
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"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -15177,10 +33293,40 @@
]
},
"capabilities": [
- "structured_output"
+ "structured_output",
+ "streaming"
],
"pricing": {},
"metadata": {
+ "description": "Venice Uncensored Dolphin Mistral 24B Venice Edition is a fine-tuned variant of Mistral-Small-24B-Instruct-2501, developed by dphn.ai in collaboration with Venice.ai. This model is designed as an “uncensored” instruct-tuned LLM, preserving...",
+ "architecture": {
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"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -15198,12 +33344,402 @@
"knowledge": "2025-06"
}
},
+ {
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+ "name": "Cohere: Command A",
+ "provider": "openrouter",
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+ "metadata": {
+ "description": "Command A is an open-weights 111B parameter model with a 256k context window focused on delivering great performance across agentic, multilingual, and coding use cases. Compared to other leading proprietary...",
+ "architecture": {
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+ "top_p"
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+ "name": "Cohere: Command R (08-2024)",
+ "provider": "openrouter",
+ "family": "cohere",
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+ "output_per_million": 0.6
+ }
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+ },
+ "metadata": {
+ "description": "command-r-08-2024 is an update of the [Command R](/models/cohere/command-r) with improved performance for multilingual retrieval-augmented generation (RAG) and tool use. More broadly, it is better at math, code and reasoning and...",
+ "architecture": {
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+ "family": "cohere",
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+ "output_per_million": 10.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "command-r-plus-08-2024 is an update of the [Command R+](/models/cohere/command-r-plus) with roughly 50% higher throughput and 25% lower latencies as compared to the previous Command R+ version, while keeping the hardware footprint...",
+ "architecture": {
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+ "provider": "openrouter",
+ "family": "cohere",
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+ }
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+ },
+ "metadata": {
+ "description": "Command R7B (12-2024) is a small, fast update of the Command R+ model, delivered in December 2024. It excels at RAG, tool use, agents, and similar tasks requiring complex reasoning...",
+ "architecture": {
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+ "top_p"
+ ]
+ }
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+ {
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+ "name": "Deep Cogito: Cogito v2.1 671B",
+ "provider": "openrouter",
+ "family": "deepcogito",
+ "created_at": "2025-11-13 22:00:33 UTC",
+ "context_window": 128000,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "text_tokens": {
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+ "output_per_million": 1.25
+ }
+ }
+ },
+ "metadata": {
+ "description": "Cogito v2.1 671B MoE represents one of the strongest open models globally, matching performance of frontier closed and open models. This model is trained using self play with reinforcement learning...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
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+ "output_modalities": [
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+ "response_format",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "deepseek/deepseek-chat",
+ "name": "DeepSeek: DeepSeek V3",
+ "provider": "openrouter",
+ "family": "deepseek",
+ "created_at": "2024-12-26 19:28:40 UTC",
+ "context_window": 163840,
+ "max_output_tokens": 16384,
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+ "input_per_million": 0.32,
+ "output_per_million": 0.8899999999999999
+ }
+ }
+ },
+ "metadata": {
+ "description": "DeepSeek-V3 is the latest model from the DeepSeek team, building upon the instruction following and coding abilities of the previous versions. Pre-trained on nearly 15 trillion tokens, the reported evaluations...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
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+ "tokenizer": "DeepSeek",
+ "instruct_type": null
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+ "is_moderated": false
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+ "supported_parameters": [
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+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
{
"id": "deepseek/deepseek-chat-v3-0324",
"name": "DeepSeek V3 0324",
"provider": "openrouter",
"family": "deepseek",
- "created_at": "2025-03-24 00:00:00 +0530",
+ "created_at": "2025-03-24 00:00:00 UTC",
"context_window": 16384,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -15216,10 +33752,56 @@
]
},
"capabilities": [
- "structured_output"
+ "structured_output",
+ "streaming",
+ "function_calling",
+ "predicted_outputs"
],
- "pricing": {},
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.19999999999999998,
+ "output_per_million": 0.77,
+ "cache_read_input_per_million": 0.135
+ }
+ }
+ },
"metadata": {
+ "description": "DeepSeek V3, a 685B-parameter, mixture-of-experts model, is the latest iteration of the flagship chat model family from the DeepSeek team. It succeeds the [DeepSeek V3](/deepseek/deepseek-chat-v3) model and performs really well...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "DeepSeek",
+ "instruct_type": null
+ },
+ "top_provider": {
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+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -15242,7 +33824,7 @@
"name": "DeepSeek-V3.1",
"provider": "openrouter",
"family": "deepseek",
- "created_at": "2025-08-21 00:00:00 +0530",
+ "created_at": "2025-08-21 00:00:00 UTC",
"context_window": 163840,
"max_output_tokens": 163840,
"knowledge_cutoff": null,
@@ -15257,7 +33839,9 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -15268,6 +33852,45 @@
}
},
"metadata": {
+ "description": "DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "DeepSeek",
+ "instruct_type": "deepseek-v3.1"
+ },
+ "top_provider": {
+ "context_length": 32768,
+ "max_completion_tokens": 7168,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -15290,7 +33913,7 @@
"name": "DeepSeek: R1",
"provider": "openrouter",
"family": "deepseek-thinking",
- "created_at": "2025-01-20 00:00:00 +0530",
+ "created_at": "2025-01-20 00:00:00 UTC",
"context_window": 64000,
"max_output_tokens": 16000,
"knowledge_cutoff": null,
@@ -15304,7 +33927,8 @@
},
"capabilities": [
"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -15315,6 +33939,40 @@
}
},
"metadata": {
+ "description": "DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass....",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "DeepSeek",
+ "instruct_type": "deepseek-r1"
+ },
+ "top_provider": {
+ "context_length": 64000,
+ "max_completion_tokens": 16000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "max_completion_tokens",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "seed",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -15332,12 +33990,84 @@
"knowledge": "2024-07"
}
},
+ {
+ "id": "deepseek/deepseek-r1-0528",
+ "name": "DeepSeek: R1 0528",
+ "provider": "openrouter",
+ "family": "deepseek",
+ "created_at": "2025-05-28 17:59:30 UTC",
+ "context_window": 163840,
+ "max_output_tokens": 32768,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.5,
+ "output_per_million": 2.1500000000000004,
+ "cache_read_input_per_million": 0.35
+ }
+ }
+ },
+ "metadata": {
+ "description": "May 28th update to the [original DeepSeek R1](/deepseek/deepseek-r1) Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "DeepSeek",
+ "instruct_type": "deepseek-r1"
+ },
+ "top_provider": {
+ "context_length": 163840,
+ "max_completion_tokens": 32768,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
{
"id": "deepseek/deepseek-r1-distill-llama-70b",
"name": "DeepSeek R1 Distill Llama 70B",
"provider": "openrouter",
"family": "deepseek-thinking",
- "created_at": "2025-01-23 00:00:00 +0530",
+ "created_at": "2025-01-23 00:00:00 UTC",
"context_window": 8192,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -15351,10 +34081,53 @@
},
"capabilities": [
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
- "pricing": {},
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.7,
+ "output_per_million": 0.7999999999999999
+ }
+ }
+ },
"metadata": {
+ "description": "DeepSeek R1 Distill Llama 70B is a distilled large language model based on [Llama-3.3-70B-Instruct](/meta-llama/llama-3.3-70b-instruct), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). The model combines advanced distillation techniques to achieve high performance across...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Llama3",
+ "instruct_type": "deepseek-r1"
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "temperature",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -15372,12 +34145,78 @@
"knowledge": "2024-10"
}
},
+ {
+ "id": "deepseek/deepseek-r1-distill-qwen-32b",
+ "name": "DeepSeek: R1 Distill Qwen 32B",
+ "provider": "openrouter",
+ "family": "deepseek",
+ "created_at": "2025-01-29 23:53:50 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 32768,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.29,
+ "output_per_million": 0.29
+ }
+ }
+ },
+ "metadata": {
+ "description": "DeepSeek R1 Distill Qwen 32B is a distilled large language model based on [Qwen 2.5 32B](https://huggingface.co/Qwen/Qwen2.5-32B), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). It outperforms OpenAI's o1-mini across various benchmarks, achieving new...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen",
+ "instruct_type": "deepseek-r1"
+ },
+ "top_provider": {
+ "context_length": 32768,
+ "max_completion_tokens": 32768,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logprobs",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
{
"id": "deepseek/deepseek-v3.1-terminus",
"name": "DeepSeek V3.1 Terminus",
"provider": "openrouter",
"family": "deepseek",
- "created_at": "2025-09-22 00:00:00 +0530",
+ "created_at": "2025-09-22 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -15392,7 +34231,9 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -15403,6 +34244,43 @@
}
},
"metadata": {
+ "description": "DeepSeek-V3.1 Terminus is an update to [DeepSeek V3.1](/deepseek/deepseek-chat-v3.1) that maintains the model's original capabilities while addressing issues reported by users, including language consistency and agent capabilities, further optimizing the model's...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "DeepSeek",
+ "instruct_type": "deepseek-v3.1"
+ },
+ "top_provider": {
+ "context_length": 163840,
+ "max_completion_tokens": 32768,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -15425,7 +34303,7 @@
"name": "DeepSeek V3.1 Terminus (exacto)",
"provider": "openrouter",
"family": "deepseek",
- "created_at": "2025-09-22 00:00:00 +0530",
+ "created_at": "2025-09-22 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -15473,7 +34351,7 @@
"name": "DeepSeek V3.2",
"provider": "openrouter",
"family": "deepseek",
- "created_at": "2025-12-01 00:00:00 +0530",
+ "created_at": "2025-12-01 00:00:00 UTC",
"context_window": 163840,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -15488,7 +34366,9 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -15499,6 +34379,43 @@
}
},
"metadata": {
+ "description": "DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "DeepSeek",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -15516,12 +34433,83 @@
"knowledge": "2024-07"
}
},
+ {
+ "id": "deepseek/deepseek-v3.2-exp",
+ "name": "DeepSeek: DeepSeek V3.2 Exp",
+ "provider": "openrouter",
+ "family": "deepseek",
+ "created_at": "2025-09-29 12:54:41 UTC",
+ "context_window": 163840,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.27,
+ "output_per_million": 0.41
+ }
+ }
+ },
+ "metadata": {
+ "description": "DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "DeepSeek",
+ "instruct_type": "deepseek-v3.1"
+ },
+ "top_provider": {
+ "context_length": 163840,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
{
"id": "deepseek/deepseek-v3.2-speciale",
"name": "DeepSeek V3.2 Speciale",
"provider": "openrouter",
"family": "deepseek",
- "created_at": "2025-12-01 00:00:00 +0530",
+ "created_at": "2025-12-01 00:00:00 UTC",
"context_window": 163840,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -15536,7 +34524,9 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -15547,6 +34537,41 @@
}
},
"metadata": {
+ "description": "DeepSeek-V3.2-Speciale is a high-compute variant of DeepSeek-V3.2 optimized for maximum reasoning and agentic performance. It builds on DeepSeek Sparse Attention (DSA) for efficient long-context processing, then scales post-training reinforcement learning...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "DeepSeek",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 163840,
+ "max_completion_tokens": 163840,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -15564,12 +34589,268 @@
"knowledge": "2024-07"
}
},
+ {
+ "id": "deepseek/deepseek-v4-flash",
+ "name": "DeepSeek V4 Flash",
+ "provider": "openrouter",
+ "family": "deepseek-flash",
+ "created_at": "2026-04-24 00:00:00 UTC",
+ "context_window": 1048576,
+ "max_output_tokens": 393216,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.14,
+ "output_per_million": 0.28,
+ "cache_read_input_per_million": 0.028
+ }
+ }
+ },
+ "metadata": {
+ "description": "DeepSeek V4 Flash is an efficiency-optimized Mixture-of-Experts model from DeepSeek with 284B total parameters and 13B activated parameters, supporting a 1M-token context window. It is designed for fast inference and...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "DeepSeek",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1048576,
+ "max_completion_tokens": 384000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ],
+ "source": "models.dev",
+ "provider_id": "openrouter",
+ "open_weights": true,
+ "attachment": false,
+ "temperature": true,
+ "last_updated": "2026-04-24",
+ "interleaved": {
+ "field": "reasoning_content"
+ },
+ "cost": {
+ "input": 0.14,
+ "output": 0.28,
+ "cache_read": 0.028
+ },
+ "limit": {
+ "context": 1048576,
+ "output": 393216
+ },
+ "knowledge": "2025-05"
+ }
+ },
+ {
+ "id": "deepseek/deepseek-v4-pro",
+ "name": "DeepSeek V4 Pro",
+ "provider": "openrouter",
+ "family": "deepseek-thinking",
+ "created_at": "2026-04-24 00:00:00 UTC",
+ "context_window": 1048576,
+ "max_output_tokens": 393216,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 1.74,
+ "output_per_million": 3.48,
+ "cache_read_input_per_million": 0.145
+ }
+ }
+ },
+ "metadata": {
+ "description": "DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding,...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "DeepSeek",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1048576,
+ "max_completion_tokens": 384000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ],
+ "source": "models.dev",
+ "provider_id": "openrouter",
+ "open_weights": true,
+ "attachment": false,
+ "temperature": true,
+ "last_updated": "2026-04-24",
+ "interleaved": {
+ "field": "reasoning_content"
+ },
+ "cost": {
+ "input": 1.74,
+ "output": 3.48,
+ "cache_read": 0.145
+ },
+ "limit": {
+ "context": 1048576,
+ "output": 393216
+ },
+ "knowledge": "2025-05"
+ }
+ },
+ {
+ "id": "essentialai/rnj-1-instruct",
+ "name": "EssentialAI: Rnj 1 Instruct",
+ "provider": "openrouter",
+ "family": "essentialai",
+ "created_at": "2025-12-07 08:07:27 UTC",
+ "context_window": 32768,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.15,
+ "output_per_million": 0.15
+ }
+ }
+ },
+ "metadata": {
+ "description": "Rnj-1 is an 8B-parameter, dense, open-weight model family developed by Essential AI and trained from scratch with a focus on programming, math, and scientific reasoning. The model demonstrates strong performance...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 32768,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
{
"id": "google/gemini-2.0-flash-001",
"name": "Gemini 2.0 Flash",
"provider": "openrouter",
"family": "gemini-flash",
- "created_at": "2024-12-11 00:00:00 +0530",
+ "created_at": "2024-12-11 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -15588,18 +34869,52 @@
"capabilities": [
"function_calling",
"structured_output",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.1,
"output_per_million": 0.4,
- "cached_input_per_million": 0.025
+ "cache_read_input_per_million": 0.025
}
}
},
"metadata": {
+ "description": "Gemini Flash 2.0 offers a significantly faster time to first token (TTFT) compared to [Gemini Flash 1.5](/google/gemini-flash-1.5), while maintaining quality on par with larger models like [Gemini Pro 1.5](/google/gemini-pro-1.5). It...",
+ "architecture": {
+ "modality": "text+image+file+audio+video->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file",
+ "audio",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1048576,
+ "max_completion_tokens": 8192,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -15618,12 +34933,83 @@
"knowledge": "2024-06"
}
},
+ {
+ "id": "google/gemini-2.0-flash-lite-001",
+ "name": "Google: Gemini 2.0 Flash Lite",
+ "provider": "openrouter",
+ "family": "google",
+ "created_at": "2025-02-25 17:56:52 UTC",
+ "context_window": 1048576,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "file",
+ "audio",
+ "video"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.3,
+ "reasoning_output_per_million": 0.3
+ }
+ }
+ },
+ "metadata": {
+ "description": "Gemini 2.0 Flash Lite offers a significantly faster time to first token (TTFT) compared to [Gemini Flash 1.5](/google/gemini-flash-1.5), while maintaining quality on par with larger models like [Gemini Pro 1.5](/google/gemini-pro-1.5),...",
+ "architecture": {
+ "modality": "text+image+file+audio+video->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file",
+ "audio",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1048576,
+ "max_completion_tokens": 8192,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
{
"id": "google/gemini-2.5-flash",
"name": "Gemini 2.5 Flash",
"provider": "openrouter",
"family": "gemini-flash",
- "created_at": "2025-07-17 00:00:00 +0530",
+ "created_at": "2025-07-17 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -15643,18 +35029,54 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.3,
"output_per_million": 2.5,
- "cached_input_per_million": 0.0375
+ "cache_read_input_per_million": 0.0375
}
}
},
"metadata": {
+ "description": "Gemini 2.5 Flash is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in \"thinking\" capabilities, enabling it to provide responses with greater...",
+ "architecture": {
+ "modality": "text+image+file+audio+video->text",
+ "input_modalities": [
+ "file",
+ "image",
+ "text",
+ "audio",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1048576,
+ "max_completion_tokens": 65535,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -15673,12 +35095,77 @@
"knowledge": "2025-01"
}
},
+ {
+ "id": "google/gemini-2.5-flash-image",
+ "name": "Google: Nano Banana (Gemini 2.5 Flash Image)",
+ "provider": "openrouter",
+ "family": "google",
+ "created_at": "2025-10-07 20:53:51 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 32768,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "image",
+ "text"
+ ],
+ "output": [
+ "image",
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.3,
+ "output_per_million": 2.5,
+ "cache_read_input_per_million": 0.03,
+ "reasoning_output_per_million": 2.5
+ }
+ }
+ },
+ "metadata": {
+ "description": "Gemini 2.5 Flash Image, a.k.a. \"Nano Banana,\" is now generally available. It is a state of the art image generation model with contextual understanding. It is capable of image generation,...",
+ "architecture": {
+ "modality": "text+image->text+image",
+ "input_modalities": [
+ "image",
+ "text"
+ ],
+ "output_modalities": [
+ "image",
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 32768,
+ "max_completion_tokens": 32768,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "top_p"
+ ]
+ }
+ },
{
"id": "google/gemini-2.5-flash-lite",
"name": "Gemini 2.5 Flash Lite",
"provider": "openrouter",
"family": "gemini-flash-lite",
- "created_at": "2025-06-17 00:00:00 +0530",
+ "created_at": "2025-06-17 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -15698,18 +35185,54 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.1,
"output_per_million": 0.4,
- "cached_input_per_million": 0.025
+ "cache_read_input_per_million": 0.025
}
}
},
"metadata": {
+ "description": "Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance...",
+ "architecture": {
+ "modality": "text+image+file+audio+video->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file",
+ "audio",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1048576,
+ "max_completion_tokens": 65535,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -15733,7 +35256,7 @@
"name": "Gemini 2.5 Flash Lite Preview 09-25",
"provider": "openrouter",
"family": "gemini-flash-lite",
- "created_at": "2025-09-25 00:00:00 +0530",
+ "created_at": "2025-09-25 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -15753,18 +35276,54 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.1,
"output_per_million": 0.4,
- "cached_input_per_million": 0.025
+ "cache_read_input_per_million": 0.025
}
}
},
"metadata": {
+ "description": "Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance...",
+ "architecture": {
+ "modality": "text+image+file+audio+video->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file",
+ "audio",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1048576,
+ "max_completion_tokens": 65535,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -15788,7 +35347,7 @@
"name": "Gemini 2.5 Flash Preview 09-25",
"provider": "openrouter",
"family": "gemini-flash",
- "created_at": "2025-09-25 00:00:00 +0530",
+ "created_at": "2025-09-25 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -15815,7 +35374,7 @@
"standard": {
"input_per_million": 0.3,
"output_per_million": 2.5,
- "cached_input_per_million": 0.031
+ "cache_read_input_per_million": 0.031
}
}
},
@@ -15843,7 +35402,7 @@
"name": "Gemini 2.5 Pro",
"provider": "openrouter",
"family": "gemini-pro",
- "created_at": "2025-03-20 00:00:00 +0530",
+ "created_at": "2025-03-20 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -15863,18 +35422,54 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 1.25,
"output_per_million": 10,
- "cached_input_per_million": 0.31
+ "cache_read_input_per_million": 0.125
}
}
},
"metadata": {
+ "description": "Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy...",
+ "architecture": {
+ "modality": "text+image+file+audio+video->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file",
+ "audio",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1048576,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -15884,7 +35479,12 @@
"cost": {
"input": 1.25,
"output": 10,
- "cache_read": 0.31
+ "cache_read": 0.125,
+ "context_over_200k": {
+ "input": 2.5,
+ "output": 15,
+ "cache_read": 0.25
+ }
},
"limit": {
"context": 1048576,
@@ -15893,12 +35493,84 @@
"knowledge": "2025-01"
}
},
+ {
+ "id": "google/gemini-2.5-pro-preview",
+ "name": "Google: Gemini 2.5 Pro Preview 06-05",
+ "provider": "openrouter",
+ "family": "google",
+ "created_at": "2025-06-05 15:27:37 UTC",
+ "context_window": 1048576,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "file",
+ "image",
+ "text",
+ "audio"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 1.25,
+ "output_per_million": 10.0,
+ "cache_read_input_per_million": 0.125,
+ "reasoning_output_per_million": 10.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy...",
+ "architecture": {
+ "modality": "text+image+file+audio->text",
+ "input_modalities": [
+ "file",
+ "image",
+ "text",
+ "audio"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1048576,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
{
"id": "google/gemini-2.5-pro-preview-05-06",
"name": "Gemini 2.5 Pro Preview 05-06",
"provider": "openrouter",
"family": "gemini-pro",
- "created_at": "2025-05-06 00:00:00 +0530",
+ "created_at": "2025-05-06 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -15918,18 +35590,54 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 1.25,
"output_per_million": 10,
- "cached_input_per_million": 0.31
+ "cache_read_input_per_million": 0.31
}
}
},
"metadata": {
+ "description": "Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy...",
+ "architecture": {
+ "modality": "text+image+file+audio+video->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file",
+ "audio",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1048576,
+ "max_completion_tokens": 65535,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -15953,7 +35661,7 @@
"name": "Gemini 2.5 Pro Preview 06-05",
"provider": "openrouter",
"family": "gemini-pro",
- "created_at": "2025-06-05 00:00:00 +0530",
+ "created_at": "2025-06-05 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -15980,7 +35688,7 @@
"standard": {
"input_per_million": 1.25,
"output_per_million": 10,
- "cached_input_per_million": 0.31
+ "cache_read_input_per_million": 0.31
}
}
},
@@ -16008,7 +35716,7 @@
"name": "Gemini 3 Flash Preview",
"provider": "openrouter",
"family": "gemini-flash",
- "created_at": "2025-12-17 00:00:00 +0530",
+ "created_at": "2025-12-17 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -16028,18 +35736,54 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.5,
"output_per_million": 3,
- "cached_input_per_million": 0.05
+ "cache_read_input_per_million": 0.05
}
}
},
"metadata": {
+ "description": "Gemini 3 Flash Preview is a high speed, high value thinking model designed for agentic workflows, multi turn chat, and coding assistance. It delivers near Pro level reasoning and tool...",
+ "architecture": {
+ "modality": "text+image+file+audio+video->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file",
+ "audio",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1048576,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -16061,12 +35805,79 @@
"knowledge": "2025-01"
}
},
+ {
+ "id": "google/gemini-3-pro-image-preview",
+ "name": "Google: Nano Banana Pro (Gemini 3 Pro Image Preview)",
+ "provider": "openrouter",
+ "family": "google",
+ "created_at": "2025-11-20 15:49:57 UTC",
+ "context_window": 65536,
+ "max_output_tokens": 32768,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "image",
+ "text"
+ ],
+ "output": [
+ "image",
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 2.0,
+ "output_per_million": 12.0,
+ "cache_read_input_per_million": 0.19999999999999998,
+ "reasoning_output_per_million": 12.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "Nano Banana Pro is Google’s most advanced image-generation and editing model, built on Gemini 3 Pro. It extends the original Nano Banana with significantly improved multimodal reasoning, real-world grounding, and...",
+ "architecture": {
+ "modality": "text+image->text+image",
+ "input_modalities": [
+ "image",
+ "text"
+ ],
+ "output_modalities": [
+ "image",
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 65536,
+ "max_completion_tokens": 32768,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "top_p"
+ ]
+ }
+ },
{
"id": "google/gemini-3-pro-preview",
"name": "Gemini 3 Pro Preview",
"provider": "openrouter",
"family": "gemini-pro",
- "created_at": "2025-11-18 00:00:00 +0530",
+ "created_at": "2025-11-18 00:00:00 UTC",
"context_window": 1050000,
"max_output_tokens": 66000,
"knowledge_cutoff": null,
@@ -16117,12 +35928,94 @@
"knowledge": "2025-01"
}
},
+ {
+ "id": "google/gemini-3.1-flash-image-preview",
+ "name": "Gemini 3.1 Flash Image Preview (Nano Banana 2)",
+ "provider": "openrouter",
+ "family": "gemini-flash",
+ "created_at": "2026-02-26 00:00:00 UTC",
+ "context_window": 65536,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "text",
+ "image"
+ ]
+ },
+ "capabilities": [
+ "structured_output",
+ "reasoning",
+ "vision",
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.5,
+ "output_per_million": 3
+ }
+ }
+ },
+ "metadata": {
+ "description": "Gemini 3.1 Flash Image Preview, a.k.a. \"Nano Banana 2,\" is Google’s latest state of the art image generation and editing model, delivering Pro-level visual quality at Flash speed. It combines...",
+ "architecture": {
+ "modality": "text+image->text+image",
+ "input_modalities": [
+ "image",
+ "text"
+ ],
+ "output_modalities": [
+ "image",
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 65536,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "top_p"
+ ],
+ "source": "models.dev",
+ "provider_id": "openrouter",
+ "open_weights": false,
+ "attachment": true,
+ "temperature": true,
+ "last_updated": "2026-02-26",
+ "cost": {
+ "input": 0.5,
+ "output": 3
+ },
+ "limit": {
+ "context": 65536,
+ "output": 65536
+ },
+ "knowledge": "2025-01"
+ }
+ },
{
"id": "google/gemini-3.1-flash-lite-preview",
"name": "Gemini 3.1 Flash Lite Preview",
"provider": "openrouter",
"family": "gemini-flash-lite",
- "created_at": "2026-03-03 00:00:00 +0530",
+ "created_at": "2026-03-03 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -16142,14 +36035,16 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.25,
"output_per_million": 1.5,
- "cached_input_per_million": 0.025,
+ "cache_read_input_per_million": 0.025,
+ "cache_write_input_per_million": 0.083,
"reasoning_output_per_million": 1.5
}
},
@@ -16161,6 +36056,41 @@
}
},
"metadata": {
+ "description": "Gemini 3.1 Flash Lite Preview is Google's high-efficiency model optimized for high-volume use cases. It outperforms Gemini 2.5 Flash Lite on overall quality and approaches Gemini 2.5 Flash performance across...",
+ "architecture": {
+ "modality": "text+image+file+audio+video->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "video",
+ "file",
+ "audio"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1048576,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -16187,7 +36117,7 @@
"name": "Gemini 3.1 Pro Preview",
"provider": "openrouter",
"family": "gemini-pro",
- "created_at": "2026-02-19 00:00:00 +0530",
+ "created_at": "2026-02-19 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -16207,7 +36137,8 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -16219,6 +36150,41 @@
}
},
"metadata": {
+ "description": "Gemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Building on the multimodal foundation...",
+ "architecture": {
+ "modality": "text+image+file+audio+video->text",
+ "input_modalities": [
+ "audio",
+ "file",
+ "image",
+ "text",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1048576,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -16250,7 +36216,7 @@
"name": "Gemini 3.1 Pro Preview Custom Tools",
"provider": "openrouter",
"family": "gemini-pro",
- "created_at": "2026-02-19 00:00:00 +0530",
+ "created_at": "2026-02-19 00:00:00 UTC",
"context_window": 1048576,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -16270,7 +36236,8 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -16282,6 +36249,41 @@
}
},
"metadata": {
+ "description": "Gemini 3.1 Pro Preview Custom Tools is a variant of Gemini 3.1 Pro that improves tool selection behavior by preventing overuse of a general bash tool when more efficient third-party...",
+ "architecture": {
+ "modality": "text+image+file+audio+video->text",
+ "input_modalities": [
+ "text",
+ "audio",
+ "image",
+ "video",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1048576,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -16308,12 +36310,74 @@
"knowledge": "2025-01"
}
},
+ {
+ "id": "google/gemma-2-27b-it",
+ "name": "Google: Gemma 2 27B",
+ "provider": "openrouter",
+ "family": "google",
+ "created_at": "2024-07-13 00:00:00 UTC",
+ "context_window": 8192,
+ "max_output_tokens": 2048,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.65,
+ "output_per_million": 0.65
+ }
+ }
+ },
+ "metadata": {
+ "description": "Gemma 2 27B by Google is an open model built from the same research and technology used to create the [Gemini models](/models?q=gemini). Gemma models are well-suited for a variety of...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": "gemma"
+ },
+ "top_provider": {
+ "context_length": 8192,
+ "max_completion_tokens": 2048,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "top_p"
+ ]
+ }
+ },
{
"id": "google/gemma-2-9b-it",
"name": "Gemma 2 9B",
"provider": "openrouter",
"family": "gemma",
- "created_at": "2024-06-28 00:00:00 +0530",
+ "created_at": "2024-06-28 00:00:00 UTC",
"context_window": 8192,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -16357,7 +36421,7 @@
"name": "Gemma 3 12B",
"provider": "openrouter",
"family": "gemma",
- "created_at": "2025-03-13 00:00:00 +0530",
+ "created_at": "2025-03-13 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -16372,7 +36436,10 @@
},
"capabilities": [
"structured_output",
- "vision"
+ "vision",
+ "streaming",
+ "function_calling",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -16383,6 +36450,42 @@
}
},
"metadata": {
+ "description": "Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities,...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": "gemma"
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -16405,7 +36508,7 @@
"name": "Gemma 3 12B (free)",
"provider": "openrouter",
"family": "gemma",
- "created_at": "2025-03-13 00:00:00 +0530",
+ "created_at": "2025-03-13 00:00:00 UTC",
"context_window": 32768,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -16445,7 +36548,7 @@
"name": "Gemma 3 27B",
"provider": "openrouter",
"family": "gemma",
- "created_at": "2025-03-12 00:00:00 +0530",
+ "created_at": "2025-03-12 00:00:00 UTC",
"context_window": 96000,
"max_output_tokens": 96000,
"knowledge_cutoff": null,
@@ -16461,7 +36564,9 @@
"capabilities": [
"function_calling",
"structured_output",
- "vision"
+ "vision",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -16472,6 +36577,42 @@
}
},
"metadata": {
+ "description": "Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities,...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": "gemma"
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -16494,7 +36635,7 @@
"name": "Gemma 3 27B (free)",
"provider": "openrouter",
"family": "gemma",
- "created_at": "2025-03-12 00:00:00 +0530",
+ "created_at": "2025-03-12 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -16535,7 +36676,7 @@
"name": "Gemma 3 4B",
"provider": "openrouter",
"family": "gemma",
- "created_at": "2025-03-13 00:00:00 +0530",
+ "created_at": "2025-03-13 00:00:00 UTC",
"context_window": 96000,
"max_output_tokens": 96000,
"knowledge_cutoff": null,
@@ -16549,7 +36690,10 @@
]
},
"capabilities": [
- "vision"
+ "vision",
+ "streaming",
+ "structured_output",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -16560,6 +36704,40 @@
}
},
"metadata": {
+ "description": "Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities,...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemini",
+ "instruct_type": "gemma"
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -16582,7 +36760,7 @@
"name": "Gemma 3 4B (free)",
"provider": "openrouter",
"family": "gemma",
- "created_at": "2025-03-13 00:00:00 +0530",
+ "created_at": "2025-03-13 00:00:00 UTC",
"context_window": 32768,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -16622,7 +36800,7 @@
"name": "Gemma 3n 2B (free)",
"provider": "openrouter",
"family": "gemma",
- "created_at": "2025-07-09 00:00:00 +0530",
+ "created_at": "2025-07-09 00:00:00 UTC",
"context_window": 8192,
"max_output_tokens": 2000,
"knowledge_cutoff": null,
@@ -16659,7 +36837,7 @@
"name": "Gemma 3n 4B",
"provider": "openrouter",
"family": "gemma",
- "created_at": "2025-05-20 00:00:00 +0530",
+ "created_at": "2025-05-20 00:00:00 UTC",
"context_window": 32768,
"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -16671,7 +36849,10 @@
"text"
]
},
- "capabilities": [],
+ "capabilities": [
+ "streaming",
+ "predicted_outputs"
+ ],
"pricing": {
"text_tokens": {
"standard": {
@@ -16681,6 +36862,36 @@
}
},
"metadata": {
+ "description": "Gemma 3n E4B-it is optimized for efficient execution on mobile and low-resource devices, such as phones, laptops, and tablets. It supports multimodal inputs—including text, visual data, and audio—enabling diverse tasks...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 32768,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "stop",
+ "temperature",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -16703,7 +36914,7 @@
"name": "Gemma 3n 4B (free)",
"provider": "openrouter",
"family": "gemma",
- "created_at": "2025-05-20 00:00:00 +0530",
+ "created_at": "2025-05-20 00:00:00 UTC",
"context_window": 8192,
"max_output_tokens": 2000,
"knowledge_cutoff": null,
@@ -16740,7 +36951,7 @@
"name": "Gemma 4 26B A4B",
"provider": "openrouter",
"family": "gemma",
- "created_at": "2026-04-03 00:00:00 +0530",
+ "created_at": "2026-04-03 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 262144,
"knowledge_cutoff": null,
@@ -16758,7 +36969,9 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -16769,6 +36982,47 @@
}
},
"metadata": {
+ "description": "Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...",
+ "architecture": {
+ "modality": "text+image+video->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemma",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -16791,7 +37045,7 @@
"name": "Gemma 4 26B A4B (free)",
"provider": "openrouter",
"family": "gemma",
- "created_at": "2026-04-03 00:00:00 +0530",
+ "created_at": "2026-04-03 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -16809,10 +37063,42 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {},
"metadata": {
+ "description": "Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...",
+ "architecture": {
+ "modality": "text+image+video->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemma",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": 32768,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -16835,7 +37121,7 @@
"name": "Gemma 4 31B",
"provider": "openrouter",
"family": "gemma",
- "created_at": "2026-04-02 00:00:00 +0530",
+ "created_at": "2026-04-02 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 262144,
"knowledge_cutoff": null,
@@ -16853,7 +37139,9 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -16864,6 +37152,47 @@
}
},
"metadata": {
+ "description": "Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...",
+ "architecture": {
+ "modality": "text+image+video->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemma",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -16886,7 +37215,7 @@
"name": "Gemma 4 31B (free)",
"provider": "openrouter",
"family": "gemma",
- "created_at": "2026-04-02 00:00:00 +0530",
+ "created_at": "2026-04-02 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -16904,10 +37233,42 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {},
"metadata": {
+ "description": "Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...",
+ "architecture": {
+ "modality": "text+image+video->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Gemma",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": 32768,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -16925,12 +37286,315 @@
"knowledge": "2025-01"
}
},
+ {
+ "id": "google/lyria-3-clip-preview",
+ "name": "Google: Lyria 3 Clip Preview",
+ "provider": "openrouter",
+ "family": "google",
+ "created_at": "2026-03-30 21:47:35 UTC",
+ "context_window": 1048576,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "text",
+ "audio"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "structured_output"
+ ],
+ "pricing": {},
+ "metadata": {
+ "description": "30 second duration clips are priced at $0.04 per clip. Lyria 3 is Google's family of music generation models, available through the Gemini API. With Lyria 3, you can generate...",
+ "architecture": {
+ "modality": "text+image->text+audio",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text",
+ "audio"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1048576,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
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+ "name": "Google: Lyria 3 Pro Preview",
+ "provider": "openrouter",
+ "family": "google",
+ "created_at": "2026-03-30 21:48:06 UTC",
+ "context_window": 1048576,
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+ },
+ "capabilities": [
+ "streaming",
+ "structured_output"
+ ],
+ "pricing": {},
+ "metadata": {
+ "description": "Full-length songs are priced at $0.08 per song. Lyria 3 is Google's family of music generation models, available through the Gemini API. With Lyria 3, you can generate high-quality, 48kHz...",
+ "architecture": {
+ "modality": "text+image->text+audio",
+ "input_modalities": [
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+ "image"
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+ {
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+ "name": "MythoMax 13B",
+ "provider": "openrouter",
+ "family": "gryphe",
+ "created_at": "2023-07-02 00:00:00 UTC",
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+ "max_output_tokens": 4096,
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+ }
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+ "metadata": {
+ "description": "One of the highest performing and most popular fine-tunes of Llama 2 13B, with rich descriptions and roleplay. #merge",
+ "architecture": {
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+ "input_modalities": [
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+ "temperature",
+ "top_a",
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+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "ibm-granite/granite-4.0-h-micro",
+ "name": "IBM: Granite 4.0 Micro",
+ "provider": "openrouter",
+ "family": "ibm-granite",
+ "created_at": "2025-10-20 02:34:55 UTC",
+ "context_window": 131000,
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+ "input_per_million": 0.017,
+ "output_per_million": 0.11
+ }
+ }
+ },
+ "metadata": {
+ "description": "Granite-4.0-H-Micro is a 3B parameter from the Granite 4 family of models. These models are the latest in a series of models released by IBM. They are fine-tuned for long...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
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+ "output_modalities": [
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+ "tokenizer": "Other",
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+ "supported_parameters": [
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+ "max_tokens",
+ "presence_penalty",
+ "repetition_penalty",
+ "seed",
+ "temperature",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "ibm-granite/granite-4.1-8b",
+ "name": "IBM: Granite 4.1 8B",
+ "provider": "openrouter",
+ "family": "ibm-granite",
+ "created_at": "2026-04-30 19:24:31 UTC",
+ "context_window": 131072,
+ "max_output_tokens": 131072,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "pricing": {
+ "text_tokens": {
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+ "output_per_million": 0.09999999999999999,
+ "cache_read_input_per_million": 0.049999999999999996
+ }
+ }
+ },
+ "metadata": {
+ "description": "Granite 4.1 8B is a dense, decoder-only 8-billion-parameter language model from IBM, part of the Granite 4.1 family. It supports a 131K-token context window and is designed for enterprise tasks...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 131072,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
{
"id": "inception/mercury-2",
"name": "Mercury 2",
"provider": "openrouter",
"family": "mercury",
- "created_at": "2026-03-04 00:00:00 +0530",
+ "created_at": "2026-03-04 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 50000,
"knowledge_cutoff": null,
@@ -16945,18 +37609,48 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.25,
"output_per_million": 0.75,
- "cached_input_per_million": 0.025
+ "cache_read_input_per_million": 0.025
}
}
},
"metadata": {
+ "description": "Mercury 2 is an extremely fast reasoning LLM, and the first reasoning diffusion LLM (dLLM). Instead of generating tokens sequentially, Mercury 2 produces and refines multiple tokens in parallel, achieving...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 50000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -16979,7 +37673,7 @@
"name": "Mercury Edit 2",
"provider": "openrouter",
"family": null,
- "created_at": "2026-03-30 00:00:00 +0530",
+ "created_at": "2026-03-30 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -16999,7 +37693,7 @@
"standard": {
"input_per_million": 0.25,
"output_per_million": 0.75,
- "cached_input_per_million": 0.025
+ "cache_read_input_per_million": 0.025
}
}
},
@@ -17021,12 +37715,380 @@
}
}
},
+ {
+ "id": "inclusionai/ling-2.6-1t:free",
+ "name": "inclusionAI: Ling-2.6-1T (free)",
+ "provider": "openrouter",
+ "family": "inclusionai",
+ "created_at": "2026-04-23 12:43:58 UTC",
+ "context_window": 262144,
+ "max_output_tokens": 32768,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "output": [
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+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {},
+ "metadata": {
+ "description": "Ling-2.6-1T is an instant (instruct) model from inclusionAI and the company’s trillion-parameter flagship, designed for real-world agents that require fast execution and high efficiency at scale. It uses a “fast...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
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+ "supported_parameters": [
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+ "max_tokens",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "inclusionai/ling-2.6-flash",
+ "name": "inclusionAI: Ling-2.6-flash",
+ "provider": "openrouter",
+ "family": "inclusionai",
+ "created_at": "2026-04-21 18:24:46 UTC",
+ "context_window": 262144,
+ "max_output_tokens": 32768,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "output": [
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+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
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+ "pricing": {
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+ "output_per_million": 0.24,
+ "cache_read_input_per_million": 0.016
+ }
+ }
+ },
+ "metadata": {
+ "description": "Ling-2.6-flash is an instant (instruct) model from inclusionAI with 104B total parameters and 7.4B active parameters, designed for real-world agents that require fast responses, strong execution, and high token efficiency....",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
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+ "output_modalities": [
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+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
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+ "max_tokens",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "inflection/inflection-3-pi",
+ "name": "Inflection: Inflection 3 Pi",
+ "provider": "openrouter",
+ "family": "inflection",
+ "created_at": "2024-10-11 00:00:00 UTC",
+ "context_window": 8000,
+ "max_output_tokens": 1024,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 2.5,
+ "output_per_million": 10.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "Inflection 3 Pi powers Inflection's [Pi](https://pi.ai) chatbot, including backstory, emotional intelligence, productivity, and safety. It has access to recent news, and excels in scenarios like customer support and roleplay. Pi...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
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+ "output_modalities": [
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+ "supported_parameters": [
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+ "stop",
+ "temperature",
+ "top_p"
+ ]
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+ {
+ "id": "inflection/inflection-3-productivity",
+ "name": "Inflection: Inflection 3 Productivity",
+ "provider": "openrouter",
+ "family": "inflection",
+ "created_at": "2024-10-11 00:00:00 UTC",
+ "context_window": 8000,
+ "max_output_tokens": 1024,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "capabilities": [
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+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 2.5,
+ "output_per_million": 10.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "Inflection 3 Productivity is optimized for following instructions. It is better for tasks requiring JSON output or precise adherence to provided guidelines. It has access to recent news. For emotional...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
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+ "max_completion_tokens": 1024,
+ "is_moderated": false
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+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "stop",
+ "temperature",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "kwaipilot/kat-coder-pro-v2",
+ "name": "Kwaipilot: KAT-Coder-Pro V2",
+ "provider": "openrouter",
+ "family": "kwaipilot",
+ "created_at": "2026-03-27 22:08:30 UTC",
+ "context_window": 256000,
+ "max_output_tokens": 80000,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "output": [
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+ "capabilities": [
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+ "function_calling",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.3,
+ "output_per_million": 1.2,
+ "cache_read_input_per_million": 0.06
+ }
+ }
+ },
+ "metadata": {
+ "description": "KAT-Coder-Pro V2 is the latest high-performance model in KwaiKAT’s KAT-Coder series, designed for complex enterprise-grade software engineering and SaaS integration. It builds on the agentic coding strengths of earlier versions,...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 256000,
+ "max_completion_tokens": 80000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "liquid/lfm-2-24b-a2b",
+ "name": "LiquidAI: LFM2-24B-A2B",
+ "provider": "openrouter",
+ "family": "liquid",
+ "created_at": "2026-02-25 19:45:11 UTC",
+ "context_window": 32768,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "output": [
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+ },
+ "capabilities": [
+ "streaming",
+ "predicted_outputs"
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+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.03,
+ "output_per_million": 0.12
+ }
+ }
+ },
+ "metadata": {
+ "description": "LFM2-24B-A2B is the largest model in the LFM2 family of hybrid architectures designed for efficient on-device deployment. Built as a 24B parameter Mixture-of-Experts model with only 2B active parameters per...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 32768,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "stop",
+ "temperature",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
{
"id": "liquid/lfm-2.5-1.2b-instruct:free",
"name": "LFM2.5-1.2B-Instruct (free)",
"provider": "openrouter",
"family": "liquid",
- "created_at": "2026-01-20 00:00:00 +0530",
+ "created_at": "2026-01-20 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -17038,9 +38100,41 @@
"text"
]
},
- "capabilities": [],
+ "capabilities": [
+ "streaming"
+ ],
"pricing": {},
"metadata": {
+ "description": "LFM2.5-1.2B-Instruct is a compact, high-performance instruction-tuned model built for fast on-device AI. It delivers strong chat quality in a 1.2B parameter footprint, with efficient edge inference and broad runtime support.",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 32768,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "seed",
+ "stop",
+ "temperature",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -17063,7 +38157,7 @@
"name": "LFM2.5-1.2B-Thinking (free)",
"provider": "openrouter",
"family": "liquid",
- "created_at": "2026-01-20 00:00:00 +0530",
+ "created_at": "2026-01-20 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -17076,10 +38170,43 @@
]
},
"capabilities": [
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {},
"metadata": {
+ "description": "LFM2.5-1.2B-Thinking is a lightweight reasoning-focused model optimized for agentic tasks, data extraction, and RAG—while still running comfortably on edge devices. It supports long context (up to 32K tokens) and is...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 32768,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "seed",
+ "stop",
+ "temperature",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -17097,12 +38224,348 @@
"knowledge": "2025-06"
}
},
+ {
+ "id": "mancer/weaver",
+ "name": "Mancer: Weaver (alpha)",
+ "provider": "openrouter",
+ "family": "mancer",
+ "created_at": "2023-08-02 00:00:00 UTC",
+ "context_window": 8000,
+ "max_output_tokens": 2000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.75,
+ "output_per_million": 1.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "An attempt to recreate Claude-style verbosity, but don't expect the same level of coherence or memory. Meant for use in roleplay/narrative situations.",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Llama2",
+ "instruct_type": "alpaca"
+ },
+ "top_provider": {
+ "context_length": 8000,
+ "max_completion_tokens": 2000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "temperature",
+ "top_a",
+ "top_k",
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+ "architecture": {
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+ "top_k",
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+ "top_p"
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{
"id": "meta-llama/llama-3.2-11b-vision-instruct",
"name": "Llama 3.2 11B Vision Instruct",
"provider": "openrouter",
"family": "llama",
- "created_at": "2024-09-25 00:00:00 +0530",
+ "created_at": "2024-09-25 00:00:00 UTC",
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"knowledge_cutoff": null,
@@ -17116,10 +38579,53 @@
]
},
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- "vision"
+ "vision",
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+ "structured_output",
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],
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+ "output_per_million": 0.245
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+ "architecture": {
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+ "input_modalities": [
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+ "image"
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+ "temperature",
+ "top_k",
+ "top_p"
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"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -17137,12 +38643,130 @@
"knowledge": "2023-12"
}
},
+ {
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+ "name": "Meta: Llama 3.2 1B Instruct",
+ "provider": "openrouter",
+ "family": "meta-llama",
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+ "architecture": {
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+ "id": "meta-llama/llama-3.2-3b-instruct",
+ "name": "Meta: Llama 3.2 3B Instruct",
+ "provider": "openrouter",
+ "family": "meta-llama",
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+ "metadata": {
+ "description": "Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it...",
+ "architecture": {
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{
"id": "meta-llama/llama-3.2-3b-instruct:free",
"name": "Llama 3.2 3B Instruct (free)",
"provider": "openrouter",
"family": "llama",
- "created_at": "2024-09-25 00:00:00 +0530",
+ "created_at": "2024-09-25 00:00:00 UTC",
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@@ -17156,10 +38780,38 @@
]
},
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- "vision"
+ "vision",
+ "streaming"
],
"pricing": {},
"metadata": {
+ "description": "Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it...",
+ "architecture": {
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+ "stop",
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+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -17177,12 +38829,81 @@
"knowledge": "2023-12"
}
},
+ {
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+ "name": "Meta: Llama 3.3 70B Instruct",
+ "provider": "openrouter",
+ "family": "meta-llama",
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+ "output_per_million": 0.32
+ }
+ }
+ },
+ "metadata": {
+ "description": "The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
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+ "temperature",
+ "tool_choice",
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+ "top_k",
+ "top_p"
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+ }
+ },
{
"id": "meta-llama/llama-3.3-70b-instruct:free",
"name": "Llama 3.3 70B Instruct (free)",
"provider": "openrouter",
"family": "llama",
- "created_at": "2024-12-06 00:00:00 +0530",
+ "created_at": "2024-12-06 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -17196,10 +38917,40 @@
},
"capabilities": [
"function_calling",
- "structured_output"
+ "structured_output",
+ "streaming"
],
"pricing": {},
"metadata": {
+ "description": "The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
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+ "output_modalities": [
+ "text"
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+ "tokenizer": "Llama3",
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+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -17217,12 +38968,469 @@
"knowledge": "2024-12"
}
},
+ {
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+ "name": "Meta: Llama 4 Maverick",
+ "provider": "openrouter",
+ "family": "meta-llama",
+ "created_at": "2025-04-05 19:37:02 UTC",
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+ "output_per_million": 0.6
+ }
+ }
+ },
+ "metadata": {
+ "description": "Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward...",
+ "architecture": {
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+ "top_k",
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+ }
+ },
+ {
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+ "name": "Meta: Llama 4 Scout",
+ "provider": "openrouter",
+ "family": "meta-llama",
+ "created_at": "2025-04-05 19:31:59 UTC",
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+ "metadata": {
+ "description": "Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...",
+ "architecture": {
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+ "name": "Llama Guard 3 8B",
+ "provider": "openrouter",
+ "family": "meta-llama",
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+ "metadata": {
+ "description": "Llama Guard 3 is a Llama-3.1-8B pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM inputs (prompt classification)...",
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+ }
+ },
+ {
+ "id": "meta-llama/llama-guard-4-12b",
+ "name": "Meta: Llama Guard 4 12B",
+ "provider": "openrouter",
+ "family": "meta-llama",
+ "created_at": "2025-04-30 01:06:33 UTC",
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+ }
+ }
+ },
+ "metadata": {
+ "description": "Llama Guard 4 is a Llama 4 Scout-derived multimodal pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM...",
+ "architecture": {
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+ "input_modalities": [
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+ "text"
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+ "output_modalities": [
+ "text"
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+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 163840,
+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "temperature",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "microsoft/phi-4",
+ "name": "Microsoft: Phi 4",
+ "provider": "openrouter",
+ "family": "microsoft",
+ "created_at": "2025-01-10 06:17:52 UTC",
+ "context_window": 16384,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.065,
+ "output_per_million": 0.14
+ }
+ }
+ },
+ "metadata": {
+ "description": "[Microsoft Research](/microsoft) Phi-4 is designed to perform well in complex reasoning tasks and can operate efficiently in situations with limited memory or where quick responses are needed. At 14 billion...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
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+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "microsoft/phi-4-mini-instruct",
+ "name": "Microsoft: Phi 4 Mini Instruct",
+ "provider": "openrouter",
+ "family": "microsoft",
+ "created_at": "2025-10-17 18:34:09 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 128000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.08,
+ "output_per_million": 0.35,
+ "cache_read_input_per_million": 0.08
+ }
+ }
+ },
+ "metadata": {
+ "description": "Phi-4-mini-instruct is a lightweight open model built upon synthetic data and filtered publicly available websites - with a focus on high-quality, reasoning dense data. The model belongs to the Phi-4...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 128000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "microsoft/wizardlm-2-8x22b",
+ "name": "WizardLM-2 8x22B",
+ "provider": "openrouter",
+ "family": "microsoft",
+ "created_at": "2024-04-16 00:00:00 UTC",
+ "context_window": 65535,
+ "max_output_tokens": 8000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.62,
+ "output_per_million": 0.62
+ }
+ }
+ },
+ "metadata": {
+ "description": "WizardLM-2 8x22B is Microsoft AI's most advanced Wizard model. It demonstrates highly competitive performance compared to leading proprietary models, and it consistently outperforms all existing state-of-the-art opensource models. It is...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Mistral",
+ "instruct_type": "vicuna"
+ },
+ "top_provider": {
+ "context_length": 65535,
+ "max_completion_tokens": 8000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "presence_penalty",
+ "repetition_penalty",
+ "seed",
+ "stop",
+ "temperature",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
{
"id": "minimax/minimax-01",
"name": "MiniMax-01",
"provider": "openrouter",
"family": "minimax",
- "created_at": "2025-01-15 00:00:00 +0530",
+ "created_at": "2025-01-15 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 1000000,
"knowledge_cutoff": null,
@@ -17238,7 +39446,8 @@
"capabilities": [
"function_calling",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -17249,6 +39458,30 @@
}
},
"metadata": {
+ "description": "MiniMax-01 is a combines MiniMax-Text-01 for text generation and MiniMax-VL-01 for image understanding. It has 456 billion parameters, with 45.9 billion parameters activated per inference, and can handle a context...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1000192,
+ "max_completion_tokens": 1000192,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "temperature",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -17270,7 +39503,7 @@
"name": "MiniMax M1",
"provider": "openrouter",
"family": "minimax",
- "created_at": "2025-06-17 00:00:00 +0530",
+ "created_at": "2025-06-17 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 40000,
"knowledge_cutoff": null,
@@ -17284,7 +39517,8 @@
},
"capabilities": [
"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -17295,6 +39529,39 @@
}
},
"metadata": {
+ "description": "MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom \"lightning attention\" mechanism, allowing it...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1000000,
+ "max_completion_tokens": 40000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "seed",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -17316,7 +39583,7 @@
"name": "MiniMax M2",
"provider": "openrouter",
"family": "minimax",
- "created_at": "2025-10-23 00:00:00 +0530",
+ "created_at": "2025-10-23 00:00:00 UTC",
"context_window": 196600,
"max_output_tokens": 118000,
"knowledge_cutoff": null,
@@ -17331,18 +39598,58 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.28,
"output_per_million": 1.15,
- "cached_input_per_million": 0.28
+ "cache_read_input_per_million": 0.28,
+ "cache_write_input_per_million": 1.15
}
}
},
"metadata": {
+ "description": "MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier intelligence across general reasoning,...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 196608,
+ "max_completion_tokens": 196608,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -17364,12 +39671,67 @@
}
}
},
+ {
+ "id": "minimax/minimax-m2-her",
+ "name": "MiniMax: MiniMax M2-her",
+ "provider": "openrouter",
+ "family": "minimax",
+ "created_at": "2026-01-23 14:07:19 UTC",
+ "context_window": 65536,
+ "max_output_tokens": 2048,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.3,
+ "output_per_million": 1.2,
+ "cache_read_input_per_million": 0.03
+ }
+ }
+ },
+ "metadata": {
+ "description": "MiniMax M2-her is a dialogue-first large language model built for immersive roleplay, character-driven chat, and expressive multi-turn conversations. Designed to stay consistent in tone and personality, it supports rich message...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 65536,
+ "max_completion_tokens": 2048,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "temperature",
+ "top_p"
+ ]
+ }
+ },
{
"id": "minimax/minimax-m2.1",
"name": "MiniMax M2.1",
"provider": "openrouter",
"family": "minimax",
- "created_at": "2025-12-23 00:00:00 +0530",
+ "created_at": "2025-12-23 00:00:00 UTC",
"context_window": 204800,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -17384,7 +39746,9 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -17395,6 +39759,43 @@
}
},
"metadata": {
+ "description": "MiniMax-M2.1 is a lightweight, state-of-the-art large language model optimized for coding, agentic workflows, and modern application development. With only 10 billion activated parameters, it delivers a major jump in real-world...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 196608,
+ "max_completion_tokens": 196608,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -17419,7 +39820,7 @@
"name": "MiniMax M2.5",
"provider": "openrouter",
"family": "minimax",
- "created_at": "2026-02-12 00:00:00 +0530",
+ "created_at": "2026-02-12 00:00:00 UTC",
"context_window": 204800,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -17434,18 +39835,61 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.3,
"output_per_million": 1.2,
- "cached_input_per_million": 0.03
+ "cache_read_input_per_million": 0.03
}
}
},
"metadata": {
+ "description": "MiniMax-M2.5 is a SOTA large language model designed for real-world productivity. Trained in a diverse range of complex real-world digital working environments, M2.5 builds upon the coding expertise of M2.1...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 196608,
+ "max_completion_tokens": 131072,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "min_p",
+ "parallel_tool_calls",
+ "presence_penalty",
+ "reasoning",
+ "reasoning_effort",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -17471,7 +39915,7 @@
"name": "MiniMax M2.5 (free)",
"provider": "openrouter",
"family": "minimax",
- "created_at": "2026-02-12 00:00:00 +0530",
+ "created_at": "2026-02-12 00:00:00 UTC",
"context_window": 204800,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -17486,10 +39930,39 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {},
"metadata": {
+ "description": "MiniMax-M2.5 is a SOTA large language model designed for real-world productivity. Trained in a diverse range of complex real-world digital working environments, M2.5 builds upon the coding expertise of M2.1...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 196608,
+ "max_completion_tokens": 8192,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "temperature",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -17514,7 +39987,7 @@
"name": "MiniMax M2.7",
"provider": "openrouter",
"family": "minimax",
- "created_at": "2026-03-18 00:00:00 +0530",
+ "created_at": "2026-03-18 00:00:00 UTC",
"context_window": 204800,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -17528,18 +40001,61 @@
},
"capabilities": [
"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "structured_output",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.3,
"output_per_million": 1.2,
- "cached_input_per_million": 0.06
+ "cache_read_input_per_million": 0.06,
+ "cache_write_input_per_million": 0.375
}
}
},
"metadata": {
+ "description": "MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 196608,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -17563,7 +40079,7 @@
"name": "Codestral 2508",
"provider": "openrouter",
"family": "codestral",
- "created_at": "2025-08-01 00:00:00 +0530",
+ "created_at": "2025-08-01 00:00:00 UTC",
"context_window": 256000,
"max_output_tokens": 256000,
"knowledge_cutoff": null,
@@ -17577,7 +40093,8 @@
},
"capabilities": [
"function_calling",
- "structured_output"
+ "structured_output",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -17588,6 +40105,37 @@
}
},
"metadata": {
+ "description": "Mistral's cutting-edge language model for coding released end of July 2025. Codestral specializes in low-latency, high-frequency tasks such as fill-in-the-middle (FIM), code correction and test generation.\n\n[Blog Post](https://mistral.ai/news/codestral-25-08)",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Mistral",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 256000,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -17610,7 +40158,7 @@
"name": "Devstral 2 2512",
"provider": "openrouter",
"family": "devstral",
- "created_at": "2025-09-12 00:00:00 +0530",
+ "created_at": "2025-09-12 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 262144,
"knowledge_cutoff": null,
@@ -17624,7 +40172,8 @@
},
"capabilities": [
"function_calling",
- "structured_output"
+ "structured_output",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -17635,6 +40184,37 @@
}
},
"metadata": {
+ "description": "Devstral 2 is a state-of-the-art open-source model by Mistral AI specializing in agentic coding. It is a 123B-parameter dense transformer model supporting a 256K context window. Devstral 2 supports exploring...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Mistral",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -17652,12 +40232,77 @@
"knowledge": "2025-12"
}
},
+ {
+ "id": "mistralai/devstral-medium",
+ "name": "Mistral: Devstral Medium",
+ "provider": "openrouter",
+ "family": "mistralai",
+ "created_at": "2025-07-10 15:28:41 UTC",
+ "context_window": 131072,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.39999999999999997,
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+ }
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+ "metadata": {
+ "description": "Devstral Medium is a high-performance code generation and agentic reasoning model developed jointly by Mistral AI and All Hands AI. Positioned as a step up from Devstral Small, it achieves...",
+ "architecture": {
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+ "text"
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+ "tool_choice",
+ "tools",
+ "top_p"
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+ }
+ },
{
"id": "mistralai/devstral-medium-2507",
"name": "Devstral Medium",
"provider": "openrouter",
"family": "devstral",
- "created_at": "2025-07-10 00:00:00 +0530",
+ "created_at": "2025-07-10 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -17699,12 +40344,77 @@
"knowledge": "2025-05"
}
},
+ {
+ "id": "mistralai/devstral-small",
+ "name": "Mistral: Devstral Small 1.1",
+ "provider": "openrouter",
+ "family": "mistralai",
+ "created_at": "2025-07-10 15:19:11 UTC",
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+ "description": "Devstral Small 1.1 is a 24B parameter open-weight language model for software engineering agents, developed by Mistral AI in collaboration with All Hands AI. Finetuned from Mistral Small 3.1 and...",
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+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
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+ }
+ },
{
"id": "mistralai/devstral-small-2505",
"name": "Devstral Small",
"provider": "openrouter",
"family": "devstral",
- "created_at": "2025-05-07 00:00:00 +0530",
+ "created_at": "2025-05-07 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 128000,
"knowledge_cutoff": null,
@@ -17750,7 +40460,7 @@
"name": "Devstral Small 1.1",
"provider": "openrouter",
"family": "devstral",
- "created_at": "2025-07-10 00:00:00 +0530",
+ "created_at": "2025-07-10 00:00:00 UTC",
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"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -17792,12 +40502,543 @@
"knowledge": "2025-05"
}
},
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+ "output_per_million": 0.19999999999999998,
+ "cache_read_input_per_million": 0.02
+ }
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+ },
+ "metadata": {
+ "description": "The largest model in the Ministral 3 family, Ministral 3 14B offers frontier capabilities and performance comparable to its larger Mistral Small 3.2 24B counterpart. A powerful and efficient language...",
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+ "cache_read_input_per_million": 0.01
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+ "metadata": {
+ "description": "A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.",
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+ "provider": "openrouter",
+ "family": "mistralai",
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+ "family": "mistralai",
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+ "cache_read_input_per_million": 0.19999999999999998
+ }
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+ },
+ "metadata": {
+ "description": "This is Mistral AI's flagship model, Mistral Large 2 (version `mistral-large-2407`). It's a proprietary weights-available model and excels at reasoning, code, JSON, chat, and more. Read the launch announcement [here](https://mistral.ai/news/mistral-large-2407/)....",
+ "architecture": {
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+ "family": "mistralai",
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+ "metadata": {
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+ "cache_read_input_per_million": 0.19999999999999998
+ }
+ }
+ },
+ "metadata": {
+ "description": "Mistral Large 2 2411 is an update of [Mistral Large 2](/mistralai/mistral-large) released together with [Pixtral Large 2411](/mistralai/pixtral-large-2411) It provides a significant upgrade on the previous [Mistral Large 24.07](/mistralai/mistral-large-2407), with notable...",
+ "architecture": {
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+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "mistralai/mistral-large-2512",
+ "name": "Mistral: Mistral Large 3 2512",
+ "provider": "openrouter",
+ "family": "mistralai",
+ "created_at": "2025-12-01 21:27:52 UTC",
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+ "cache_read_input_per_million": 0.049999999999999996
+ }
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+ "metadata": {
+ "description": "Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
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+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
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+ }
+ },
{
"id": "mistralai/mistral-medium-3",
"name": "Mistral Medium 3",
"provider": "openrouter",
"family": "mistral-medium",
- "created_at": "2025-05-07 00:00:00 +0530",
+ "created_at": "2025-05-07 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -17813,7 +41054,8 @@
"capabilities": [
"function_calling",
"structured_output",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -17824,6 +41066,38 @@
}
},
"metadata": {
+ "description": "Mistral Medium 3 is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances state-of-the-art reasoning and multimodal performance with 8× lower cost...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
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+ "output_modalities": [
+ "text"
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+ "tokenizer": "Mistral",
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+ "supported_parameters": [
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+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -17841,12 +41115,80 @@
"knowledge": "2025-05"
}
},
+ {
+ "id": "mistralai/mistral-medium-3-5",
+ "name": "Mistral: Mistral Medium 3.5",
+ "provider": "openrouter",
+ "family": "mistralai",
+ "created_at": "2026-04-30 17:33:59 UTC",
+ "context_window": 262144,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "standard": {
+ "input_per_million": 1.5,
+ "output_per_million": 7.5
+ }
+ }
+ },
+ "metadata": {
+ "description": "Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI. It supports text and image inputs with text output, and is designed for agentic workflows, coding, and complex...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
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+ "output_modalities": [
+ "text"
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+ "tokenizer": "Mistral",
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+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
{
"id": "mistralai/mistral-medium-3.1",
"name": "Mistral Medium 3.1",
"provider": "openrouter",
"family": "mistral-medium",
- "created_at": "2025-08-12 00:00:00 +0530",
+ "created_at": "2025-08-12 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 262144,
"knowledge_cutoff": null,
@@ -17862,7 +41204,8 @@
"capabilities": [
"function_calling",
"structured_output",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -17873,6 +41216,38 @@
}
},
"metadata": {
+ "description": "Mistral Medium 3.1 is an updated version of Mistral Medium 3, which is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
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+ "tokenizer": "Mistral",
+ "instruct_type": null
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+ "max_completion_tokens": null,
+ "is_moderated": false
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+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -17890,12 +41265,214 @@
"knowledge": "2025-05"
}
},
+ {
+ "id": "mistralai/mistral-nemo",
+ "name": "Mistral: Mistral Nemo",
+ "provider": "openrouter",
+ "family": "mistralai",
+ "created_at": "2024-07-19 00:00:00 UTC",
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+ "input_per_million": 0.02,
+ "output_per_million": 0.03
+ }
+ }
+ },
+ "metadata": {
+ "description": "A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. The model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese,...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
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+ "output_modalities": [
+ "text"
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+ "tokenizer": "Mistral",
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+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "mistralai/mistral-saba",
+ "name": "Mistral: Saba",
+ "provider": "openrouter",
+ "family": "mistralai",
+ "created_at": "2025-02-17 14:40:39 UTC",
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+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
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+ "output_per_million": 0.6,
+ "cache_read_input_per_million": 0.02
+ }
+ }
+ },
+ "metadata": {
+ "description": "Mistral Saba is a 24B-parameter language model specifically designed for the Middle East and South Asia, delivering accurate and contextually relevant responses while maintaining efficient performance. Trained on curated regional...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
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+ "output_modalities": [
+ "text"
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+ "tokenizer": "Mistral",
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+ "response_format",
+ "seed",
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+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "mistralai/mistral-small-24b-instruct-2501",
+ "name": "Mistral: Mistral Small 3",
+ "provider": "openrouter",
+ "family": "mistralai",
+ "created_at": "2025-01-30 16:43:29 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 16384,
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+ "standard": {
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+ "output_per_million": 0.08
+ }
+ }
+ },
+ "metadata": {
+ "description": "Mistral Small 3 is a 24B-parameter language model optimized for low-latency performance across common AI tasks. Released under the Apache 2.0 license, it features both pre-trained and instruction-tuned versions designed...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Mistral",
+ "instruct_type": null
+ },
+ "top_provider": {
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+ "max_completion_tokens": 16384,
+ "is_moderated": false
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+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
{
"id": "mistralai/mistral-small-2603",
"name": "Mistral Small 4",
"provider": "openrouter",
"family": "mistral-small",
- "created_at": "2026-03-16 00:00:00 +0530",
+ "created_at": "2026-03-16 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 262144,
"knowledge_cutoff": null,
@@ -17911,7 +41488,9 @@
"capabilities": [
"function_calling",
"reasoning",
- "vision"
+ "vision",
+ "streaming",
+ "structured_output"
],
"pricing": {
"text_tokens": {
@@ -17922,6 +41501,41 @@
}
},
"metadata": {
+ "description": "Mistral Small 4 is the next major release in the Mistral Small family, unifying the capabilities of several flagship Mistral models into a single system. It combines strong reasoning from...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Mistral",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -17944,7 +41558,7 @@
"name": "Mistral Small 3.1 24B Instruct",
"provider": "openrouter",
"family": "mistral-small",
- "created_at": "2025-03-17 00:00:00 +0530",
+ "created_at": "2025-03-17 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -17960,10 +41574,47 @@
"capabilities": [
"function_calling",
"structured_output",
- "vision"
+ "vision",
+ "streaming"
],
- "pricing": {},
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.35,
+ "output_per_million": 0.56
+ }
+ }
+ },
"metadata": {
+ "description": "Mistral Small 3.1 24B Instruct is an upgraded variant of Mistral Small 3 (2501), featuring 24 billion parameters with advanced multimodal capabilities. It provides state-of-the-art performance in text-based reasoning and...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Mistral",
+ "instruct_type": null
+ },
+ "top_provider": {
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+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "presence_penalty",
+ "repetition_penalty",
+ "seed",
+ "temperature",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -17986,7 +41637,7 @@
"name": "Mistral Small 3.2 24B Instruct",
"provider": "openrouter",
"family": "mistral-small",
- "created_at": "2025-06-20 00:00:00 +0530",
+ "created_at": "2025-06-20 00:00:00 UTC",
"context_window": 96000,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -18002,10 +41653,55 @@
"capabilities": [
"function_calling",
"structured_output",
- "vision"
+ "vision",
+ "streaming",
+ "predicted_outputs"
],
- "pricing": {},
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.075,
+ "output_per_million": 0.19999999999999998
+ }
+ }
+ },
"metadata": {
+ "description": "Mistral-Small-3.2-24B-Instruct-2506 is an updated 24B parameter model from Mistral optimized for instruction following, repetition reduction, and improved function calling. Compared to the 3.1 release, version 3.2 significantly improves accuracy on...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "image",
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Mistral",
+ "instruct_type": null
+ },
+ "top_provider": {
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+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -18023,12 +41719,280 @@
"knowledge": "2024-10"
}
},
+ {
+ "id": "mistralai/mixtral-8x22b-instruct",
+ "name": "Mistral: Mixtral 8x22B Instruct",
+ "provider": "openrouter",
+ "family": "mistralai",
+ "created_at": "2024-04-17 00:00:00 UTC",
+ "context_window": 65536,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
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+ "output": [
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+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
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+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 2.0,
+ "output_per_million": 6.0,
+ "cache_read_input_per_million": 0.19999999999999998
+ }
+ }
+ },
+ "metadata": {
+ "description": "Mistral's official instruct fine-tuned version of [Mixtral 8x22B](/models/mistralai/mixtral-8x22b). It uses 39B active parameters out of 141B, offering unparalleled cost efficiency for its size. Its strengths include: - strong math, coding,...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Mistral",
+ "instruct_type": "mistral"
+ },
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+ "max_completion_tokens": null,
+ "is_moderated": false
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+ "supported_parameters": [
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+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "mistralai/mixtral-8x7b-instruct",
+ "name": "Mistral: Mixtral 8x7B Instruct",
+ "provider": "openrouter",
+ "family": "mistralai",
+ "created_at": "2023-12-10 00:00:00 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.54,
+ "output_per_million": 0.54
+ }
+ }
+ },
+ "metadata": {
+ "description": "Mixtral 8x7B Instruct is a pretrained generative Sparse Mixture of Experts, by Mistral AI, for chat and instruction use. Incorporates 8 experts (feed-forward networks) for a total of 47 billion...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Mistral",
+ "instruct_type": "mistral"
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+ "max_completion_tokens": 16384,
+ "is_moderated": false
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+ "supported_parameters": [
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+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "mistralai/pixtral-large-2411",
+ "name": "Mistral: Pixtral Large 2411",
+ "provider": "openrouter",
+ "family": "mistralai",
+ "created_at": "2024-11-19 00:49:48 UTC",
+ "context_window": 131072,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 2.0,
+ "output_per_million": 6.0,
+ "cache_read_input_per_million": 0.19999999999999998
+ }
+ }
+ },
+ "metadata": {
+ "description": "Pixtral Large is a 124B parameter, open-weight, multimodal model built on top of [Mistral Large 2](/mistralai/mistral-large-2411). The model is able to understand documents, charts and natural images. The model is...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Mistral",
+ "instruct_type": null
+ },
+ "top_provider": {
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+ "max_completion_tokens": null,
+ "is_moderated": false
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+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "mistralai/voxtral-small-24b-2507",
+ "name": "Mistral: Voxtral Small 24B 2507",
+ "provider": "openrouter",
+ "family": "mistralai",
+ "created_at": "2025-10-30 14:39:04 UTC",
+ "context_window": 32000,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "audio"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.09999999999999999,
+ "output_per_million": 0.3,
+ "cache_read_input_per_million": 0.01
+ }
+ }
+ },
+ "metadata": {
+ "description": "Voxtral Small is an enhancement of Mistral Small 3, incorporating state-of-the-art audio input capabilities while retaining best-in-class text performance. It excels at speech transcription, translation and audio understanding. Input audio...",
+ "architecture": {
+ "modality": "text+audio->text",
+ "input_modalities": [
+ "text",
+ "audio"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Mistral",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 32000,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
{
"id": "moonshotai/kimi-k2",
"name": "Kimi K2",
"provider": "openrouter",
"family": "kimi",
- "created_at": "2025-07-11 00:00:00 +0530",
+ "created_at": "2025-07-11 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -18041,7 +42005,8 @@
]
},
"capabilities": [
- "function_calling"
+ "function_calling",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -18052,6 +42017,37 @@
}
},
"metadata": {
+ "description": "Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It is optimized for...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 32768,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "presence_penalty",
+ "repetition_penalty",
+ "seed",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -18074,7 +42070,7 @@
"name": "Kimi K2 Instruct 0905",
"provider": "openrouter",
"family": "kimi",
- "created_at": "2025-09-05 00:00:00 +0530",
+ "created_at": "2025-09-05 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 16384,
"knowledge_cutoff": null,
@@ -18088,7 +42084,9 @@
},
"capabilities": [
"function_calling",
- "structured_output"
+ "structured_output",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -18099,6 +42097,41 @@
}
},
"metadata": {
+ "description": "Kimi K2 0905 is the September update of [Kimi K2 0711](moonshotai/kimi-k2). It is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": 262144,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -18121,7 +42154,7 @@
"name": "Kimi K2 Instruct 0905 (exacto)",
"provider": "openrouter",
"family": "kimi",
- "created_at": "2025-09-05 00:00:00 +0530",
+ "created_at": "2025-09-05 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 16384,
"knowledge_cutoff": null,
@@ -18168,7 +42201,7 @@
"name": "Kimi K2 Thinking",
"provider": "openrouter",
"family": "kimi-thinking",
- "created_at": "2025-11-06 00:00:00 +0530",
+ "created_at": "2025-11-06 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 262144,
"knowledge_cutoff": null,
@@ -18183,18 +42216,57 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.6,
"output_per_million": 2.5,
- "cached_input_per_million": 0.15
+ "cache_read_input_per_million": 0.15
}
}
},
"metadata": {
+ "description": "Kimi K2 Thinking is Moonshot AI’s most advanced open reasoning model to date, extending the K2 series into agentic, long-horizon reasoning. Built on the trillion-parameter Mixture-of-Experts (MoE) architecture introduced in...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": 262144,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -18221,7 +42293,7 @@
"name": "Kimi K2.5",
"provider": "openrouter",
"family": "kimi",
- "created_at": "2026-01-27 00:00:00 +0530",
+ "created_at": "2026-01-27 00:00:00 UTC",
"context_window": 262144,
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@@ -18272,12 +42387,409 @@
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{
"id": "nousresearch/hermes-3-llama-3.1-405b:free",
"name": "Hermes 3 405B Instruct (free)",
"provider": "openrouter",
"family": "hermes",
- "created_at": "2024-08-16 00:00:00 +0530",
+ "created_at": "2024-08-16 00:00:00 UTC",
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@@ -18290,10 +42802,38 @@
]
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- "reasoning"
+ "reasoning",
+ "streaming"
],
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+ "description": "Hermes 3 is a generalist language model with many improvements over Hermes 2, including advanced agentic capabilities, much better roleplaying, reasoning, multi-turn conversation, long context coherence, and improvements across the...",
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+ "top_p"
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"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -18311,12 +42851,78 @@
"knowledge": "2023-12"
}
},
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+ "name": "Nous: Hermes 3 70B Instruct",
+ "provider": "openrouter",
+ "family": "nousresearch",
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+ "description": "Hermes 3 is a generalist language model with many improvements over [Hermes 2](/models/nousresearch/nous-hermes-2-mistral-7b-dpo), including advanced agentic capabilities, much better roleplaying, reasoning, multi-turn conversation, long context coherence, and improvements across the...",
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+ "temperature",
+ "top_k",
+ "top_p"
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{
"id": "nousresearch/hermes-4-405b",
"name": "Hermes 4 405B",
"provider": "openrouter",
"family": "hermes",
- "created_at": "2025-08-25 00:00:00 +0530",
+ "created_at": "2025-08-25 00:00:00 UTC",
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@@ -18330,7 +42936,9 @@
},
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- "reasoning"
+ "reasoning",
+ "streaming",
+ "structured_output"
],
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"text_tokens": {
@@ -18341,6 +42949,36 @@
}
},
"metadata": {
+ "description": "Hermes 4 is a large-scale reasoning model built on Meta-Llama-3.1-405B and released by Nous Research. It introduces a hybrid reasoning mode, where the model can choose to deliberate internally with...",
+ "architecture": {
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@@ -18363,7 +43001,7 @@
"name": "Hermes 4 70B",
"provider": "openrouter",
"family": "hermes",
- "created_at": "2025-08-25 00:00:00 +0530",
+ "created_at": "2025-08-25 00:00:00 UTC",
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@@ -18378,7 +43016,8 @@
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- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
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@@ -18389,6 +43028,36 @@
}
},
"metadata": {
+ "description": "Hermes 4 70B is a hybrid reasoning model from Nous Research, built on Meta-Llama-3.1-70B. It introduces the same hybrid mode as the larger 405B release, allowing the model to either...",
+ "architecture": {
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"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -18406,12 +43075,220 @@
"knowledge": "2023-12"
}
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+ "name": "NVIDIA: Llama 3.1 Nemotron 70B Instruct",
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+ "description": "NVIDIA's Llama 3.1 Nemotron 70B is a language model designed for generating precise and useful responses. Leveraging [Llama 3.1 70B](/models/meta-llama/llama-3.1-70b-instruct) architecture and Reinforcement Learning from Human Feedback (RLHF), it excels...",
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+ "standard": {
+ "input_per_million": 0.049999999999999996,
+ "output_per_million": 0.19999999999999998
+ }
+ }
+ },
+ "metadata": {
+ "description": "NVIDIA Nemotron 3 Nano 30B A3B is a small language MoE model with highest compute efficiency and accuracy for developers to build specialized agentic AI systems. The model is fully...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": 228000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
{
"id": "nvidia/nemotron-3-nano-30b-a3b:free",
"name": "Nemotron 3 Nano 30B A3B (free)",
"provider": "openrouter",
"family": "nemotron",
- "created_at": "2025-12-14 00:00:00 +0530",
+ "created_at": "2025-12-14 00:00:00 UTC",
"context_window": 256000,
"max_output_tokens": 256000,
"knowledge_cutoff": null,
@@ -18426,10 +43303,39 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {},
"metadata": {
+ "description": "NVIDIA Nemotron 3 Nano 30B A3B is a small language MoE model with highest compute efficiency and accuracy for developers to build specialized agentic AI systems. The model is fully...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 256000,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "seed",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -18447,12 +43353,88 @@
"knowledge": "2025-11"
}
},
+ {
+ "id": "nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free",
+ "name": "Nemotron 3 Nano Omni (free)",
+ "provider": "openrouter",
+ "family": "nemotron",
+ "created_at": "2026-04-28 00:00:00 UTC",
+ "context_window": 256000,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "video",
+ "audio"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "reasoning",
+ "vision",
+ "streaming"
+ ],
+ "pricing": {},
+ "metadata": {
+ "description": "NVIDIA Nemotron™ 3 Nano Omni is a 30B-A3B open multimodal model designed to function as a perception and context sub-agent in enterprise agent systems. It accepts text, image, video, and...",
+ "architecture": {
+ "modality": "text+image+audio+video->text",
+ "input_modalities": [
+ "text",
+ "audio",
+ "image",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 256000,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "seed",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
+ "source": "models.dev",
+ "provider_id": "openrouter",
+ "open_weights": true,
+ "attachment": true,
+ "temperature": true,
+ "last_updated": "2026-04-28",
+ "cost": {
+ "input": 0,
+ "output": 0
+ },
+ "limit": {
+ "context": 256000,
+ "output": 65536
+ }
+ }
+ },
{
"id": "nvidia/nemotron-3-super-120b-a12b",
"name": "Nemotron 3 Super",
"provider": "openrouter",
"family": "nemotron",
- "created_at": "2026-03-11 00:00:00 +0530",
+ "created_at": "2026-03-11 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 262144,
"knowledge_cutoff": null,
@@ -18466,7 +43448,10 @@
},
"capabilities": [
"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "structured_output",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -18477,6 +43462,44 @@
}
},
"metadata": {
+ "description": "NVIDIA Nemotron 3 Super is a 120B-parameter open hybrid MoE model, activating just 12B parameters for maximum compute efficiency and accuracy in complex multi-agent applications. Built on a hybrid Mamba-Transformer...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -18499,7 +43522,7 @@
"name": "Nemotron 3 Super (free)",
"provider": "openrouter",
"family": "nemotron",
- "created_at": "2026-03-11 00:00:00 +0530",
+ "created_at": "2026-03-11 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 262144,
"knowledge_cutoff": null,
@@ -18513,10 +43536,42 @@
},
"capabilities": [
"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "structured_output"
],
"pricing": {},
"metadata": {
+ "description": "NVIDIA Nemotron 3 Super is a 120B-parameter open hybrid MoE model, activating just 12B parameters for maximum compute efficiency and accuracy in complex multi-agent applications. Built on a hybrid Mamba-Transformer...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": 262144,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -18534,12 +43589,83 @@
"knowledge": "2024-04"
}
},
+ {
+ "id": "nvidia/nemotron-nano-12b-v2-vl",
+ "name": "NVIDIA: Nemotron Nano 12B 2 VL",
+ "provider": "openrouter",
+ "family": "nvidia",
+ "created_at": "2025-10-28 18:19:25 UTC",
+ "context_window": 131072,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "image",
+ "text",
+ "video"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.19999999999999998,
+ "output_per_million": 0.6
+ }
+ }
+ },
+ "metadata": {
+ "description": "NVIDIA Nemotron Nano 2 VL is a 12-billion-parameter open multimodal reasoning model designed for video understanding and document intelligence. It introduces a hybrid Transformer-Mamba architecture, combining transformer-level accuracy with Mamba’s...",
+ "architecture": {
+ "modality": "text+image+video->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "temperature",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
{
"id": "nvidia/nemotron-nano-12b-v2-vl:free",
"name": "Nemotron Nano 12B 2 VL (free)",
"provider": "openrouter",
"family": "nemotron",
- "created_at": "2025-10-28 00:00:00 +0530",
+ "created_at": "2025-10-28 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 128000,
"knowledge_cutoff": null,
@@ -18555,10 +43681,41 @@
"capabilities": [
"function_calling",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {},
"metadata": {
+ "description": "NVIDIA Nemotron Nano 2 VL is a 12-billion-parameter open multimodal reasoning model designed for video understanding and document intelligence. It introduces a hybrid Transformer-Mamba architecture, combining transformer-level accuracy with Mamba’s...",
+ "architecture": {
+ "modality": "text+image+video->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 128000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "seed",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -18581,7 +43738,7 @@
"name": "nvidia-nemotron-nano-9b-v2",
"provider": "openrouter",
"family": "nemotron",
- "created_at": "2025-08-18 00:00:00 +0530",
+ "created_at": "2025-08-18 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -18595,7 +43752,10 @@
},
"capabilities": [
"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "structured_output",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -18606,6 +43766,42 @@
}
},
"metadata": {
+ "description": "NVIDIA-Nemotron-Nano-9B-v2 is a large language model (LLM) trained from scratch by NVIDIA, and designed as a unified model for both reasoning and non-reasoning tasks. It responds to user queries and...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -18628,7 +43824,7 @@
"name": "Nemotron Nano 9B V2 (free)",
"provider": "openrouter",
"family": "nemotron",
- "created_at": "2025-09-05 00:00:00 +0530",
+ "created_at": "2025-09-05 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 128000,
"knowledge_cutoff": null,
@@ -18643,10 +43839,41 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {},
"metadata": {
+ "description": "NVIDIA-Nemotron-Nano-9B-v2 is a large language model (LLM) trained from scratch by NVIDIA, and designed as a unified model for both reasoning and non-reasoning tasks. It responds to user queries and...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -18664,12 +43891,616 @@
"knowledge": "2024-09"
}
},
+ {
+ "id": "openai/gpt-3.5-turbo",
+ "name": "OpenAI: GPT-3.5 Turbo",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2023-05-28 00:00:00 UTC",
+ "context_window": 16385,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.5,
+ "output_per_million": 1.5
+ }
+ }
+ },
+ "metadata": {
+ "description": "GPT-3.5 Turbo is OpenAI's fastest model. It can understand and generate natural language or code, and is optimized for chat and traditional completion tasks.\n\nTraining data up to Sep 2021.",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 16385,
+ "max_completion_tokens": 4096,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "openai/gpt-3.5-turbo-0613",
+ "name": "OpenAI: GPT-3.5 Turbo (older v0613)",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2024-01-25 00:00:00 UTC",
+ "context_window": 4095,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 1.0,
+ "output_per_million": 2.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "GPT-3.5 Turbo is OpenAI's fastest model. It can understand and generate natural language or code, and is optimized for chat and traditional completion tasks.\n\nTraining data up to Sep 2021.",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 4095,
+ "max_completion_tokens": 4096,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_completion_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "openai/gpt-3.5-turbo-16k",
+ "name": "OpenAI: GPT-3.5 Turbo 16k",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2023-08-28 00:00:00 UTC",
+ "context_window": 16385,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 3.0,
+ "output_per_million": 4.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "This model offers four times the context length of gpt-3.5-turbo, allowing it to support approximately 20 pages of text in a single request at a higher cost. Training data: up...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 16385,
+ "max_completion_tokens": 4096,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_completion_tokens",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "openai/gpt-3.5-turbo-instruct",
+ "name": "OpenAI: GPT-3.5 Turbo Instruct",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2023-09-28 00:00:00 UTC",
+ "context_window": 4095,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 1.5,
+ "output_per_million": 2.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "This model is a variant of GPT-3.5 Turbo tuned for instructional prompts and omitting chat-related optimizations. Training data: up to Sep 2021.",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": "chatml"
+ },
+ "top_provider": {
+ "context_length": 4095,
+ "max_completion_tokens": 4096,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "openai/gpt-4",
+ "name": "OpenAI: GPT-4",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2023-05-28 00:00:00 UTC",
+ "context_window": 8191,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 30.0,
+ "output_per_million": 60.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "OpenAI's flagship model, GPT-4 is a large-scale multimodal language model capable of solving difficult problems with greater accuracy than previous models due to its broader general knowledge and advanced reasoning...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 8191,
+ "max_completion_tokens": 4096,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_completion_tokens",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "openai/gpt-4-0314",
+ "name": "OpenAI: GPT-4 (older v0314)",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2023-05-28 00:00:00 UTC",
+ "context_window": 8191,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 30.0,
+ "output_per_million": 60.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "GPT-4-0314 is the first version of GPT-4 released, with a context length of 8,192 tokens, and was supported until June 14. Training data: up to Sep 2021.",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 8191,
+ "max_completion_tokens": 4096,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "openai/gpt-4-1106-preview",
+ "name": "OpenAI: GPT-4 Turbo (older v1106)",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2023-11-06 00:00:00 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 10.0,
+ "output_per_million": 30.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "The latest GPT-4 Turbo model with vision capabilities. Vision requests can now use JSON mode and function calling.\n\nTraining data: up to April 2023.",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 4096,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "openai/gpt-4-turbo",
+ "name": "OpenAI: GPT-4 Turbo",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2024-04-09 00:00:00 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 10.0,
+ "output_per_million": 30.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "The latest GPT-4 Turbo model with vision capabilities. Vision requests can now use JSON mode and function calling.\n\nTraining data: up to December 2023.",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 4096,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "openai/gpt-4-turbo-preview",
+ "name": "OpenAI: GPT-4 Turbo Preview",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2024-01-25 00:00:00 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 10.0,
+ "output_per_million": 30.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "The preview GPT-4 model with improved instruction following, JSON mode, reproducible outputs, parallel function calling, and more. Training data: up to Dec 2023. **Note:** heavily rate limited by OpenAI while...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 4096,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
{
"id": "openai/gpt-4.1",
"name": "GPT-4.1",
"provider": "openrouter",
"family": "gpt",
- "created_at": "2025-04-14 00:00:00 +0530",
+ "created_at": "2025-04-14 00:00:00 UTC",
"context_window": 1047576,
"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -18685,18 +44516,50 @@
"capabilities": [
"function_calling",
"structured_output",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 2,
"output_per_million": 8,
- "cached_input_per_million": 0.5
+ "cache_read_input_per_million": 0.5
}
}
},
"metadata": {
+ "description": "GPT-4.1 is a flagship large language model optimized for advanced instruction following, real-world software engineering, and long-context reasoning. It supports a 1 million token context window and outperforms GPT-4o and...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1047576,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_completion_tokens",
+ "max_tokens",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -18720,7 +44583,7 @@
"name": "GPT-4.1 Mini",
"provider": "openrouter",
"family": "gpt-mini",
- "created_at": "2025-04-14 00:00:00 +0530",
+ "created_at": "2025-04-14 00:00:00 UTC",
"context_window": 1047576,
"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -18736,18 +44599,50 @@
"capabilities": [
"function_calling",
"structured_output",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.4,
"output_per_million": 1.6,
- "cached_input_per_million": 0.1
+ "cache_read_input_per_million": 0.1
}
}
},
"metadata": {
+ "description": "GPT-4.1 Mini is a mid-sized model delivering performance competitive with GPT-4o at substantially lower latency and cost. It retains a 1 million token context window and scores 45.1% on hard...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1047576,
+ "max_completion_tokens": 32768,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_completion_tokens",
+ "max_tokens",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -18766,12 +44661,443 @@
"knowledge": "2024-04"
}
},
+ {
+ "id": "openai/gpt-4.1-nano",
+ "name": "OpenAI: GPT-4.1 Nano",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2025-04-14 17:22:49 UTC",
+ "context_window": 1047576,
+ "max_output_tokens": 32768,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "image",
+ "text",
+ "file"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.09999999999999999,
+ "output_per_million": 0.39999999999999997,
+ "cache_read_input_per_million": 0.024999999999999998
+ }
+ }
+ },
+ "metadata": {
+ "description": "For tasks that demand low latency, GPT‑4.1 nano is the fastest and cheapest model in the GPT-4.1 series. It delivers exceptional performance at a small size with its 1 million...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1047576,
+ "max_completion_tokens": 32768,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_completion_tokens",
+ "max_tokens",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "openai/gpt-4o",
+ "name": "OpenAI: GPT-4o",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2024-05-13 00:00:00 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 2.5,
+ "output_per_million": 10.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "GPT-4o (\"o\" for \"omni\") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_completion_tokens",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p",
+ "web_search_options"
+ ]
+ }
+ },
+ {
+ "id": "openai/gpt-4o-2024-05-13",
+ "name": "OpenAI: GPT-4o (2024-05-13)",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2024-05-13 00:00:00 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 4096,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 5.0,
+ "output_per_million": 15.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "GPT-4o (\"o\" for \"omni\") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 4096,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_completion_tokens",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p",
+ "web_search_options"
+ ]
+ }
+ },
+ {
+ "id": "openai/gpt-4o-2024-08-06",
+ "name": "OpenAI: GPT-4o (2024-08-06)",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2024-08-06 00:00:00 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 2.5,
+ "output_per_million": 10.0,
+ "cache_read_input_per_million": 1.25
+ }
+ }
+ },
+ "metadata": {
+ "description": "The 2024-08-06 version of GPT-4o offers improved performance in structured outputs, with the ability to supply a JSON schema in the respone_format. Read more [here](https://openai.com/index/introducing-structured-outputs-in-the-api/). GPT-4o (\"o\" for \"omni\") is...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_completion_tokens",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p",
+ "web_search_options"
+ ]
+ }
+ },
+ {
+ "id": "openai/gpt-4o-2024-11-20",
+ "name": "OpenAI: GPT-4o (2024-11-20)",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2024-11-20 18:33:14 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 2.5,
+ "output_per_million": 10.0,
+ "cache_read_input_per_million": 1.25
+ }
+ }
+ },
+ "metadata": {
+ "description": "The 2024-11-20 version of GPT-4o offers a leveled-up creative writing ability with more natural, engaging, and tailored writing to improve relevance & readability. It’s also better at working with uploaded...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 16384,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p",
+ "web_search_options"
+ ]
+ }
+ },
+ {
+ "id": "openai/gpt-4o-audio-preview",
+ "name": "OpenAI: GPT-4o Audio",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2025-08-15 04:44:21 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "audio",
+ "text"
+ ],
+ "output": [
+ "text",
+ "audio"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 2.5,
+ "output_per_million": 10.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "The gpt-4o-audio-preview model adds support for audio inputs as prompts. This enhancement allows the model to detect nuances within audio recordings and add depth to generated user experiences. Audio outputs...",
+ "architecture": {
+ "modality": "text+audio->text+audio",
+ "input_modalities": [
+ "audio",
+ "text"
+ ],
+ "output_modalities": [
+ "text",
+ "audio"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 16384,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
{
"id": "openai/gpt-4o-mini",
"name": "GPT-4o-mini",
"provider": "openrouter",
"family": "gpt-mini",
- "created_at": "2024-07-18 00:00:00 +0530",
+ "created_at": "2024-07-18 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 16384,
"knowledge_cutoff": null,
@@ -18787,18 +45113,57 @@
"capabilities": [
"function_calling",
"structured_output",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.15,
"output_per_million": 0.6,
- "cached_input_per_million": 0.08
+ "cache_read_input_per_million": 0.08
}
}
},
"metadata": {
+ "description": "GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs. As their most advanced small model, it is many multiples more affordable...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_completion_tokens",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p",
+ "web_search_options"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -18817,12 +45182,197 @@
"knowledge": "2024-10"
}
},
+ {
+ "id": "openai/gpt-4o-mini-2024-07-18",
+ "name": "OpenAI: GPT-4o-mini (2024-07-18)",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2024-07-18 00:00:00 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.15,
+ "output_per_million": 0.6,
+ "cache_read_input_per_million": 0.075
+ }
+ }
+ },
+ "metadata": {
+ "description": "GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs. As their most advanced small model, it is many multiples more affordable...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 16384,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p",
+ "web_search_options"
+ ]
+ }
+ },
+ {
+ "id": "openai/gpt-4o-mini-search-preview",
+ "name": "OpenAI: GPT-4o-mini Search Preview",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2025-03-12 22:22:02 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.15,
+ "output_per_million": 0.6
+ }
+ }
+ },
+ "metadata": {
+ "description": "GPT-4o mini Search Preview is a specialized model for web search in Chat Completions. It is trained to understand and execute web search queries.",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 16384,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "response_format",
+ "structured_outputs",
+ "web_search_options"
+ ]
+ }
+ },
+ {
+ "id": "openai/gpt-4o-search-preview",
+ "name": "OpenAI: GPT-4o Search Preview",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2025-03-12 22:19:09 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 2.5,
+ "output_per_million": 10.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "GPT-4o Search Previewis a specialized model for web search in Chat Completions. It is trained to understand and execute web search queries.",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 16384,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "response_format",
+ "structured_outputs",
+ "web_search_options"
+ ]
+ }
+ },
{
"id": "openai/gpt-5",
"name": "GPT-5",
"provider": "openrouter",
"family": "gpt",
- "created_at": "2025-08-07 00:00:00 +0530",
+ "created_at": "2025-08-07 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2024-10-01",
@@ -18839,7 +45389,8 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -18850,6 +45401,37 @@
}
},
"metadata": {
+ "description": "GPT-5 is OpenAI’s most advanced model, offering major improvements in reasoning, code quality, and user experience. It is optimized for complex tasks that require step-by-step reasoning, instruction following, and accuracy...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 400000,
+ "max_completion_tokens": 128000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_completion_tokens",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -18872,7 +45454,7 @@
"name": "GPT-5 Chat (latest)",
"provider": "openrouter",
"family": "gpt-codex",
- "created_at": "2025-08-07 00:00:00 +0530",
+ "created_at": "2025-08-07 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2024-09-30",
@@ -18888,7 +45470,8 @@
"capabilities": [
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -18899,6 +45482,32 @@
}
},
"metadata": {
+ "description": "GPT-5 Chat is designed for advanced, natural, multimodal, and context-aware conversations for enterprise applications.",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "file",
+ "image",
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 16384,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "response_format",
+ "seed",
+ "structured_outputs"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -18921,7 +45530,7 @@
"name": "GPT-5 Codex",
"provider": "openrouter",
"family": "gpt-codex",
- "created_at": "2025-09-15 00:00:00 +0530",
+ "created_at": "2025-09-15 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2024-10-01",
@@ -18938,18 +45547,48 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 1.25,
"output_per_million": 10,
- "cached_input_per_million": 0.125
+ "cache_read_input_per_million": 0.125
}
}
},
"metadata": {
+ "description": "GPT-5-Codex is a specialized version of GPT-5 optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks....",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 400000,
+ "max_completion_tokens": 128000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -18973,7 +45612,7 @@
"name": "GPT-5 Image",
"provider": "openrouter",
"family": "gpt",
- "created_at": "2025-10-14 00:00:00 +0530",
+ "created_at": "2025-10-14 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2024-10-01",
@@ -18992,18 +45631,56 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 5,
"output_per_million": 10,
- "cached_input_per_million": 1.25
+ "cache_read_input_per_million": 1.25
}
}
},
"metadata": {
+ "description": "[GPT-5](https://openrouter.ai/openai/gpt-5) Image combines OpenAI's GPT-5 model with state-of-the-art image generation capabilities. It offers major improvements in reasoning, code quality, and user experience while incorporating GPT Image 1's superior instruction following,...",
+ "architecture": {
+ "modality": "text+image+file->text+image",
+ "input_modalities": [
+ "image",
+ "text",
+ "file"
+ ],
+ "output_modalities": [
+ "image",
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 400000,
+ "max_completion_tokens": 128000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -19022,12 +45699,85 @@
"knowledge": "2024-10-01"
}
},
+ {
+ "id": "openai/gpt-5-image-mini",
+ "name": "OpenAI: GPT-5 Image Mini",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2025-10-16 14:23:03 UTC",
+ "context_window": 400000,
+ "max_output_tokens": 128000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "file",
+ "image",
+ "text"
+ ],
+ "output": [
+ "image",
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 2.5,
+ "output_per_million": 2.0,
+ "cache_read_input_per_million": 0.25
+ }
+ }
+ },
+ "metadata": {
+ "description": "GPT-5 Image Mini combines OpenAI's advanced language capabilities, powered by [GPT-5 Mini](https://openrouter.ai/openai/gpt-5-mini), with GPT Image 1 Mini for efficient image generation. This natively multimodal model features superior instruction following, text...",
+ "architecture": {
+ "modality": "text+image+file->text+image",
+ "input_modalities": [
+ "file",
+ "image",
+ "text"
+ ],
+ "output_modalities": [
+ "image",
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 400000,
+ "max_completion_tokens": 128000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
{
"id": "openai/gpt-5-mini",
"name": "GPT-5 Mini",
"provider": "openrouter",
"family": "gpt-mini",
- "created_at": "2025-08-07 00:00:00 +0530",
+ "created_at": "2025-08-07 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2024-10-01",
@@ -19044,7 +45794,8 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -19055,6 +45806,37 @@
}
},
"metadata": {
+ "description": "GPT-5 Mini is a compact version of GPT-5, designed to handle lighter-weight reasoning tasks. It provides the same instruction-following and safety-tuning benefits as GPT-5, but with reduced latency and cost....",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 400000,
+ "max_completion_tokens": 128000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_completion_tokens",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -19077,7 +45859,7 @@
"name": "GPT-5 Nano",
"provider": "openrouter",
"family": "gpt-nano",
- "created_at": "2025-08-07 00:00:00 +0530",
+ "created_at": "2025-08-07 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2024-10-01",
@@ -19094,7 +45876,8 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -19105,6 +45888,37 @@
}
},
"metadata": {
+ "description": "GPT-5-Nano is the smallest and fastest variant in the GPT-5 system, optimized for developer tools, rapid interactions, and ultra-low latency environments. While limited in reasoning depth compared to its larger...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 400000,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_completion_tokens",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -19127,7 +45941,7 @@
"name": "GPT-5 Pro",
"provider": "openrouter",
"family": "gpt-pro",
- "created_at": "2025-10-06 00:00:00 +0530",
+ "created_at": "2025-10-06 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 272000,
"knowledge_cutoff": "2024-09-30",
@@ -19144,7 +45958,8 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -19155,6 +45970,36 @@
}
},
"metadata": {
+ "description": "GPT-5 Pro is OpenAI’s most advanced model, offering major improvements in reasoning, code quality, and user experience. It is optimized for complex tasks that require step-by-step reasoning, instruction following, and...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 400000,
+ "max_completion_tokens": 128000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -19177,7 +46022,7 @@
"name": "GPT-5.1",
"provider": "openrouter",
"family": "gpt",
- "created_at": "2025-11-13 00:00:00 +0530",
+ "created_at": "2025-11-13 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2024-09-30",
@@ -19194,18 +46039,50 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 1.25,
"output_per_million": 10,
- "cached_input_per_million": 0.125
+ "cache_read_input_per_million": 0.125
}
}
},
"metadata": {
+ "description": "GPT-5.1 is the latest frontier-grade model in the GPT-5 series, offering stronger general-purpose reasoning, improved instruction adherence, and a more natural conversational style compared to GPT-5. It uses adaptive reasoning...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 400000,
+ "max_completion_tokens": 128000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_completion_tokens",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -19229,7 +46106,7 @@
"name": "GPT-5.1 Chat",
"provider": "openrouter",
"family": "gpt-codex",
- "created_at": "2025-11-13 00:00:00 +0530",
+ "created_at": "2025-11-13 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 16384,
"knowledge_cutoff": "2024-09-30",
@@ -19246,18 +46123,48 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 1.25,
"output_per_million": 10,
- "cached_input_per_million": 0.125
+ "cache_read_input_per_million": 0.125
}
}
},
"metadata": {
+ "description": "GPT-5.1 Chat (AKA Instant is the fast, lightweight member of the 5.1 family, optimized for low-latency chat while retaining strong general intelligence. It uses adaptive reasoning to selectively “think” on...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "file",
+ "image",
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 16384,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_completion_tokens",
+ "max_tokens",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -19281,7 +46188,7 @@
"name": "GPT-5.1-Codex",
"provider": "openrouter",
"family": "gpt-codex",
- "created_at": "2025-11-13 00:00:00 +0530",
+ "created_at": "2025-11-13 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2024-09-30",
@@ -19298,18 +46205,49 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 1.25,
"output_per_million": 10,
- "cached_input_per_million": 0.125
+ "cache_read_input_per_million": 0.125
}
}
},
"metadata": {
+ "description": "GPT-5.1-Codex is a specialized version of GPT-5.1 optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks....",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 400000,
+ "max_completion_tokens": 128000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_completion_tokens",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -19333,7 +46271,7 @@
"name": "GPT-5.1-Codex-Max",
"provider": "openrouter",
"family": "gpt-codex",
- "created_at": "2025-11-13 00:00:00 +0530",
+ "created_at": "2025-11-13 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2024-09-30",
@@ -19350,18 +46288,49 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 1.1,
"output_per_million": 9,
- "cached_input_per_million": 0.11
+ "cache_read_input_per_million": 0.11
}
}
},
"metadata": {
+ "description": "GPT-5.1-Codex-Max is OpenAI’s latest agentic coding model, designed for long-running, high-context software development tasks. It is based on an updated version of the 5.1 reasoning stack and trained on agentic...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
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+ "max_completion_tokens": 128000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_completion_tokens",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -19385,7 +46354,7 @@
"name": "GPT-5.1-Codex-Mini",
"provider": "openrouter",
"family": "gpt-codex",
- "created_at": "2025-11-13 00:00:00 +0530",
+ "created_at": "2025-11-13 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 100000,
"knowledge_cutoff": "2024-09-30",
@@ -19402,18 +46371,49 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
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"output_per_million": 2,
- "cached_input_per_million": 0.025
+ "cache_read_input_per_million": 0.025
}
}
},
"metadata": {
+ "description": "GPT-5.1-Codex-Mini is a smaller and faster version of GPT-5.1-Codex",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "image",
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 400000,
+ "max_completion_tokens": 128000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_completion_tokens",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -19437,7 +46437,7 @@
"name": "GPT-5.2",
"provider": "openrouter",
"family": "gpt",
- "created_at": "2025-12-11 00:00:00 +0530",
+ "created_at": "2025-12-11 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2025-08-31",
@@ -19454,18 +46454,50 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
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"output_per_million": 14,
- "cached_input_per_million": 0.175
+ "cache_read_input_per_million": 0.175
}
}
},
"metadata": {
+ "description": "GPT-5.2 is the latest frontier-grade model in the GPT-5 series, offering stronger agentic and long context perfomance compared to GPT-5.1. It uses adaptive reasoning to allocate computation dynamically, responding quickly...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "file",
+ "image",
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 400000,
+ "max_completion_tokens": 128000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_completion_tokens",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -19489,7 +46521,7 @@
"name": "GPT-5.2 Chat",
"provider": "openrouter",
"family": "gpt-codex",
- "created_at": "2025-12-11 00:00:00 +0530",
+ "created_at": "2025-12-11 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 16384,
"knowledge_cutoff": "2025-08-31",
@@ -19506,18 +46538,48 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 1.75,
"output_per_million": 14,
- "cached_input_per_million": 0.175
+ "cache_read_input_per_million": 0.175
}
}
},
"metadata": {
+ "description": "GPT-5.2 Chat (AKA Instant) is the fast, lightweight member of the 5.2 family, optimized for low-latency chat while retaining strong general intelligence. It uses adaptive reasoning to selectively “think” on...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "file",
+ "image",
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 32000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_completion_tokens",
+ "max_tokens",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -19541,7 +46603,7 @@
"name": "GPT-5.2-Codex",
"provider": "openrouter",
"family": "gpt-codex",
- "created_at": "2026-01-14 00:00:00 +0530",
+ "created_at": "2026-01-14 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2025-08-31",
@@ -19558,18 +46620,49 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
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"output_per_million": 14,
- "cached_input_per_million": 0.175
+ "cache_read_input_per_million": 0.175
}
}
},
"metadata": {
+ "description": "GPT-5.2-Codex is an upgraded version of GPT-5.1-Codex optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks....",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 400000,
+ "max_completion_tokens": 128000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_completion_tokens",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -19593,7 +46686,7 @@
"name": "GPT-5.2 Pro",
"provider": "openrouter",
"family": "gpt-pro",
- "created_at": "2025-12-11 00:00:00 +0530",
+ "created_at": "2025-12-11 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2025-08-31",
@@ -19610,7 +46703,8 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -19621,6 +46715,36 @@
}
},
"metadata": {
+ "description": "GPT-5.2 Pro is OpenAI’s most advanced model, offering major improvements in agentic coding and long context performance over GPT-5 Pro. It is optimized for complex tasks that require step-by-step reasoning,...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 400000,
+ "max_completion_tokens": 128000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -19638,12 +46762,77 @@
"knowledge": "2025-08-31"
}
},
+ {
+ "id": "openai/gpt-5.3-chat",
+ "name": "OpenAI: GPT-5.3 Chat",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2026-03-03 18:54:21 UTC",
+ "context_window": 128000,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
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+ "input_per_million": 1.75,
+ "output_per_million": 14.0,
+ "cache_read_input_per_million": 0.175
+ }
+ }
+ },
+ "metadata": {
+ "description": "GPT-5.3 Chat is an update to ChatGPT's most-used model that makes everyday conversations smoother, more useful, and more directly helpful. It delivers more accurate answers with better contextualization and significantly...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": 16384,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_completion_tokens",
+ "max_tokens",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ]
+ }
+ },
{
"id": "openai/gpt-5.3-codex",
"name": "GPT-5.3-Codex",
"provider": "openrouter",
"family": "gpt-codex",
- "created_at": "2026-02-24 00:00:00 +0530",
+ "created_at": "2026-02-24 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2025-08-31",
@@ -19661,18 +46850,50 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 1.75,
"output_per_million": 14,
- "cached_input_per_million": 0.175
+ "cache_read_input_per_million": 0.175
}
}
},
"metadata": {
+ "description": "GPT-5.3-Codex is OpenAI’s most advanced agentic coding model, combining the frontier software engineering performance of GPT-5.2-Codex with the broader reasoning and professional knowledge capabilities of GPT-5.2. It achieves state-of-the-art results...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 400000,
+ "max_completion_tokens": 128000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_completion_tokens",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -19696,7 +46917,7 @@
"name": "GPT-5.4",
"provider": "openrouter",
"family": "gpt",
- "created_at": "2026-03-05 00:00:00 +0530",
+ "created_at": "2026-03-05 00:00:00 UTC",
"context_window": 1050000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2025-08-31",
@@ -19714,18 +46935,50 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 2.5,
"output_per_million": 15,
- "cached_input_per_million": 0.25
+ "cache_read_input_per_million": 0.25
}
}
},
"metadata": {
+ "description": "GPT-5.4 is OpenAI’s latest frontier model, unifying the Codex and GPT lines into a single system. It features a 1M+ token context window (922K input, 128K output) with support for...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1050000,
+ "max_completion_tokens": 128000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_completion_tokens",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -19750,12 +47003,83 @@
"knowledge": "2025-08-31"
}
},
+ {
+ "id": "openai/gpt-5.4-image-2",
+ "name": "OpenAI: GPT-5.4 Image 2",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2026-04-21 18:52:08 UTC",
+ "context_window": 272000,
+ "max_output_tokens": 128000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "image",
+ "text",
+ "file"
+ ],
+ "output": [
+ "image",
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 8.0,
+ "output_per_million": 15.0,
+ "cache_read_input_per_million": 2.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "[GPT-5.4](https://openrouter.ai/openai/gpt-5.4) Image 2 combines OpenAI's GPT-5.4 model with state-of-the-art image generation capabilities from GPT Image 2. It enables rich multimodal workflows, allowing users to seamlessly move between reasoning, coding, and...",
+ "architecture": {
+ "modality": "text+image+file->text+image",
+ "input_modalities": [
+ "image",
+ "text",
+ "file"
+ ],
+ "output_modalities": [
+ "image",
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 272000,
+ "max_completion_tokens": 128000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "top_logprobs"
+ ]
+ }
+ },
{
"id": "openai/gpt-5.4-mini",
"name": "GPT-5.4 Mini",
"provider": "openrouter",
"family": "gpt-mini",
- "created_at": "2026-03-17 00:00:00 +0530",
+ "created_at": "2026-03-17 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2025-08-31",
@@ -19773,18 +47097,50 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
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"standard": {
- "input_per_million": 0.00000075,
- "output_per_million": 0.0000045,
- "cached_input_per_million": 0.000000075
+ "input_per_million": 0.75,
+ "output_per_million": 4.5,
+ "cache_read_input_per_million": 0.075
}
}
},
"metadata": {
+ "description": "GPT-5.4 mini brings the core capabilities of GPT-5.4 to a faster, more efficient model optimized for high-throughput workloads. It supports text and image inputs with strong performance across reasoning, coding,...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "file",
+ "image",
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 400000,
+ "max_completion_tokens": 128000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_completion_tokens",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -19792,9 +47148,9 @@
"temperature": true,
"last_updated": "2026-03-17",
"cost": {
- "input": 0.00000075,
- "output": 0.0000045,
- "cache_read": 0.000000075
+ "input": 0.75,
+ "output": 4.5,
+ "cache_read": 0.075
},
"limit": {
"context": 400000,
@@ -19808,7 +47164,7 @@
"name": "GPT-5.4 Nano",
"provider": "openrouter",
"family": "gpt-nano",
- "created_at": "2026-03-17 00:00:00 +0530",
+ "created_at": "2026-03-17 00:00:00 UTC",
"context_window": 400000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2025-08-31",
@@ -19825,18 +47181,50 @@
"capabilities": [
"function_calling",
"structured_output",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
- "input_per_million": 0.0000002,
- "output_per_million": 0.00000125,
- "cached_input_per_million": 0.00000002
+ "input_per_million": 0.2,
+ "output_per_million": 1.25,
+ "cache_read_input_per_million": 0.02
}
}
},
"metadata": {
+ "description": "GPT-5.4 nano is the most lightweight and cost-efficient variant of the GPT-5.4 family, optimized for speed-critical and high-volume tasks. It supports text and image inputs and is designed for low-latency...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "file",
+ "image",
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 400000,
+ "max_completion_tokens": 128000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_completion_tokens",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -19844,9 +47232,9 @@
"temperature": true,
"last_updated": "2026-03-17",
"cost": {
- "input": 0.0000002,
- "output": 0.00000125,
- "cache_read": 0.00000002
+ "input": 0.2,
+ "output": 1.25,
+ "cache_read": 0.02
},
"limit": {
"context": 400000,
@@ -19860,7 +47248,7 @@
"name": "GPT-5.4 Pro",
"provider": "openrouter",
"family": "gpt-pro",
- "created_at": "2026-03-05 00:00:00 +0530",
+ "created_at": "2026-03-05 00:00:00 UTC",
"context_window": 1050000,
"max_output_tokens": 128000,
"knowledge_cutoff": "2025-08-31",
@@ -19877,18 +47265,51 @@
"capabilities": [
"function_calling",
"reasoning",
- "vision"
+ "vision",
+ "streaming",
+ "structured_output"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 30,
"output_per_million": 180,
- "cached_input_per_million": 30
+ "cache_read_input_per_million": 30
}
}
},
"metadata": {
+ "description": "GPT-5.4 Pro is OpenAI's most advanced model, building on GPT-5.4's unified architecture with enhanced reasoning capabilities for complex, high-stakes tasks. It features a 1M+ token context window (922K input, 128K...",
+ "architecture": {
+ "modality": "text+image+file->text",
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@@ -19908,12 +47329,402 @@
"knowledge": "2025-08-31"
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+ "name": "OpenAI: GPT Chat Latest",
+ "provider": "openrouter",
+ "family": "openai",
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+ "cache_read_input_per_million": 0.5
+ }
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+ "metadata": {
+ "description": "GPT Chat Latest points to OpenAI's stable API alias `chat-latest` that always resolves to the latest Instant chat model used in ChatGPT. As OpenAI rolls out new Instant model updates...",
+ "architecture": {
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+ "structured_outputs",
+ "tool_choice",
+ "tools",
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+ }
+ },
{
"id": "openai/gpt-oss-120b",
"name": "GPT OSS 120B",
"provider": "openrouter",
"family": "gpt-oss",
- "created_at": "2025-08-05 00:00:00 +0530",
+ "created_at": "2025-08-05 00:00:00 UTC",
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"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -19928,7 +47739,9 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -19939,6 +47752,45 @@
}
},
"metadata": {
+ "description": "gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized...",
+ "architecture": {
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+ "input_modalities": [
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+ "output_modalities": [
+ "text"
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+ "tokenizer": "GPT",
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+ "supported_parameters": [
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+ "logprobs",
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+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -19960,7 +47812,7 @@
"name": "GPT OSS 120B (exacto)",
"provider": "openrouter",
"family": "gpt-oss",
- "created_at": "2025-08-05 00:00:00 +0530",
+ "created_at": "2025-08-05 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -20007,7 +47859,7 @@
"name": "gpt-oss-120b (free)",
"provider": "openrouter",
"family": "gpt-oss",
- "created_at": "2025-08-05 00:00:00 +0530",
+ "created_at": "2025-08-05 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -20021,10 +47873,39 @@
},
"capabilities": [
"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {},
"metadata": {
+ "description": "gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized...",
+ "architecture": {
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+ "input_modalities": [
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+ "output_modalities": [
+ "text"
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+ "tokenizer": "GPT",
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+ "supported_parameters": [
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+ "reasoning",
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+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -20046,7 +47927,7 @@
"name": "GPT OSS 20B",
"provider": "openrouter",
"family": "gpt-oss",
- "created_at": "2025-08-05 00:00:00 +0530",
+ "created_at": "2025-08-05 00:00:00 UTC",
"context_window": 131072,
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"knowledge_cutoff": null,
@@ -20061,7 +47942,9 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -20072,6 +47955,45 @@
}
},
"metadata": {
+ "description": "gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for...",
+ "architecture": {
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+ "input_modalities": [
+ "text"
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+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
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+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
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+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -20093,7 +48015,7 @@
"name": "gpt-oss-20b (free)",
"provider": "openrouter",
"family": "gpt-oss",
- "created_at": "2025-08-05 00:00:00 +0530",
+ "created_at": "2025-08-05 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -20107,10 +48029,39 @@
},
"capabilities": [
"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {},
"metadata": {
+ "description": "gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for...",
+ "architecture": {
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+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
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+ "supported_parameters": [
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+ "reasoning",
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+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -20132,7 +48083,7 @@
"name": "GPT OSS Safeguard 20B",
"provider": "openrouter",
"family": "gpt-oss",
- "created_at": "2025-10-29 00:00:00 +0530",
+ "created_at": "2025-10-29 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -20146,7 +48097,9 @@
},
"capabilities": [
"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "structured_output"
],
"pricing": {
"text_tokens": {
@@ -20157,6 +48110,36 @@
}
},
"metadata": {
+ "description": "gpt-oss-safeguard-20b is a safety reasoning model from OpenAI built upon gpt-oss-20b. This open-weight, 21B-parameter Mixture-of-Experts (MoE) model offers lower latency for safety tasks like content classification, LLM filtering, and trust...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
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+ "max_completion_tokens": 65536,
+ "is_moderated": false
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+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -20173,12 +48156,473 @@
}
}
},
+ {
+ "id": "openai/o1",
+ "name": "OpenAI: o1",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2024-12-17 18:26:39 UTC",
+ "context_window": 200000,
+ "max_output_tokens": 100000,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "text",
+ "image",
+ "file"
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+ "output": [
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+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
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+ "output_per_million": 60.0,
+ "cache_read_input_per_million": 7.5
+ }
+ }
+ },
+ "metadata": {
+ "description": "The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
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+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
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+ "tool_choice",
+ "tools"
+ ]
+ }
+ },
+ {
+ "id": "openai/o1-pro",
+ "name": "OpenAI: o1-pro",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2025-03-19 22:26:51 UTC",
+ "context_window": 200000,
+ "max_output_tokens": 100000,
+ "knowledge_cutoff": null,
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+ "image",
+ "file"
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+ "standard": {
+ "input_per_million": 150.0,
+ "output_per_million": 600.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "The o1 series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o1-pro model uses more compute to think harder and provide...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
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+ "supported_parameters": [
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+ "max_tokens",
+ "reasoning",
+ "response_format",
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+ ]
+ }
+ },
+ {
+ "id": "openai/o3",
+ "name": "OpenAI: o3",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2025-04-16 17:10:57 UTC",
+ "context_window": 200000,
+ "max_output_tokens": 100000,
+ "knowledge_cutoff": null,
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+ "cache_read_input_per_million": 0.5
+ }
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+ },
+ "metadata": {
+ "description": "o3 is a well-rounded and powerful model across domains. It sets a new standard for math, science, coding, and visual reasoning tasks. It also excels at technical writing and instruction-following....",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "file"
+ ],
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+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ]
+ }
+ },
+ {
+ "id": "openai/o3-deep-research",
+ "name": "OpenAI: o3 Deep Research",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2025-10-10 20:54:21 UTC",
+ "context_window": 200000,
+ "max_output_tokens": 100000,
+ "knowledge_cutoff": null,
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+ "image",
+ "text",
+ "file"
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+ "output_per_million": 40.0,
+ "cache_read_input_per_million": 2.5
+ }
+ }
+ },
+ "metadata": {
+ "description": "o3-deep-research is OpenAI's advanced model for deep research, designed to tackle complex, multi-step research tasks.\n\nNote: This model always uses the 'web_search' tool which adds additional cost.",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "file"
+ ],
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+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "openai/o3-mini",
+ "name": "OpenAI: o3 Mini",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2025-01-31 19:28:41 UTC",
+ "context_window": 200000,
+ "max_output_tokens": 100000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
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+ "file"
+ ],
+ "output": [
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+ "output_per_million": 4.4,
+ "cache_read_input_per_million": 0.55
+ }
+ }
+ },
+ "metadata": {
+ "description": "OpenAI o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding. This model supports the `reasoning_effort` parameter, which can be set to...",
+ "architecture": {
+ "modality": "text+file->text",
+ "input_modalities": [
+ "text",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
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+ "max_completion_tokens": 100000,
+ "is_moderated": true
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+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ]
+ }
+ },
+ {
+ "id": "openai/o3-mini-high",
+ "name": "OpenAI: o3 Mini High",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2025-02-12 15:03:31 UTC",
+ "context_window": 200000,
+ "max_output_tokens": 100000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "file"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
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+ "standard": {
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+ "output_per_million": 4.4,
+ "cache_read_input_per_million": 0.55
+ }
+ }
+ },
+ "metadata": {
+ "description": "OpenAI o3-mini-high is the same model as [o3-mini](/openai/o3-mini) with reasoning_effort set to high. o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and...",
+ "architecture": {
+ "modality": "text+file->text",
+ "input_modalities": [
+ "text",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 200000,
+ "max_completion_tokens": 100000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ]
+ }
+ },
+ {
+ "id": "openai/o3-pro",
+ "name": "OpenAI: o3 Pro",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2025-06-10 23:32:32 UTC",
+ "context_window": 200000,
+ "max_output_tokens": 100000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "file",
+ "image"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 20.0,
+ "output_per_million": 80.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "The o-series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o3-pro model uses more compute to think harder and provide consistently...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "file",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 200000,
+ "max_completion_tokens": 100000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ]
+ }
+ },
{
"id": "openai/o4-mini",
"name": "o4 Mini",
"provider": "openrouter",
"family": "o-mini",
- "created_at": "2025-04-16 00:00:00 +0530",
+ "created_at": "2025-04-16 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 100000,
"knowledge_cutoff": null,
@@ -20195,18 +48639,49 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 1.1,
"output_per_million": 4.4,
- "cached_input_per_million": 0.28
+ "cache_read_input_per_million": 0.28
}
}
},
"metadata": {
+ "description": "OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities. It supports tool use and demonstrates competitive reasoning...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 200000,
+ "max_completion_tokens": 100000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -20225,12 +48700,273 @@
"knowledge": "2024-06"
}
},
+ {
+ "id": "openai/o4-mini-deep-research",
+ "name": "OpenAI: o4 Mini Deep Research",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2025-10-10 20:54:02 UTC",
+ "context_window": 200000,
+ "max_output_tokens": 100000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "file",
+ "image",
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 2.0,
+ "output_per_million": 8.0,
+ "cache_read_input_per_million": 0.5
+ }
+ }
+ },
+ "metadata": {
+ "description": "o4-mini-deep-research is OpenAI's faster, more affordable deep research model—ideal for tackling complex, multi-step research tasks.\n\nNote: This model always uses the 'web_search' tool which adds additional cost.",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "file",
+ "image",
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 200000,
+ "max_completion_tokens": 100000,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "openai/o4-mini-high",
+ "name": "OpenAI: o4 Mini High",
+ "provider": "openrouter",
+ "family": "openai",
+ "created_at": "2025-04-16 17:23:32 UTC",
+ "context_window": 200000,
+ "max_output_tokens": 100000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "image",
+ "text",
+ "file"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 1.1,
+ "output_per_million": 4.4,
+ "cache_read_input_per_million": 0.275
+ }
+ }
+ },
+ "metadata": {
+ "description": "OpenAI o4-mini-high is the same model as [o4-mini](/openai/o4-mini) with reasoning_effort set to high. OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "GPT",
+ "instruct_type": null
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+ "max_completion_tokens": 100000,
+ "is_moderated": true
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+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "tool_choice",
+ "tools"
+ ]
+ }
+ },
+ {
+ "id": "openrouter/auto",
+ "name": "Auto Router",
+ "provider": "openrouter",
+ "family": "openrouter",
+ "created_at": "2023-11-08 00:00:00 UTC",
+ "context_window": 2000000,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "audio",
+ "file",
+ "video"
+ ],
+ "output": [
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+ "image"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {},
+ "metadata": {
+ "description": "\"Your prompt will be processed by a meta-model and routed to one of dozens of models (see below), optimizing for the best possible output. To see which model was used,...",
+ "architecture": {
+ "modality": "text+image+file+audio+video->text+image",
+ "input_modalities": [
+ "text",
+ "image",
+ "audio",
+ "file",
+ "video"
+ ],
+ "output_modalities": [
+ "text",
+ "image"
+ ],
+ "tokenizer": "Router",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": null,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_completion_tokens",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p",
+ "web_search_options"
+ ]
+ }
+ },
+ {
+ "id": "openrouter/bodybuilder",
+ "name": "Body Builder (beta)",
+ "provider": "openrouter",
+ "family": "openrouter",
+ "created_at": "2025-12-05 03:00:53 UTC",
+ "context_window": 128000,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {},
+ "metadata": {
+ "description": "Transform your natural language requests into structured OpenRouter API request objects. Describe what you want to accomplish with AI models, and Body Builder will construct the appropriate API calls. Example:...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Router",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": null,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": []
+ }
+ },
{
"id": "openrouter/elephant-alpha",
"name": "Elephant (free)",
"provider": "openrouter",
"family": "elephant",
- "created_at": "2026-04-13 00:00:00 +0530",
+ "created_at": "2026-04-13 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -20269,8 +49005,8 @@
"id": "openrouter/free",
"name": "Free Models Router",
"provider": "openrouter",
- "family": null,
- "created_at": "2026-02-01 00:00:00 +0530",
+ "family": "openrouter",
+ "created_at": "2026-02-01 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 8000,
"knowledge_cutoff": null,
@@ -20287,10 +49023,48 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {},
"metadata": {
+ "description": "The simplest way to get free inference. openrouter/free is a router that selects free models at random from the models available on OpenRouter. The router smartly filters for models that...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Router",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": null,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -20308,12 +49082,592 @@
}
}
},
+ {
+ "id": "openrouter/owl-alpha",
+ "name": "Owl Alpha",
+ "provider": "openrouter",
+ "family": "openrouter",
+ "created_at": "2026-04-28 00:00:00 UTC",
+ "context_window": 1048756,
+ "max_output_tokens": 262144,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "text"
+ ],
+ "output": [
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+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
+ ],
+ "pricing": {},
+ "metadata": {
+ "description": "Owl Alpha is a high-performance foundation model designed for agentic workloads. Natively supports tool use, and long-context tasks, with strong performance in code generation, automated workflows, and complex instruction execution....",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1048756,
+ "max_completion_tokens": 262144,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
+ "source": "models.dev",
+ "provider_id": "openrouter",
+ "open_weights": false,
+ "attachment": false,
+ "temperature": true,
+ "last_updated": "2026-04-30",
+ "status": "alpha",
+ "cost": {
+ "input": 0,
+ "output": 0
+ },
+ "limit": {
+ "context": 1048756,
+ "output": 262144
+ }
+ }
+ },
+ {
+ "id": "openrouter/pareto-code",
+ "name": "Pareto Code Router",
+ "provider": "openrouter",
+ "family": "openrouter",
+ "created_at": "2026-04-21 00:00:00 UTC",
+ "context_window": 200000,
+ "max_output_tokens": 200000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "reasoning",
+ "streaming"
+ ],
+ "pricing": {},
+ "metadata": {
+ "description": "The Pareto Router is a way to have OpenRouter always pick a strong coding model for your needs without committing to a specific one. You express a single `min_coding_score` preference...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Router",
+ "instruct_type": null
+ },
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+ },
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+ "supported_parameters": [],
+ "source": "models.dev",
+ "provider_id": "openrouter",
+ "open_weights": false,
+ "attachment": true,
+ "temperature": true,
+ "last_updated": "2026-04-21",
+ "limit": {
+ "context": 200000,
+ "output": 200000
+ }
+ }
+ },
+ {
+ "id": "perplexity/sonar",
+ "name": "Perplexity: Sonar",
+ "provider": "openrouter",
+ "family": "perplexity",
+ "created_at": "2025-01-27 21:36:48 UTC",
+ "context_window": 127072,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "text",
+ "image"
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+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 1.0,
+ "output_per_million": 1.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "Sonar is lightweight, affordable, fast, and simple to use — now featuring citations and the ability to customize sources. It is designed for companies seeking to integrate lightweight question-and-answer features...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
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+ "tokenizer": "Other",
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+ },
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+ "max_tokens",
+ "presence_penalty",
+ "temperature",
+ "top_k",
+ "top_p",
+ "web_search_options"
+ ]
+ }
+ },
+ {
+ "id": "perplexity/sonar-deep-research",
+ "name": "Perplexity: Sonar Deep Research",
+ "provider": "openrouter",
+ "family": "perplexity",
+ "created_at": "2025-03-07 01:34:06 UTC",
+ "context_window": 128000,
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+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 2.0,
+ "output_per_million": 8.0,
+ "reasoning_output_per_million": 3.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "Sonar Deep Research is a research-focused model designed for multi-step retrieval, synthesis, and reasoning across complex topics. It autonomously searches, reads, and evaluates sources, refining its approach as it gathers...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": "deepseek-r1"
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "temperature",
+ "top_k",
+ "top_p",
+ "web_search_options"
+ ]
+ }
+ },
+ {
+ "id": "perplexity/sonar-pro",
+ "name": "Perplexity: Sonar Pro",
+ "provider": "openrouter",
+ "family": "perplexity",
+ "created_at": "2025-03-07 01:53:43 UTC",
+ "context_window": 200000,
+ "max_output_tokens": 8000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 3.0,
+ "output_per_million": 15.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "Note: Sonar Pro pricing includes Perplexity search pricing. See [details here](https://docs.perplexity.ai/guides/pricing#detailed-pricing-breakdown-for-sonar-reasoning-pro-and-sonar-pro) For enterprises seeking more advanced capabilities, the Sonar Pro API can handle in-depth, multi-step queries with added extensibility, like...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
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+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 200000,
+ "max_completion_tokens": 8000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "presence_penalty",
+ "temperature",
+ "top_k",
+ "top_p",
+ "web_search_options"
+ ]
+ }
+ },
+ {
+ "id": "perplexity/sonar-pro-search",
+ "name": "Perplexity: Sonar Pro Search",
+ "provider": "openrouter",
+ "family": "perplexity",
+ "created_at": "2025-10-30 19:59:26 UTC",
+ "context_window": 200000,
+ "max_output_tokens": 8000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 3.0,
+ "output_per_million": 15.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "Exclusively available on the OpenRouter API, Sonar Pro's new Pro Search mode is Perplexity's most advanced agentic search system. It is designed for deeper reasoning and analysis. Pricing is based...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 200000,
+ "max_completion_tokens": 8000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "structured_outputs",
+ "temperature",
+ "top_k",
+ "top_p",
+ "web_search_options"
+ ]
+ }
+ },
+ {
+ "id": "perplexity/sonar-reasoning-pro",
+ "name": "Perplexity: Sonar Reasoning Pro",
+ "provider": "openrouter",
+ "family": "perplexity",
+ "created_at": "2025-03-07 02:08:28 UTC",
+ "context_window": 128000,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
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+ ]
+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 2.0,
+ "output_per_million": 8.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "Note: Sonar Pro pricing includes Perplexity search pricing. See [details here](https://docs.perplexity.ai/guides/pricing#detailed-pricing-breakdown-for-sonar-reasoning-pro-and-sonar-pro) Sonar Reasoning Pro is a premier reasoning model powered by DeepSeek R1 with Chain of Thought (CoT). Designed for...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": "deepseek-r1"
+ },
+ "top_provider": {
+ "context_length": 128000,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "temperature",
+ "top_k",
+ "top_p",
+ "web_search_options"
+ ]
+ }
+ },
+ {
+ "id": "poolside/laguna-m.1:free",
+ "name": "Laguna M.1",
+ "provider": "openrouter",
+ "family": "poolside",
+ "created_at": "2026-04-28 00:00:00 UTC",
+ "context_window": 131072,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
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+ ],
+ "output": [
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+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "reasoning",
+ "streaming"
+ ],
+ "pricing": {},
+ "metadata": {
+ "description": "Laguna M.1 is the flagship coding agent model from [Poolside](https://poolside.ai), optimized for complex software engineering tasks. Designed for agentic coding workflows, it supports tool calling and reasoning, with a 128K...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
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+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "temperature",
+ "tool_choice",
+ "tools"
+ ],
+ "source": "models.dev",
+ "provider_id": "openrouter",
+ "open_weights": false,
+ "attachment": false,
+ "temperature": true,
+ "last_updated": "2026-04-28",
+ "interleaved": {
+ "field": "reasoning_content"
+ },
+ "cost": {
+ "input": 0,
+ "output": 0,
+ "cache_read": 0,
+ "cache_write": 0
+ },
+ "limit": {
+ "context": 131072,
+ "output": 8192
+ }
+ }
+ },
+ {
+ "id": "poolside/laguna-xs.2:free",
+ "name": "Laguna XS.2",
+ "provider": "openrouter",
+ "family": "poolside",
+ "created_at": "2026-04-28 00:00:00 UTC",
+ "context_window": 131072,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "reasoning",
+ "streaming"
+ ],
+ "pricing": {},
+ "metadata": {
+ "description": "Laguna XS.2 is the second-generation model in the XS size class from [Poolside](https://poolside.ai), their efficient coding agent series. It combines tool calling and reasoning capabilities with a compact footprint, offering...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 8192,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "temperature",
+ "tool_choice",
+ "tools"
+ ],
+ "source": "models.dev",
+ "provider_id": "openrouter",
+ "open_weights": true,
+ "attachment": false,
+ "temperature": true,
+ "last_updated": "2026-04-28",
+ "interleaved": {
+ "field": "reasoning_content"
+ },
+ "cost": {
+ "input": 0,
+ "output": 0,
+ "cache_read": 0,
+ "cache_write": 0
+ },
+ "limit": {
+ "context": 131072,
+ "output": 8192
+ }
+ }
+ },
{
"id": "prime-intellect/intellect-3",
"name": "Intellect 3",
"provider": "openrouter",
"family": "glm",
- "created_at": "2025-01-15 00:00:00 +0530",
+ "created_at": "2025-01-15 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -20328,7 +49682,8 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -20339,6 +49694,39 @@
}
},
"metadata": {
+ "description": "INTELLECT-3 is a 106B-parameter Mixture-of-Experts model (12B active) post-trained from GLM-4.5-Air-Base using supervised fine-tuning (SFT) followed by large-scale reinforcement learning (RL). It offers state-of-the-art performance for its size across math,...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 131072,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -20356,12 +49744,149 @@
"knowledge": "2024-10"
}
},
+ {
+ "id": "qwen/qwen-2.5-72b-instruct",
+ "name": "Qwen2.5 72B Instruct",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2024-09-19 00:00:00 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.36,
+ "output_per_million": 0.39999999999999997
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen2.5 72B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabilities in coding and...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen",
+ "instruct_type": "chatml"
+ },
+ "top_provider": {
+ "context_length": 32768,
+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "qwen/qwen-2.5-7b-instruct",
+ "name": "Qwen: Qwen2.5 7B Instruct",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2024-10-16 00:00:00 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 32768,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.04,
+ "output_per_million": 0.09999999999999999
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen2.5 7B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabilities in coding and...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen",
+ "instruct_type": "chatml"
+ },
+ "top_provider": {
+ "context_length": 32768,
+ "max_completion_tokens": 32768,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
{
"id": "qwen/qwen-2.5-coder-32b-instruct",
"name": "Qwen2.5 Coder 32B Instruct",
"provider": "openrouter",
"family": "qwen",
- "created_at": "2024-11-11 00:00:00 +0530",
+ "created_at": "2024-11-11 00:00:00 UTC",
"context_window": 32768,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -20374,10 +49899,46 @@
]
},
"capabilities": [
- "structured_output"
+ "structured_output",
+ "streaming"
],
- "pricing": {},
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.66,
+ "output_per_million": 1.0
+ }
+ }
+ },
"metadata": {
+ "description": "Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen). Qwen2.5-Coder brings the following improvements upon CodeQwen1.5: - Significantly improvements in **code generation**, **code reasoning**...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen",
+ "instruct_type": "chatml"
+ },
+ "top_provider": {
+ "context_length": 32768,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "presence_penalty",
+ "repetition_penalty",
+ "seed",
+ "temperature",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -20395,12 +49956,498 @@
"knowledge": "2024-10"
}
},
+ {
+ "id": "qwen/qwen-3.6-27b",
+ "name": "Qwen3.6 27B",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2026-04-22 00:00:00 UTC",
+ "context_window": 262144,
+ "max_output_tokens": 81920,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "video"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "vision"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.195,
+ "output_per_million": 1.56
+ }
+ }
+ },
+ "metadata": {
+ "source": "models.dev",
+ "provider_id": "openrouter",
+ "open_weights": true,
+ "attachment": true,
+ "temperature": true,
+ "last_updated": "2026-04-22",
+ "cost": {
+ "input": 0.195,
+ "output": 1.56
+ },
+ "limit": {
+ "context": 262144,
+ "output": 81920
+ },
+ "knowledge": "2025-04"
+ }
+ },
+ {
+ "id": "qwen/qwen-max",
+ "name": "Qwen: Qwen-Max ",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2025-02-01 09:31:29 UTC",
+ "context_window": 32768,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 1.04,
+ "output_per_million": 4.16,
+ "cache_read_input_per_million": 0.20800000000000002
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen-Max, based on Qwen2.5, provides the best inference performance among [Qwen models](/qwen), especially for complex multi-step tasks. It's a large-scale MoE model that has been pretrained on over 20 trillion...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 32768,
+ "max_completion_tokens": 8192,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "qwen/qwen-plus",
+ "name": "Qwen: Qwen-Plus",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2025-02-01 11:37:20 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 32768,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.26,
+ "output_per_million": 0.78,
+ "cache_read_input_per_million": 0.052000000000000005
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen-Plus, based on the Qwen2.5 foundation model, is a 131K context model with a balanced performance, speed, and cost combination.",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1000000,
+ "max_completion_tokens": 32768,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "qwen/qwen-plus-2025-07-28",
+ "name": "Qwen: Qwen Plus 0728",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2025-09-08 16:06:39 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 32768,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.26,
+ "output_per_million": 0.78
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen Plus 0728, based on the Qwen3 foundation model, is a 1 million context hybrid reasoning model with a balanced performance, speed, and cost combination.",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1000000,
+ "max_completion_tokens": 32768,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "qwen/qwen-plus-2025-07-28:thinking",
+ "name": "Qwen: Qwen Plus 0728 (thinking)",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2025-09-08 16:06:39 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 32768,
+ "knowledge_cutoff": null,
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+ "output_per_million": 0.78
+ }
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+ "metadata": {
+ "description": "Qwen Plus 0728, based on the Qwen3 foundation model, is a 1 million context hybrid reasoning model with a balanced performance, speed, and cost combination.",
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+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "qwen/qwen-turbo",
+ "name": "Qwen: Qwen-Turbo",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2025-02-01 11:56:14 UTC",
+ "context_window": 131072,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
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+ "output_per_million": 0.13,
+ "cache_read_input_per_million": 0.006500000000000001
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen-Turbo, based on Qwen2.5, is a 1M context model that provides fast speed and low cost, suitable for simple tasks.",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
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+ "output_modalities": [
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+ "tokenizer": "Qwen",
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+ }
+ },
+ {
+ "id": "qwen/qwen-vl-max",
+ "name": "Qwen: Qwen VL Max",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2025-02-01 18:25:04 UTC",
+ "context_window": 131072,
+ "max_output_tokens": 32768,
+ "knowledge_cutoff": null,
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+ "image"
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+ "standard": {
+ "input_per_million": 0.52,
+ "output_per_million": 2.08
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen VL Max is a visual understanding model with 7500 tokens context length. It excels in delivering optimal performance for a broader spectrum of complex tasks.\n",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
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+ "tokenizer": "Qwen",
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+ "supported_parameters": [
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+ "response_format",
+ "seed",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "qwen/qwen-vl-plus",
+ "name": "Qwen: Qwen VL Plus",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2025-02-05 04:54:15 UTC",
+ "context_window": 131072,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
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+ "image"
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+ "structured_output"
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+ "pricing": {
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+ "output_per_million": 0.40950000000000003,
+ "cache_read_input_per_million": 0.027299999999999998
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen's Enhanced Large Visual Language Model. Significantly upgraded for detailed recognition capabilities and text recognition abilities, supporting ultra-high pixel resolutions up to millions of pixels and extreme aspect ratios for...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 8192,
+ "is_moderated": false
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+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "temperature",
+ "top_p"
+ ]
+ }
+ },
{
"id": "qwen/qwen2.5-vl-72b-instruct",
"name": "Qwen2.5 VL 72B Instruct",
"provider": "openrouter",
"family": "qwen",
- "created_at": "2025-02-01 00:00:00 +0530",
+ "created_at": "2025-02-01 00:00:00 UTC",
"context_window": 32768,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -20415,10 +50462,52 @@
},
"capabilities": [
"structured_output",
- "vision"
+ "vision",
+ "streaming",
+ "predicted_outputs"
],
- "pricing": {},
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.25,
+ "output_per_million": 0.75
+ }
+ }
+ },
"metadata": {
+ "description": "Qwen2.5-VL is proficient in recognizing common objects such as flowers, birds, fish, and insects. It is also highly capable of analyzing texts, charts, icons, graphics, and layouts within images.",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen",
+ "instruct_type": null
+ },
+ "top_provider": {
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+ "max_completion_tokens": null,
+ "is_moderated": false
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+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -20436,12 +50525,148 @@
"knowledge": "2024-10"
}
},
+ {
+ "id": "qwen/qwen3-14b",
+ "name": "Qwen: Qwen3 14B",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2025-04-28 21:41:18 UTC",
+ "context_window": 40960,
+ "max_output_tokens": 40960,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.06,
+ "output_per_million": 0.24
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen3-14B is a dense 14.8B parameter causal language model from the Qwen3 series, designed for both complex reasoning and efficient dialogue. It supports seamless switching between a \"thinking\" mode for...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": "qwen3"
+ },
+ "top_provider": {
+ "context_length": 40960,
+ "max_completion_tokens": 40960,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "qwen/qwen3-235b-a22b",
+ "name": "Qwen: Qwen3 235B A22B",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2025-04-28 21:29:17 UTC",
+ "context_window": 131072,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "output": [
+ "text"
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+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.45499999999999996,
+ "output_per_million": 1.8199999999999998
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen3-235B-A22B is a 235B parameter mixture-of-experts (MoE) model developed by Qwen, activating 22B parameters per forward pass. It supports seamless switching between a \"thinking\" mode for complex reasoning, math, and...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": "qwen3"
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 8192,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "response_format",
+ "seed",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
{
"id": "qwen/qwen3-235b-a22b-07-25",
"name": "Qwen3 235B A22B Instruct 2507",
"provider": "openrouter",
"family": "qwen",
- "created_at": "2025-04-28 00:00:00 +0530",
+ "created_at": "2025-04-28 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -20483,12 +50708,83 @@
"knowledge": "2025-04"
}
},
+ {
+ "id": "qwen/qwen3-235b-a22b-2507",
+ "name": "Qwen: Qwen3 235B A22B Instruct 2507",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2025-07-21 17:39:15 UTC",
+ "context_window": 262144,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.071,
+ "output_per_million": 0.09999999999999999
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following,...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
{
"id": "qwen/qwen3-235b-a22b-thinking-2507",
"name": "Qwen3 235B A22B Thinking 2507",
"provider": "openrouter",
"family": "qwen",
- "created_at": "2025-07-25 00:00:00 +0530",
+ "created_at": "2025-07-25 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 81920,
"knowledge_cutoff": null,
@@ -20503,7 +50799,9 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -20514,6 +50812,43 @@
}
},
"metadata": {
+ "description": "Qwen3-235B-A22B-Thinking-2507 is a high-performance, open-weight Mixture-of-Experts (MoE) language model optimized for complex reasoning tasks. It activates 22B of its 235B parameters per forward pass and natively supports up to 262,144...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": "qwen3"
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -20531,12 +50866,85 @@
"knowledge": "2025-04"
}
},
+ {
+ "id": "qwen/qwen3-30b-a3b",
+ "name": "Qwen: Qwen3 30B A3B",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2025-04-28 22:16:44 UTC",
+ "context_window": 40960,
+ "max_output_tokens": 20000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.09,
+ "output_per_million": 0.44999999999999996
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen3, the latest generation in the Qwen large language model series, features both dense and mixture-of-experts (MoE) architectures to excel in reasoning, multilingual support, and advanced agent tasks. Its unique...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": "qwen3"
+ },
+ "top_provider": {
+ "context_length": 40960,
+ "max_completion_tokens": 20000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
{
"id": "qwen/qwen3-30b-a3b-instruct-2507",
"name": "Qwen3 30B A3B Instruct 2507",
"provider": "openrouter",
"family": "qwen",
- "created_at": "2025-07-29 00:00:00 +0530",
+ "created_at": "2025-07-29 00:00:00 UTC",
"context_window": 262000,
"max_output_tokens": 262000,
"knowledge_cutoff": null,
@@ -20550,7 +50958,9 @@
},
"capabilities": [
"function_calling",
- "structured_output"
+ "structured_output",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -20561,6 +50971,41 @@
}
},
"metadata": {
+ "description": "Qwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference. It operates in non-thinking mode and is designed for high-quality instruction following, multilingual understanding, and...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": 262144,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -20583,7 +51028,7 @@
"name": "Qwen3 30B A3B Thinking 2507",
"provider": "openrouter",
"family": "qwen",
- "created_at": "2025-07-29 00:00:00 +0530",
+ "created_at": "2025-07-29 00:00:00 UTC",
"context_window": 262000,
"max_output_tokens": 262000,
"knowledge_cutoff": null,
@@ -20598,7 +51043,9 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -20609,6 +51056,43 @@
}
},
"metadata": {
+ "description": "Qwen3-30B-A3B-Thinking-2507 is a 30B parameter Mixture-of-Experts reasoning model optimized for complex tasks requiring extended multi-step thinking. The model is designed specifically for “thinking mode,” where internal reasoning traces are separated...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 131072,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -20626,12 +51110,156 @@
"knowledge": "2025-04"
}
},
+ {
+ "id": "qwen/qwen3-32b",
+ "name": "Qwen: Qwen3 32B",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2025-04-28 21:32:25 UTC",
+ "context_window": 40960,
+ "max_output_tokens": 40960,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.08,
+ "output_per_million": 0.24,
+ "cache_read_input_per_million": 0.04
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen3-32B is a dense 32.8B parameter causal language model from the Qwen3 series, optimized for both complex reasoning and efficient dialogue. It supports seamless switching between a \"thinking\" mode for...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": "qwen3"
+ },
+ "top_provider": {
+ "context_length": 40960,
+ "max_completion_tokens": 40960,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "qwen/qwen3-8b",
+ "name": "Qwen: Qwen3 8B",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2025-04-28 21:43:52 UTC",
+ "context_window": 40960,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.049999999999999996,
+ "output_per_million": 0.39999999999999997,
+ "cache_read_input_per_million": 0.049999999999999996
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen3-8B is a dense 8.2B parameter causal language model from the Qwen3 series, designed for both reasoning-heavy tasks and efficient dialogue. It supports seamless switching between \"thinking\" mode for math,...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": "qwen3"
+ },
+ "top_provider": {
+ "context_length": 40960,
+ "max_completion_tokens": 8192,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
{
"id": "qwen/qwen3-coder",
"name": "Qwen3 Coder",
"provider": "openrouter",
"family": "qwen",
- "created_at": "2025-07-23 00:00:00 +0530",
+ "created_at": "2025-07-23 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 66536,
"knowledge_cutoff": null,
@@ -20645,7 +51273,9 @@
},
"capabilities": [
"function_calling",
- "structured_output"
+ "structured_output",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -20656,6 +51286,41 @@
}
},
"metadata": {
+ "description": "Qwen3-Coder-480B-A35B-Instruct is a Mixture-of-Experts (MoE) code generation model developed by the Qwen team. It is optimized for agentic coding tasks such as function calling, tool use, and long-context reasoning over...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -20678,7 +51343,7 @@
"name": "Qwen3 Coder 30B A3B Instruct",
"provider": "openrouter",
"family": "qwen",
- "created_at": "2025-07-31 00:00:00 +0530",
+ "created_at": "2025-07-31 00:00:00 UTC",
"context_window": 160000,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -20692,7 +51357,8 @@
},
"capabilities": [
"function_calling",
- "structured_output"
+ "structured_output",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -20703,6 +51369,39 @@
}
},
"metadata": {
+ "description": "Qwen3-Coder-30B-A3B-Instruct is a 30.5B parameter Mixture-of-Experts (MoE) model with 128 experts (8 active per forward pass), designed for advanced code generation, repository-scale understanding, and agentic tool use. Built on the...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 160000,
+ "max_completion_tokens": 32768,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -20725,7 +51424,7 @@
"name": "Qwen3 Coder Flash",
"provider": "openrouter",
"family": "qwen",
- "created_at": "2025-07-23 00:00:00 +0530",
+ "created_at": "2025-07-23 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 66536,
"knowledge_cutoff": null,
@@ -20738,7 +51437,9 @@
]
},
"capabilities": [
- "function_calling"
+ "function_calling",
+ "streaming",
+ "structured_output"
],
"pricing": {
"text_tokens": {
@@ -20749,6 +51450,34 @@
}
},
"metadata": {
+ "description": "Qwen3 Coder Flash is Alibaba's fast and cost efficient version of their proprietary Qwen3 Coder Plus. It is a powerful coding agent model specializing in autonomous programming via tool calling...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1000000,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -20766,12 +51495,145 @@
"knowledge": "2025-04"
}
},
+ {
+ "id": "qwen/qwen3-coder-next",
+ "name": "Qwen: Qwen3 Coder Next",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2026-02-04 00:15:01 UTC",
+ "context_window": 262144,
+ "max_output_tokens": 262144,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.11,
+ "output_per_million": 0.7999999999999999,
+ "cache_read_input_per_million": 0.07
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": 262144,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "qwen/qwen3-coder-plus",
+ "name": "Qwen: Qwen3 Coder Plus",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2025-09-23 21:25:07 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.65,
+ "output_per_million": 3.25,
+ "cache_read_input_per_million": 0.13
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen3 Coder Plus is Alibaba's proprietary version of the Open Source Qwen3 Coder 480B A35B. It is a powerful coding agent model specializing in autonomous programming via tool calling and...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1000000,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
{
"id": "qwen/qwen3-coder:exacto",
"name": "Qwen3 Coder (exacto)",
"provider": "openrouter",
"family": "qwen",
- "created_at": "2025-07-23 00:00:00 +0530",
+ "created_at": "2025-07-23 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -20813,12 +51675,66 @@
"knowledge": "2025-04"
}
},
+ {
+ "id": "qwen/qwen3-coder:free",
+ "name": "Qwen: Qwen3 Coder 480B A35B (free)",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2025-07-23 00:29:06 UTC",
+ "context_window": 262000,
+ "max_output_tokens": 262000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {},
+ "metadata": {
+ "description": "Qwen3-Coder-480B-A35B-Instruct is a Mixture-of-Experts (MoE) code generation model developed by the Qwen team. It is optimized for agentic coding tasks such as function calling, tool use, and long-context reasoning over...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262000,
+ "max_completion_tokens": 262000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "presence_penalty",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
{
"id": "qwen/qwen3-max",
"name": "Qwen3 Max",
"provider": "openrouter",
"family": "qwen",
- "created_at": "2025-09-05 00:00:00 +0530",
+ "created_at": "2025-09-05 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 32768,
"knowledge_cutoff": null,
@@ -20832,7 +51748,9 @@
},
"capabilities": [
"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "structured_output"
],
"pricing": {
"text_tokens": {
@@ -20843,6 +51761,34 @@
}
},
"metadata": {
+ "description": "Qwen3-Max is an updated release built on the Qwen3 series, offering major improvements in reasoning, instruction following, multilingual support, and long-tail knowledge coverage compared to the January 2025 version. It...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": 32768,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -20860,13 +51806,13 @@
}
},
{
- "id": "qwen/qwen3-next-80b-a3b-instruct",
- "name": "Qwen3 Next 80B A3B Instruct",
+ "id": "qwen/qwen3-max-thinking",
+ "name": "Qwen: Qwen3 Max Thinking",
"provider": "openrouter",
"family": "qwen",
- "created_at": "2025-09-11 00:00:00 +0530",
+ "created_at": "2026-02-09 21:18:21 UTC",
"context_window": 262144,
- "max_output_tokens": 262144,
+ "max_output_tokens": 32768,
"knowledge_cutoff": null,
"modalities": {
"input": [
@@ -20877,41 +51823,58 @@
]
},
"capabilities": [
+ "streaming",
"function_calling",
"structured_output"
],
"pricing": {
"text_tokens": {
"standard": {
- "input_per_million": 0.14,
- "output_per_million": 1.4
+ "input_per_million": 0.78,
+ "output_per_million": 3.9
}
}
},
"metadata": {
- "source": "models.dev",
- "provider_id": "openrouter",
- "open_weights": true,
- "attachment": false,
- "temperature": true,
- "last_updated": "2025-09-11",
- "cost": {
- "input": 0.14,
- "output": 1.4
+ "description": "Qwen3-Max-Thinking is the flagship reasoning model in the Qwen3 series, designed for high-stakes cognitive tasks that require deep, multi-step reasoning. By significantly scaling model capacity and reinforcement learning compute, it...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen",
+ "instruct_type": null
},
- "limit": {
- "context": 262144,
- "output": 262144
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": 32768,
+ "is_moderated": false
},
- "knowledge": "2025-04"
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
}
},
{
- "id": "qwen/qwen3-next-80b-a3b-thinking",
- "name": "Qwen3 Next 80B A3B Thinking",
+ "id": "qwen/qwen3-next-80b-a3b-instruct",
+ "name": "Qwen3 Next 80B A3B Instruct",
"provider": "openrouter",
"family": "qwen",
- "created_at": "2025-09-11 00:00:00 +0530",
+ "created_at": "2025-09-11 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 262144,
"knowledge_cutoff": null,
@@ -20926,7 +51889,8 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -20937,6 +51901,41 @@
}
},
"metadata": {
+ "description": "Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces. It targets complex tasks across reasoning, code generation, knowledge QA, and multilingual...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -20954,12 +51953,870 @@
"knowledge": "2025-04"
}
},
+ {
+ "id": "qwen/qwen3-next-80b-a3b-instruct:free",
+ "name": "Qwen: Qwen3 Next 80B A3B Instruct (free)",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2025-09-11 17:36:53 UTC",
+ "context_window": 262144,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {},
+ "metadata": {
+ "description": "Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces. It targets complex tasks across reasoning, code generation, knowledge QA, and multilingual...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "qwen/qwen3-next-80b-a3b-thinking",
+ "name": "Qwen3 Next 80B A3B Thinking",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2025-09-11 00:00:00 UTC",
+ "context_window": 262144,
+ "max_output_tokens": 262144,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.14,
+ "output_per_million": 1.4
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen3-Next-80B-A3B-Thinking is a reasoning-first chat model in the Qwen3-Next line that outputs structured “thinking” traces by default. It’s designed for hard multi-step problems; math proofs, code synthesis/debugging, logic, and agentic...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 32768,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
+ "source": "models.dev",
+ "provider_id": "openrouter",
+ "open_weights": true,
+ "attachment": false,
+ "temperature": true,
+ "last_updated": "2025-09-11",
+ "cost": {
+ "input": 0.14,
+ "output": 1.4
+ },
+ "limit": {
+ "context": 262144,
+ "output": 262144
+ },
+ "knowledge": "2025-04"
+ }
+ },
+ {
+ "id": "qwen/qwen3-vl-235b-a22b-instruct",
+ "name": "Qwen: Qwen3 VL 235B A22B Instruct",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2025-09-23 23:04:47 UTC",
+ "context_window": 262144,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.19999999999999998,
+ "output_per_million": 0.88,
+ "cache_read_input_per_million": 0.11
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
+ "top_provider": {
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{
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@@ -20977,7 +52834,9 @@
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@@ -20988,6 +52847,47 @@
}
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"open_weights": true,
@@ -21005,12 +52905,88 @@
"knowledge": "2025-04"
}
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{
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"name": "Qwen: Qwen3.5-Flash",
"provider": "openrouter",
"family": "qwen",
- "created_at": "2026-02-25 00:00:00 +0530",
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@@ -21028,7 +53004,8 @@
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+ "vision",
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@@ -21039,6 +53016,39 @@
}
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+ "architecture": {
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@@ -21060,7 +53070,7 @@
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@@ -21078,7 +53088,8 @@
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@@ -21089,6 +53100,39 @@
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},
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+ "description": "The Qwen3.5 native vision-language series Plus models are built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models, achieving higher inference efficiency. In a variety of...",
+ "architecture": {
+ "modality": "text+image+video->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1000000,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -21106,12 +53150,367 @@
"knowledge": "2025-04"
}
},
+ {
+ "id": "qwen/qwen3.5-plus-20260420",
+ "name": "Qwen: Qwen3.5 Plus 2026-04-20",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2026-04-27 03:42:48 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "video"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.39999999999999997,
+ "output_per_million": 2.4
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen3.5 Plus (April 2026) is a large-scale multimodal language model from Alibaba. It accepts text, image, and video input and produces text output, with a 1M token context window. This...",
+ "architecture": {
+ "modality": "text+image+video->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
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+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "qwen/qwen3.6-27b",
+ "name": "Qwen: Qwen3.6 27B",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2026-04-27 01:57:44 UTC",
+ "context_window": 262144,
+ "max_output_tokens": 81920,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "video"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.32,
+ "output_per_million": 3.1999999999999997
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen3.6 27B is a dense 27-billion-parameter language model from the Qwen Team at Alibaba, released in April 2026. It features hybrid multimodal capabilities — accepting text, image, and video inputs...",
+ "architecture": {
+ "modality": "text+image+video->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
+ "top_provider": {
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+ "max_completion_tokens": 81920,
+ "is_moderated": false
+ },
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+ "supported_parameters": [
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+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "qwen/qwen3.6-35b-a3b",
+ "name": "Qwen: Qwen3.6 35B A3B",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2026-04-27 03:24:15 UTC",
+ "context_window": 262144,
+ "max_output_tokens": 262144,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "image",
+ "video"
+ ],
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+ "text"
+ ]
+ },
+ "capabilities": [
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+ "function_calling",
+ "structured_output",
+ "predicted_outputs"
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+ "output_per_million": 1.0,
+ "cache_read_input_per_million": 0.049999999999999996
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. It uses a hybrid sparse mixture-of-experts architecture combining Gated...",
+ "architecture": {
+ "modality": "text+image+video->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen",
+ "instruct_type": null
+ },
+ "top_provider": {
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+ "max_completion_tokens": 262144,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "qwen/qwen3.6-flash",
+ "name": "Qwen: Qwen3.6 Flash",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2026-04-27 03:42:42 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "video"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.25,
+ "output_per_million": 1.5
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen3.6 Flash is a fast, efficient language model from Alibaba's Qwen 3.6 series. It supports text, image, and video input with a 1M token context window. Tiered pricing kicks in...",
+ "architecture": {
+ "modality": "text+image+video->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1000000,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "qwen/qwen3.6-max-preview",
+ "name": "Qwen: Qwen3.6 Max Preview",
+ "provider": "openrouter",
+ "family": "qwen",
+ "created_at": "2026-04-27 03:24:02 UTC",
+ "context_window": 262144,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 1.04,
+ "output_per_million": 6.24
+ }
+ }
+ },
+ "metadata": {
+ "description": "Qwen3.6-Max-Preview is a proprietary frontier model from Alibaba Cloud built on a sparse mixture-of-experts architecture with approximately 1 trillion total parameters. It is optimized for agentic coding, tool use, and...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "logprobs",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
{
"id": "qwen/qwen3.6-plus",
"name": "Qwen3.6 Plus",
"provider": "openrouter",
"family": "qwen",
- "created_at": "2026-04-02 00:00:00 +0530",
+ "created_at": "2026-04-02 00:00:00 UTC",
"context_window": 1000000,
"max_output_tokens": 65536,
"knowledge_cutoff": null,
@@ -21129,7 +53528,8 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -21140,6 +53540,39 @@
}
},
"metadata": {
+ "description": "Qwen 3.6 Plus builds on a hybrid architecture that combines efficient linear attention with sparse mixture-of-experts routing, enabling strong scalability and high-performance inference. Compared to the 3.5 series, it delivers...",
+ "architecture": {
+ "modality": "text+image+video->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Qwen3",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1000000,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -21157,12 +53590,582 @@
"knowledge": "2025-04"
}
},
+ {
+ "id": "rekaai/reka-edge",
+ "name": "Reka Edge",
+ "provider": "openrouter",
+ "family": "rekaai",
+ "created_at": "2026-03-20 17:16:05 UTC",
+ "context_window": 16384,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "image",
+ "text",
+ "video"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.09999999999999999,
+ "output_per_million": 0.09999999999999999
+ }
+ }
+ },
+ "metadata": {
+ "description": "Reka Edge is an extremely efficient 7B multimodal vision-language model that accepts image/video+text inputs and generates text outputs. This model is optimized specifically to deliver industry-leading performance in image understanding,...",
+ "architecture": {
+ "modality": "text+image+video->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 16384,
+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "presence_penalty",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "rekaai/reka-flash-3",
+ "name": "Reka Flash 3",
+ "provider": "openrouter",
+ "family": "rekaai",
+ "created_at": "2025-03-12 20:53:33 UTC",
+ "context_window": 65536,
+ "max_output_tokens": 65536,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.09999999999999999,
+ "output_per_million": 0.19999999999999998
+ }
+ }
+ },
+ "metadata": {
+ "description": "Reka Flash 3 is a general-purpose, instruction-tuned large language model with 21 billion parameters, developed by Reka. It excels at general chat, coding tasks, instruction-following, and function calling. Featuring a...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 65536,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "seed",
+ "stop",
+ "temperature",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "relace/relace-apply-3",
+ "name": "Relace: Relace Apply 3",
+ "provider": "openrouter",
+ "family": "relace",
+ "created_at": "2025-09-26 12:59:32 UTC",
+ "context_window": 256000,
+ "max_output_tokens": 128000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.85,
+ "output_per_million": 1.25
+ }
+ }
+ },
+ "metadata": {
+ "description": "Relace Apply 3 is a specialized code-patching LLM that merges AI-suggested edits straight into your source files. It can apply updates from GPT-4o, Claude, and others into your files at...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 256000,
+ "max_completion_tokens": 128000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "seed",
+ "stop"
+ ]
+ }
+ },
+ {
+ "id": "relace/relace-search",
+ "name": "Relace: Relace Search",
+ "provider": "openrouter",
+ "family": "relace",
+ "created_at": "2025-12-08 17:06:00 UTC",
+ "context_window": 256000,
+ "max_output_tokens": 128000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 1.0,
+ "output_per_million": 3.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "The relace-search model uses 4-12 `view_file` and `grep` tools in parallel to explore a codebase and return relevant files to the user request. In contrast to RAG, relace-search performs agentic...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 256000,
+ "max_completion_tokens": 128000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "seed",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "sao10k/l3-euryale-70b",
+ "name": "Sao10k: Llama 3 Euryale 70B v2.1",
+ "provider": "openrouter",
+ "family": "sao10k",
+ "created_at": "2024-06-18 00:00:00 UTC",
+ "context_window": 8192,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 1.48,
+ "output_per_million": 1.48
+ }
+ }
+ },
+ "metadata": {
+ "description": "Euryale 70B v2.1 is a model focused on creative roleplay from [Sao10k](https://ko-fi.com/sao10k). - Better prompt adherence. - Better anatomy / spatial awareness. - Adapts much better to unique and custom...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Llama3",
+ "instruct_type": "llama3"
+ },
+ "top_provider": {
+ "context_length": 8192,
+ "max_completion_tokens": 8192,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "max_tokens",
+ "presence_penalty",
+ "repetition_penalty",
+ "seed",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "sao10k/l3-lunaris-8b",
+ "name": "Sao10K: Llama 3 8B Lunaris",
+ "provider": "openrouter",
+ "family": "sao10k",
+ "created_at": "2024-08-13 00:00:00 UTC",
+ "context_window": 8192,
+ "max_output_tokens": 16384,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "structured_output",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.04,
+ "output_per_million": 0.049999999999999996
+ }
+ }
+ },
+ "metadata": {
+ "description": "Lunaris 8B is a versatile generalist and roleplaying model based on Llama 3. It's a strategic merge of multiple models, designed to balance creativity with improved logic and general knowledge....",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Llama3",
+ "instruct_type": "llama3"
+ },
+ "top_provider": {
+ "context_length": 8192,
+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "sao10k/l3.1-70b-hanami-x1",
+ "name": "Sao10K: Llama 3.1 70B Hanami x1",
+ "provider": "openrouter",
+ "family": "sao10k",
+ "created_at": "2025-01-08 02:20:54 UTC",
+ "context_window": 16000,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "predicted_outputs"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 3.0,
+ "output_per_million": 3.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "This is [Sao10K](/sao10k)'s experiment over [Euryale v2.2](/sao10k/l3.1-euryale-70b).",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Llama3",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 16000,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "repetition_penalty",
+ "seed",
+ "stop",
+ "temperature",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "sao10k/l3.1-euryale-70b",
+ "name": "Sao10K: Llama 3.1 Euryale 70B v2.2",
+ "provider": "openrouter",
+ "family": "sao10k",
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+ "name": "Sao10K: Llama 3.3 Euryale 70B",
+ "provider": "openrouter",
+ "family": "sao10k",
+ "created_at": "2024-12-18 15:32:08 UTC",
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+ "description": "Euryale L3.3 70B is a model focused on creative roleplay from [Sao10k](https://ko-fi.com/sao10k). It is the successor of [Euryale L3 70B v2.2](/models/sao10k/l3-euryale-70b).",
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+ "structured_outputs",
+ "temperature",
+ "top_k",
+ "top_logprobs",
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+ },
{
"id": "sourceful/riverflow-v2-fast-preview",
"name": "Riverflow V2 Fast Preview",
"provider": "openrouter",
"family": "sourceful",
- "created_at": "2025-12-08 00:00:00 +0530",
+ "created_at": "2025-12-08 00:00:00 UTC",
"context_window": 8192,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -21202,7 +54205,7 @@
"name": "Riverflow V2 Max Preview",
"provider": "openrouter",
"family": "sourceful",
- "created_at": "2025-12-08 00:00:00 +0530",
+ "created_at": "2025-12-08 00:00:00 UTC",
"context_window": 8192,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -21242,7 +54245,7 @@
"name": "Riverflow V2 Standard Preview",
"provider": "openrouter",
"family": "sourceful",
- "created_at": "2025-12-08 00:00:00 +0530",
+ "created_at": "2025-12-08 00:00:00 UTC",
"context_window": 8192,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -21282,7 +54285,7 @@
"name": "Step 3.5 Flash",
"provider": "openrouter",
"family": "step",
- "created_at": "2026-01-29 00:00:00 +0530",
+ "created_at": "2026-01-29 00:00:00 UTC",
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"max_output_tokens": 256000,
"knowledge_cutoff": null,
@@ -21296,18 +54299,57 @@
},
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+ "reasoning",
+ "streaming",
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+ "predicted_outputs"
],
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"output_per_million": 0.3,
- "cached_input_per_million": 0.02
+ "cache_read_input_per_million": 0.02
}
}
},
"metadata": {
+ "description": "Step 3.5 Flash is StepFun's most capable open-source foundation model. Built on a sparse Mixture of Experts (MoE) architecture, it selectively activates only 11B of its 196B parameters per token....",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
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+ "tokenizer": "Other",
+ "instruct_type": null
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+ "response_format",
+ "seed",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -21326,12 +54368,708 @@
"knowledge": "2025-01"
}
},
+ {
+ "id": "switchpoint/router",
+ "name": "Switchpoint Router",
+ "provider": "openrouter",
+ "family": "switchpoint",
+ "created_at": "2025-07-11 22:28:19 UTC",
+ "context_window": 131072,
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+ },
+ "metadata": {
+ "description": "Switchpoint AI's router instantly analyzes your request and directs it to the optimal AI from an ever-evolving library. As the world of LLMs advances, our router gets smarter, ensuring you...",
+ "architecture": {
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+ "name": "Tencent: Hunyuan A13B Instruct",
+ "provider": "openrouter",
+ "family": "tencent",
+ "created_at": "2025-07-08 15:14:24 UTC",
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+ }
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+ "metadata": {
+ "description": "Hunyuan-A13B is a 13B active parameter Mixture-of-Experts (MoE) language model developed by Tencent, with a total parameter count of 80B and support for reasoning via Chain-of-Thought. It offers competitive benchmark...",
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+ },
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+ "name": "Tencent: Hy3 preview (free)",
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+ "family": "tencent",
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+ "description": "Hy3 preview is a high-efficiency Mixture-of-Experts model from Tencent designed for agentic workflows and production use. It supports configurable reasoning levels across disabled, low, and high modes, allowing it to...",
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+ "metadata": {
+ "description": "Rocinante 12B is designed for engaging storytelling and rich prose. Early testers have reported: - Expanded vocabulary with unique and expressive word choices - Enhanced creativity for vivid narratives -...",
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+ "provider": "openrouter",
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+ "cache_read_input_per_million": 0.25
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+ "family": "undi95",
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+ "metadata": {
+ "description": "A recreation trial of the original MythoMax-L2-B13 but with updated models. #merge",
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+ {
+ "id": "upstage/solar-pro-3",
+ "name": "Upstage: Solar Pro 3",
+ "provider": "openrouter",
+ "family": "upstage",
+ "created_at": "2026-01-27 02:33:20 UTC",
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+ "metadata": {
+ "description": "Solar Pro 3 is Upstage's powerful Mixture-of-Experts (MoE) language model. With 102B total parameters and 12B active parameters per forward pass, it delivers exceptional performance while maintaining computational efficiency. Optimized...",
+ "architecture": {
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+ {
+ "id": "writer/palmyra-x5",
+ "name": "Writer: Palmyra X5",
+ "provider": "openrouter",
+ "family": "writer",
+ "created_at": "2026-01-21 13:57:03 UTC",
+ "context_window": 1040000,
+ "max_output_tokens": 8192,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.6,
+ "output_per_million": 6.0
+ }
+ }
+ },
+ "metadata": {
+ "description": "Palmyra X5 is Writer's most advanced model, purpose-built for building and scaling AI agents across the enterprise. It delivers industry-leading speed and efficiency on context windows up to 1 million...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1040000,
+ "max_completion_tokens": 8192,
+ "is_moderated": true
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "stop",
+ "temperature",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
{
"id": "x-ai/grok-3",
"name": "Grok 3",
"provider": "openrouter",
"family": "grok",
- "created_at": "2025-02-17 00:00:00 +0530",
+ "created_at": "2025-02-17 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -21345,18 +55083,53 @@
},
"capabilities": [
"function_calling",
- "structured_output"
+ "structured_output",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.75
+ "cache_read_input_per_million": 0.75,
+ "cache_write_input_per_million": 15
}
}
},
"metadata": {
+ "description": "Grok 3 is the latest model from xAI. It's their flagship model that excels at enterprise use cases like data extraction, coding, and text summarization. Possesses deep domain knowledge in...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Grok",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logprobs",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -21381,7 +55154,7 @@
"name": "Grok 3 Beta",
"provider": "openrouter",
"family": "grok",
- "created_at": "2025-02-17 00:00:00 +0530",
+ "created_at": "2025-02-17 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -21394,18 +55167,53 @@
]
},
"capabilities": [
- "function_calling"
+ "function_calling",
+ "streaming",
+ "structured_output"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.75
+ "cache_read_input_per_million": 0.75,
+ "cache_write_input_per_million": 15
}
}
},
"metadata": {
+ "description": "Grok 3 is the latest model from xAI. It's their flagship model that excels at enterprise use cases like data extraction, coding, and text summarization. Possesses deep domain knowledge in...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Grok",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "logprobs",
+ "max_tokens",
+ "presence_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -21430,7 +55238,7 @@
"name": "Grok 3 Mini",
"provider": "openrouter",
"family": "grok",
- "created_at": "2025-02-17 00:00:00 +0530",
+ "created_at": "2025-02-17 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -21445,18 +55253,53 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.3,
"output_per_million": 0.5,
- "cached_input_per_million": 0.075
+ "cache_read_input_per_million": 0.075,
+ "cache_write_input_per_million": 0.5
}
}
},
"metadata": {
+ "description": "A lightweight model that thinks before responding. Fast, smart, and great for logic-based tasks that do not require deep domain knowledge. The raw thinking traces are accessible.",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Grok",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "logprobs",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -21481,7 +55324,7 @@
"name": "Grok 3 Mini Beta",
"provider": "openrouter",
"family": "grok",
- "created_at": "2025-02-17 00:00:00 +0530",
+ "created_at": "2025-02-17 00:00:00 UTC",
"context_window": 131072,
"max_output_tokens": 8192,
"knowledge_cutoff": null,
@@ -21495,18 +55338,53 @@
},
"capabilities": [
"function_calling",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "structured_output"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.3,
"output_per_million": 0.5,
- "cached_input_per_million": 0.075
+ "cache_read_input_per_million": 0.075,
+ "cache_write_input_per_million": 0.5
}
}
},
"metadata": {
+ "description": "Grok 3 Mini is a lightweight, smaller thinking model. Unlike traditional models that generate answers immediately, Grok 3 Mini thinks before responding. It’s ideal for reasoning-heavy tasks that don’t demand...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Grok",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "logprobs",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -21531,7 +55409,7 @@
"name": "Grok 4",
"provider": "openrouter",
"family": "grok",
- "created_at": "2025-07-09 00:00:00 +0530",
+ "created_at": "2025-07-09 00:00:00 UTC",
"context_window": 256000,
"max_output_tokens": 64000,
"knowledge_cutoff": null,
@@ -21546,18 +55424,54 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 3,
"output_per_million": 15,
- "cached_input_per_million": 0.75
+ "cache_read_input_per_million": 0.75,
+ "cache_write_input_per_million": 15
}
}
},
"metadata": {
+ "description": "Grok 4 is xAI's latest reasoning model with a 256k context window. It supports parallel tool calling, structured outputs, and both image and text inputs. Note that reasoning is not...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Grok",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 256000,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "logprobs",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -21582,7 +55496,7 @@
"name": "Grok 4 Fast",
"provider": "openrouter",
"family": "grok",
- "created_at": "2025-08-19 00:00:00 +0530",
+ "created_at": "2025-08-19 00:00:00 UTC",
"context_window": 2000000,
"max_output_tokens": 30000,
"knowledge_cutoff": null,
@@ -21599,18 +55513,54 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.2,
"output_per_million": 0.5,
- "cached_input_per_million": 0.05
+ "cache_read_input_per_million": 0.05,
+ "cache_write_input_per_million": 0.05
}
}
},
"metadata": {
+ "description": "Grok 4 Fast is xAI's latest multimodal model with SOTA cost-efficiency and a 2M token context window. It comes in two flavors: non-reasoning and reasoning. Read more about the model...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Grok",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 2000000,
+ "max_completion_tokens": 30000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "logprobs",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -21635,7 +55585,7 @@
"name": "Grok 4.1 Fast",
"provider": "openrouter",
"family": "grok",
- "created_at": "2025-11-19 00:00:00 +0530",
+ "created_at": "2025-11-19 00:00:00 UTC",
"context_window": 2000000,
"max_output_tokens": 30000,
"knowledge_cutoff": null,
@@ -21652,18 +55602,54 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.2,
"output_per_million": 0.5,
- "cached_input_per_million": 0.05
+ "cache_read_input_per_million": 0.05,
+ "cache_write_input_per_million": 0.05
}
}
},
"metadata": {
+ "description": "Grok 4.1 Fast is xAI's best agentic tool calling model that shines in real-world use cases like customer support and deep research. 2M context window. Reasoning can be enabled/disabled using...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Grok",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 2000000,
+ "max_completion_tokens": 30000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "logprobs",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -21683,12 +55669,82 @@
"knowledge": "2024-11"
}
},
+ {
+ "id": "x-ai/grok-4.20",
+ "name": "xAI: Grok 4.20",
+ "provider": "openrouter",
+ "family": "x-ai",
+ "created_at": "2026-03-31 17:43:39 UTC",
+ "context_window": 2000000,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 1.25,
+ "output_per_million": 2.5,
+ "cache_read_input_per_million": 0.19999999999999998
+ }
+ }
+ },
+ "metadata": {
+ "description": "Grok 4.20 is xAI's newest flagship model with industry-leading speed and agentic tool calling capabilities. It combines the lowest hallucination rate on the market with strict prompt adherance, delivering consistently...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Grok",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 2000000,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "logprobs",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
{
"id": "x-ai/grok-4.20-beta",
"name": "Grok 4.20 Beta",
"provider": "openrouter",
"family": "grok",
- "created_at": "2026-03-12 00:00:00 +0530",
+ "created_at": "2026-03-12 00:00:00 UTC",
"context_window": 2000000,
"max_output_tokens": 30000,
"knowledge_cutoff": null,
@@ -21711,7 +55767,7 @@
"standard": {
"input_per_million": 2,
"output_per_million": 6,
- "cached_input_per_million": 0.2
+ "cache_read_input_per_million": 0.2
}
}
},
@@ -21738,12 +55794,79 @@
}
}
},
+ {
+ "id": "x-ai/grok-4.20-multi-agent",
+ "name": "xAI: Grok 4.20 Multi-Agent",
+ "provider": "openrouter",
+ "family": "x-ai",
+ "created_at": "2026-03-31 17:45:58 UTC",
+ "context_window": 2000000,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "structured_output"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 2.0,
+ "output_per_million": 6.0,
+ "cache_read_input_per_million": 0.19999999999999998
+ }
+ }
+ },
+ "metadata": {
+ "description": "Grok 4.20 Multi-Agent is a variant of xAI’s Grok 4.20 designed for collaborative, agent-based workflows. Multiple agents operate in parallel to conduct deep research, coordinate tool use, and synthesize information...",
+ "architecture": {
+ "modality": "text+image+file->text",
+ "input_modalities": [
+ "text",
+ "image",
+ "file"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Grok",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 2000000,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "logprobs",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "structured_outputs",
+ "temperature",
+ "top_logprobs",
+ "top_p"
+ ]
+ }
+ },
{
"id": "x-ai/grok-4.20-multi-agent-beta",
"name": "Grok 4.20 Multi - Agent Beta",
"provider": "openrouter",
"family": "grok",
- "created_at": "2026-03-12 00:00:00 +0530",
+ "created_at": "2026-03-12 00:00:00 UTC",
"context_window": 2000000,
"max_output_tokens": 30000,
"knowledge_cutoff": null,
@@ -21765,7 +55888,7 @@
"standard": {
"input_per_million": 2,
"output_per_million": 6,
- "cached_input_per_million": 0.2
+ "cache_read_input_per_million": 0.2
}
}
},
@@ -21792,12 +55915,105 @@
}
}
},
+ {
+ "id": "x-ai/grok-4.3",
+ "name": "Grok 4.3",
+ "provider": "openrouter",
+ "family": "grok",
+ "created_at": "2026-05-01 00:00:00 UTC",
+ "context_window": 1000000,
+ "max_output_tokens": 1000000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "text",
+ "image"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "function_calling",
+ "structured_output",
+ "reasoning",
+ "vision",
+ "streaming"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 1.25,
+ "output_per_million": 2.5,
+ "cache_read_input_per_million": 0.2
+ }
+ }
+ },
+ "metadata": {
+ "description": "Grok 4.3 is a reasoning model from xAI. It accepts text and image inputs with text output, and is suited for agentic workflows, instruction-following tasks, and applications requiring high factual...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Grok",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 1000000,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logprobs",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ],
+ "source": "models.dev",
+ "provider_id": "openrouter",
+ "open_weights": false,
+ "attachment": true,
+ "temperature": true,
+ "last_updated": "2026-05-01",
+ "cost": {
+ "input": 1.25,
+ "output": 2.5,
+ "cache_read": 0.2,
+ "context_over_200k": {
+ "input": 2.5,
+ "output": 5,
+ "cache_read": 0.4
+ }
+ },
+ "limit": {
+ "context": 1000000,
+ "output": 1000000
+ }
+ }
+ },
{
"id": "x-ai/grok-code-fast-1",
"name": "Grok Code Fast 1",
"provider": "openrouter",
"family": "grok",
- "created_at": "2025-08-26 00:00:00 +0530",
+ "created_at": "2025-08-26 00:00:00 UTC",
"context_window": 256000,
"max_output_tokens": 10000,
"knowledge_cutoff": null,
@@ -21812,18 +56028,52 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.2,
"output_per_million": 1.5,
- "cached_input_per_million": 0.02
+ "cache_read_input_per_million": 0.02
}
}
},
"metadata": {
+ "description": "Grok Code Fast 1 is a speedy and economical reasoning model that excels at agentic coding. With reasoning traces visible in the response, developers can steer Grok Code for high-quality...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Grok",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 256000,
+ "max_completion_tokens": 10000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "logprobs",
+ "max_tokens",
+ "reasoning",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -21844,13 +56094,13 @@
},
{
"id": "xiaomi/mimo-v2-flash",
- "name": "MiMo-V2-Flash",
+ "name": "Xiaomi: MiMo-V2-Flash",
"provider": "openrouter",
"family": "mimo",
- "created_at": "2025-12-14 00:00:00 +0530",
+ "created_at": "2025-12-16 00:00:00 UTC",
"context_window": 262144,
"max_output_tokens": 65536,
- "knowledge_cutoff": null,
+ "knowledge_cutoff": "2024-12-01",
"modalities": {
"input": [
"text"
@@ -21861,25 +56111,64 @@
},
"capabilities": [
"function_calling",
- "structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "structured_output"
],
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"output_per_million": 0.3,
- "cached_input_per_million": 0.01
+ "cache_read_input_per_million": 0.01
}
}
},
"metadata": {
+ "description": "MiMo-V2-Flash is an open-source foundation language model developed by Xiaomi. It is a Mixture-of-Experts model with 309B total parameters and 15B active parameters, adopting hybrid attention architecture. MiMo-V2-Flash supports a...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
"attachment": false,
"temperature": true,
- "last_updated": "2025-12-14",
+ "last_updated": "2026-02-04",
+ "interleaved": {
+ "field": "reasoning_details"
+ },
"cost": {
"input": 0.1,
"output": 0.3,
@@ -21889,24 +56178,25 @@
"context": 262144,
"output": 65536
},
- "knowledge": "2024-12"
+ "knowledge": "2024-12-01"
}
},
{
"id": "xiaomi/mimo-v2-omni",
- "name": "MiMo-V2-Omni",
+ "name": "Xiaomi: MiMo-V2-Omni",
"provider": "openrouter",
"family": "mimo",
- "created_at": "2026-03-18 00:00:00 +0530",
+ "created_at": "2026-03-18 00:00:00 UTC",
"context_window": 262144,
- "max_output_tokens": 65536,
+ "max_output_tokens": 131072,
"knowledge_cutoff": null,
"modalities": {
"input": [
"text",
"image",
+ "audio",
"video",
- "audio"
+ "pdf"
],
"output": [
"text"
@@ -21914,23 +56204,58 @@
},
"capabilities": [
"function_calling",
- "structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming",
+ "structured_output"
],
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"output_per_million": 2,
- "cached_input_per_million": 0.08
+ "cache_read_input_per_million": 0.08
}
}
},
"metadata": {
+ "description": "MiMo-V2-Omni is a frontier omni-modal model that natively processes image, video, and audio inputs within a unified architecture. It combines strong multimodal perception with agentic capability - visual grounding, multi-step...",
+ "architecture": {
+ "modality": "text+image+audio+video->text",
+ "input_modalities": [
+ "text",
+ "audio",
+ "image",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 262144,
+ "max_completion_tokens": 65536,
+ "is_moderated": false
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+ "supported_parameters": [
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+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "response_format",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
- "open_weights": true,
+ "open_weights": false,
"attachment": true,
"temperature": true,
"last_updated": "2026-03-18",
@@ -21944,18 +56269,19 @@
},
"limit": {
"context": 262144,
- "output": 65536
- }
+ "output": 131072
+ },
+ "knowledge": "2024-12"
}
},
{
"id": "xiaomi/mimo-v2-pro",
- "name": "MiMo-V2-Pro",
+ "name": "Xiaomi: MiMo-V2-Pro",
"provider": "openrouter",
"family": "mimo",
- "created_at": "2026-03-18 00:00:00 +0530",
+ "created_at": "2026-03-18 00:00:00 UTC",
"context_window": 1048576,
- "max_output_tokens": 65536,
+ "max_output_tokens": 131072,
"knowledge_cutoff": null,
"modalities": {
"input": [
@@ -21967,23 +56293,55 @@
},
"capabilities": [
"function_calling",
- "structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "structured_output"
],
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"input_per_million": 1,
"output_per_million": 3,
- "cached_input_per_million": 0.2
+ "cache_read_input_per_million": 0.2
}
}
},
"metadata": {
+ "description": "MiMo-V2-Pro is Xiaomi's flagship foundation model, featuring over 1T total parameters and a 1M context length, deeply optimized for agentic scenarios. It is highly adaptable to general agent frameworks like...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
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+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
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+ "top_provider": {
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+ "max_completion_tokens": 131072,
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+ "supported_parameters": [
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+ "max_tokens",
+ "presence_penalty",
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+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
- "open_weights": true,
- "attachment": false,
+ "open_weights": false,
+ "attachment": true,
"temperature": true,
"last_updated": "2026-03-18",
"interleaved": {
@@ -21992,12 +56350,262 @@
"cost": {
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"output": 3,
- "cache_read": 0.2
+ "cache_read": 0.2,
+ "context_over_200k": {
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+ "output": 6,
+ "cache_read": 0.4
+ }
},
"limit": {
"context": 1048576,
- "output": 65536
+ "output": 131072
+ },
+ "knowledge": "2024-12"
+ }
+ },
+ {
+ "id": "xiaomi/mimo-v2.5",
+ "name": "Xiaomi: MiMo-V2.5",
+ "provider": "openrouter",
+ "family": "mimo",
+ "created_at": "2026-04-22 00:00:00 UTC",
+ "context_window": 1048576,
+ "max_output_tokens": 131072,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "image",
+ "audio",
+ "video"
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+ "output": [
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+ },
+ "capabilities": [
+ "function_calling",
+ "reasoning",
+ "vision",
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+ "output_per_million": 2,
+ "cache_read_input_per_million": 0.08
+ }
}
+ },
+ "metadata": {
+ "description": "MiMo-V2.5 is a native omnimodal model by Xiaomi. It delivers Pro-level agentic performance at roughly half the inference cost, while surpassing MiMo-V2-Omni in multimodal perception across image and video understanding...",
+ "architecture": {
+ "modality": "text+image+audio+video->text",
+ "input_modalities": [
+ "text",
+ "audio",
+ "image",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
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+ "instruct_type": null
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+ "temperature",
+ "tool_choice",
+ "tools",
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+ "attachment": true,
+ "temperature": true,
+ "last_updated": "2026-04-22",
+ "interleaved": {
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+ {
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+ "name": "Xiaomi: MiMo-V2.5-Pro",
+ "provider": "openrouter",
+ "family": "mimo",
+ "created_at": "2026-04-22 00:00:00 UTC",
+ "context_window": 1048576,
+ "max_output_tokens": 131072,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "cache_read_input_per_million": 0.2
+ }
+ }
+ },
+ "metadata": {
+ "description": "MiMo-V2.5-Pro is Xiaomi’s flagship model, delivering strong performance in general agentic capabilities, complex software engineering, and long-horizon tasks, with top rankings on benchmarks such as ClawEval, GDPVal, and SWE-bench Pro....",
+ "architecture": {
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+ "tool_choice",
+ "tools",
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+ "provider_id": "openrouter",
+ "open_weights": true,
+ "attachment": true,
+ "temperature": true,
+ "last_updated": "2026-04-22",
+ "interleaved": {
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+ "limit": {
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+ "output": 131072
+ },
+ "knowledge": "2024-12"
+ }
+ },
+ {
+ "id": "z-ai/glm-4-32b",
+ "name": "Z.ai: GLM 4 32B ",
+ "provider": "openrouter",
+ "family": "z-ai",
+ "created_at": "2025-07-24 17:03:37 UTC",
+ "context_window": 128000,
+ "max_output_tokens": null,
+ "knowledge_cutoff": null,
+ "modalities": {
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+ "capabilities": [
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+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.09999999999999999,
+ "output_per_million": 0.09999999999999999
+ }
+ }
+ },
+ "metadata": {
+ "description": "GLM 4 32B is a cost-effective foundation language model. It can efficiently perform complex tasks and has significantly enhanced capabilities in tool use, online search, and code-related intelligent tasks. It...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
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+ "output_modalities": [
+ "text"
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+ "tokenizer": "Other",
+ "instruct_type": null
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+ "top_provider": {
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+ "max_completion_tokens": null,
+ "is_moderated": false
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+ "per_request_limits": null,
+ "supported_parameters": [
+ "max_tokens",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ]
}
},
{
@@ -22005,7 +56613,7 @@
"name": "GLM 4.5",
"provider": "openrouter",
"family": "glm",
- "created_at": "2025-07-28 00:00:00 +0530",
+ "created_at": "2025-07-28 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 96000,
"knowledge_cutoff": null,
@@ -22020,7 +56628,8 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -22031,6 +56640,40 @@
}
},
"metadata": {
+ "description": "GLM-4.5 is our latest flagship foundation model, purpose-built for agent-based applications. It leverages a Mixture-of-Experts (MoE) architecture and supports a context length of up to 128k tokens. GLM-4.5 delivers significantly...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 98304,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -22053,7 +56696,7 @@
"name": "GLM 4.5 Air",
"provider": "openrouter",
"family": "glm-air",
- "created_at": "2025-07-28 00:00:00 +0530",
+ "created_at": "2025-07-28 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 96000,
"knowledge_cutoff": null,
@@ -22068,7 +56711,8 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -22079,6 +56723,39 @@
}
},
"metadata": {
+ "description": "GLM-4.5-Air is the lightweight variant of our latest flagship model family, also purpose-built for agent-centric applications. Like GLM-4.5, it adopts the Mixture-of-Experts (MoE) architecture but with a more compact parameter...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 98304,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "seed",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -22101,7 +56778,7 @@
"name": "GLM 4.5 Air (free)",
"provider": "openrouter",
"family": "glm-air",
- "created_at": "2025-07-28 00:00:00 +0530",
+ "created_at": "2025-07-28 00:00:00 UTC",
"context_window": 128000,
"max_output_tokens": 96000,
"knowledge_cutoff": null,
@@ -22114,10 +56791,39 @@
]
},
"capabilities": [
- "reasoning"
+ "reasoning",
+ "streaming",
+ "function_calling"
],
"pricing": {},
"metadata": {
+ "description": "GLM-4.5-Air is the lightweight variant of our latest flagship model family, also purpose-built for agent-centric applications. Like GLM-4.5, it adopts the Mixture-of-Experts (MoE) architecture but with a more compact parameter...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 96000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "include_reasoning",
+ "max_tokens",
+ "reasoning",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -22140,7 +56846,7 @@
"name": "GLM 4.5V",
"provider": "openrouter",
"family": "glm",
- "created_at": "2025-08-11 00:00:00 +0530",
+ "created_at": "2025-08-11 00:00:00 UTC",
"context_window": 64000,
"max_output_tokens": 16384,
"knowledge_cutoff": null,
@@ -22158,7 +56864,8 @@
"function_calling",
"structured_output",
"reasoning",
- "vision"
+ "vision",
+ "streaming"
],
"pricing": {
"text_tokens": {
@@ -22169,6 +56876,40 @@
}
},
"metadata": {
+ "description": "GLM-4.5V is a vision-language foundation model for multimodal agent applications. Built on a Mixture-of-Experts (MoE) architecture with 106B parameters and 12B activated parameters, it achieves state-of-the-art results in video understanding,...",
+ "architecture": {
+ "modality": "text+image->text",
+ "input_modalities": [
+ "text",
+ "image"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 65536,
+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "seed",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -22191,7 +56932,7 @@
"name": "GLM 4.6",
"provider": "openrouter",
"family": "glm",
- "created_at": "2025-09-30 00:00:00 +0530",
+ "created_at": "2025-09-30 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 128000,
"knowledge_cutoff": null,
@@ -22206,18 +56947,57 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.6,
"output_per_million": 2.2,
- "cached_input_per_million": 0.11
+ "cache_read_input_per_million": 0.11
}
}
},
"metadata": {
+ "description": "Compared with GLM-4.5, this generation brings several key improvements: Longer context window: The context window has been expanded from 128K to 200K tokens, enabling the model to handle more complex...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 204800,
+ "max_completion_tokens": 204800,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -22241,7 +57021,7 @@
"name": "GLM 4.6 (exacto)",
"provider": "openrouter",
"family": "glm",
- "created_at": "2025-09-30 00:00:00 +0530",
+ "created_at": "2025-09-30 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 128000,
"knowledge_cutoff": null,
@@ -22263,7 +57043,7 @@
"standard": {
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"output_per_million": 1.9,
- "cached_input_per_million": 0.11
+ "cache_read_input_per_million": 0.11
}
}
},
@@ -22286,12 +57066,82 @@
"knowledge": "2025-09"
}
},
+ {
+ "id": "z-ai/glm-4.6v",
+ "name": "Z.ai: GLM 4.6V",
+ "provider": "openrouter",
+ "family": "z-ai",
+ "created_at": "2025-12-08 15:24:22 UTC",
+ "context_window": 131072,
+ "max_output_tokens": 24000,
+ "knowledge_cutoff": null,
+ "modalities": {
+ "input": [
+ "image",
+ "text",
+ "video"
+ ],
+ "output": [
+ "text"
+ ]
+ },
+ "capabilities": [
+ "streaming",
+ "function_calling"
+ ],
+ "pricing": {
+ "text_tokens": {
+ "standard": {
+ "input_per_million": 0.3,
+ "output_per_million": 0.8999999999999999,
+ "cache_read_input_per_million": 0.049999999999999996
+ }
+ }
+ },
+ "metadata": {
+ "description": "GLM-4.6V is a large multimodal model designed for high-fidelity visual understanding and long-context reasoning across images, documents, and mixed media. It supports up to 128K tokens, processes complex page layouts...",
+ "architecture": {
+ "modality": "text+image+video->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "video"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 131072,
+ "max_completion_tokens": 24000,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "max_tokens",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "seed",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ]
+ }
+ },
{
"id": "z-ai/glm-4.7",
"name": "GLM-4.7",
"provider": "openrouter",
"family": "glm",
- "created_at": "2025-12-22 00:00:00 +0530",
+ "created_at": "2025-12-22 00:00:00 UTC",
"context_window": 204800,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -22306,18 +57156,59 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.6,
"output_per_million": 2.2,
- "cached_input_per_million": 0.11
+ "cache_read_input_per_million": 0.11
}
}
},
"metadata": {
+ "description": "GLM-4.7 is Z.ai’s latest flagship model, featuring upgrades in two key areas: enhanced programming capabilities and more stable multi-step reasoning/execution. It demonstrates significant improvements in executing complex agent tasks while...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 202752,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -22344,7 +57235,7 @@
"name": "GLM-4.7-Flash",
"provider": "openrouter",
"family": "glm",
- "created_at": "2026-01-19 00:00:00 +0530",
+ "created_at": "2026-01-19 00:00:00 UTC",
"context_window": 200000,
"max_output_tokens": 65535,
"knowledge_cutoff": null,
@@ -22359,7 +57250,9 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
@@ -22370,6 +57263,43 @@
}
},
"metadata": {
+ "description": "As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning,...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 202752,
+ "max_completion_tokens": 16384,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -22394,7 +57324,7 @@
"name": "GLM-5",
"provider": "openrouter",
"family": "glm",
- "created_at": "2026-02-12 00:00:00 +0530",
+ "created_at": "2026-02-12 00:00:00 UTC",
"context_window": 202752,
"max_output_tokens": 131000,
"knowledge_cutoff": null,
@@ -22409,18 +57339,59 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 1,
"output_per_million": 3.2,
- "cached_input_per_million": 0.2
+ "cache_read_input_per_million": 0.2
}
}
},
"metadata": {
+ "description": "GLM-5 is Z.ai’s flagship open-source foundation model engineered for complex systems design and long-horizon agent workflows. Built for expert developers, it delivers production-grade performance on large-scale programming tasks, rivaling leading...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 202752,
+ "max_completion_tokens": null,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -22446,7 +57417,7 @@
"name": "GLM-5-Turbo",
"provider": "openrouter",
"family": "glm",
- "created_at": "2026-03-16 00:00:00 +0530",
+ "created_at": "2026-03-16 00:00:00 UTC",
"context_window": 202752,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -22461,18 +57432,56 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 0.96,
"output_per_million": 3.2,
- "cached_input_per_million": 0.192
+ "cache_read_input_per_million": 0.192
}
}
},
"metadata": {
+ "description": "GLM-5 Turbo is a new model from Z.ai designed for fast inference and strong performance in agent-driven environments such as OpenClaw scenarios. It is deeply optimized for real-world agent workflows...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 202752,
+ "max_completion_tokens": 131072,
+ "is_moderated": false
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+ "per_request_limits": null,
+ "supported_parameters": [
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+ "include_reasoning",
+ "logit_bias",
+ "max_tokens",
+ "min_p",
+ "presence_penalty",
+ "reasoning",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": false,
@@ -22499,7 +57508,7 @@
"name": "GLM-5.1",
"provider": "openrouter",
"family": "glm",
- "created_at": "2026-04-07 00:00:00 +0530",
+ "created_at": "2026-04-07 00:00:00 UTC",
"context_window": 202752,
"max_output_tokens": 131072,
"knowledge_cutoff": null,
@@ -22514,18 +57523,61 @@
"capabilities": [
"function_calling",
"structured_output",
- "reasoning"
+ "reasoning",
+ "streaming",
+ "predicted_outputs"
],
"pricing": {
"text_tokens": {
"standard": {
"input_per_million": 1.4,
"output_per_million": 4.4,
- "cached_input_per_million": 0.26
+ "cache_read_input_per_million": 0.26
}
}
},
"metadata": {
+ "description": "GLM-5.1 delivers a major leap in coding capability, with particularly significant gains in handling long-horizon tasks. Unlike previous models built around minute-level interactions, GLM-5.1 can work independently and continuously on...",
+ "architecture": {
+ "modality": "text->text",
+ "input_modalities": [
+ "text"
+ ],
+ "output_modalities": [
+ "text"
+ ],
+ "tokenizer": "Other",
+ "instruct_type": null
+ },
+ "top_provider": {
+ "context_length": 202752,
+ "max_completion_tokens": 65535,
+ "is_moderated": false
+ },
+ "per_request_limits": null,
+ "supported_parameters": [
+ "frequency_penalty",
+ "include_reasoning",
+ "logit_bias",
+ "logprobs",
+ "max_tokens",
+ "min_p",
+ "parallel_tool_calls",
+ "presence_penalty",
+ "reasoning",
+ "reasoning_effort",
+ "repetition_penalty",
+ "response_format",
+ "seed",
+ "stop",
+ "structured_outputs",
+ "temperature",
+ "tool_choice",
+ "tools",
+ "top_k",
+ "top_logprobs",
+ "top_p"
+ ],
"source": "models.dev",
"provider_id": "openrouter",
"open_weights": true,
@@ -22546,12 +57598,639 @@
}
}
},
+ {
+ "id": "z-ai/glm-5v-turbo",
+ "name": "Z.ai: GLM 5V Turbo",
+ "provider": "openrouter",
+ "family": "z-ai",
+ "created_at": "2026-04-01 16:37:38 UTC",
+ "context_window": 202752,
+ "max_output_tokens": 131072,
+ "knowledge_cutoff": null,
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+ "function_calling",
+ "structured_output"
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+ "output_per_million": 4.0,
+ "cache_read_input_per_million": 0.24
+ }
+ }
+ },
+ "metadata": {
+ "description": "GLM-5V-Turbo is Z.ai’s first native multimodal agent foundation model, built for vision-based coding and agent-driven tasks. It natively handles image, video, and text inputs, excels at long-horizon planning, complex coding,...",
+ "architecture": {
+ "modality": "text+image+video->text",
+ "input_modalities": [
+ "image",
+ "text",
+ "video"
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+ "output_modalities": [
+ "text"
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+ "instruct_type": null
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+ "response_format",
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+ "tools",
+ "top_p"
+ ]
+ }
+ },
+ {
+ "id": "~anthropic/claude-haiku-latest",
+ "name": "Anthropic Claude Haiku Latest",
+ "provider": "openrouter",
+ "family": "~anthropic",
+ "created_at": "2026-04-27 19:34:52 UTC",
+ "context_window": 200000,
+ "max_output_tokens": 64000,
+ "knowledge_cutoff": null,
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+ "output_per_million": 5.0,
+ "cache_read_input_per_million": 0.09999999999999999
+ }
+ }
+ },
+ "metadata": {
+ "description": "This model always redirects to the latest model in the Anthropic Claude Haiku family.",
+ "architecture": {
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+ "input_modalities": [
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+ "name": "Anthropic: Claude Opus Latest",
+ "provider": "openrouter",
+ "family": "~anthropic",
+ "created_at": "2026-04-21 18:16:01 UTC",
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+ "cache_read_input_per_million": 0.5
+ }
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+ "metadata": {
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+ "architecture": {
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+ "name": "Anthropic Claude Sonnet Latest",
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+ "cache_read_input_per_million": 0.3
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+ "family": "~google",
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+ "family": "~moonshotai",
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+ "description": "This model always redirects to the latest model in the MoonshotAI Kimi family.",
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+ "family": "~openai",
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- "created_at": "2024-01-01 00:00:00 +0530",
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@@ -22563,7 +58242,9 @@
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@@ -22595,7 +58276,7 @@
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@@ -22685,12 +58366,39 @@
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"provider": "vertexai",
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@@ -23479,12 +60286,38 @@
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"provider": "vertexai",
"family": "gemini-flash",
- "created_at": "2025-12-17 00:00:00 +0530",
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@@ -23600,11 +60439,68 @@
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- "family": "gemini-pro",
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@@ -23664,7 +60629,7 @@
"name": "Gemini 3.1 Pro Preview Custom Tools",
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@@ -23762,12 +60730,82 @@
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{
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"name": "Gemini Flash Latest",
"provider": "vertexai",
"family": "gemini-flash",
- "created_at": "2025-09-25 00:00:00 +0530",
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- "family": "llama",
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@@ -24228,37 +61274,239 @@
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