MiscSubjects

Collection

Mistral AI

27 model catalog entries

Mistral Large 4
Mistral AIMistral Large 4
mistralai/mistral-large-4-1t-a52b
Mistral Large 4 from Mistral AI, a 1T-total / 52B-active granular MoE for text and image input with reasoning, function calling and structured outputs, served…
inspect — the catalog entry
{
  "name": "Mistral Large 4",
  "publisher": "mistralai",
  "labels": [
    "Multimodal",
    "Reasoning",
    "Chat",
    "Text-to-Text",
    "Image-to-Text",
    "Free Endpoint",
    "Large Language Models",
    "Tool Use"
  ],
  "attributes": {
    "AVAILABLE": "false",
    "last_month_download_count": "0",
    "lastMonthApiInvocationCount": "608726",
    "lastMonthDownloadCount": "0",
    "logo": "https://assets.ngc.nvidia.com/products/api-catalog/images/mistral-large-4-1t-a52b.jpg",
    "PREVIEW": "true",
    "last_month_api_invocation_count": "1277246"
  },
  "id": "mistralai/mistral-large-4-1t-a52b",
  "description": "Mistral Large 4 from Mistral AI, a 1T-total / 52B-active granular MoE for text and image input with reasoning, function calling and structured outputs, served…",
  "context_length": null
}
Mistral: Mistral Large 4
Mistral AIMistral Large 4
mistralai/mistral-large-4-0
2026-10-06text+image->textreasoning: high / none
Intelligence index
26.1
Artificial Analysis
Design Arena
1231 Elo · #19
svg · 45.3% wins
Input
$0.70
per 1M tokens
Output
$2.10
per 1M tokens
Cached input
$0.07
per 1M tokens
Context
1.0M
tokens it reads
Max output
262K
tokens it writes
Mistral Large 4 is a frontier multimodal (text and image input) model from Mistral AI built for reasoning, coding, and agentic workloads. It offers a 1M-token context window with up...
inspect — the catalog entry
{
  "id": "mistralai/mistral-large-4-0",
  "canonical_slug": "mistralai/mistral-large-4-0-20261006",
  "hugging_face_id": "mistralai/Mistral-Large-4-1T-A52B",
  "name": "Mistral: Mistral Large 4",
  "created": 1791294122,
  "description": "Mistral Large 4 is a frontier multimodal (text and image input) model from Mistral AI built for reasoning, coding, and agentic workloads. It offers a 1M-token context window with up...",
  "context_length": 1048576,
  "architecture": {
    "modality": "text+image->text",
    "input_modalities": [
      "text",
      "image"
    ],
    "output_modalities": [
      "text"
    ],
    "tokenizer": "Mistral",
    "instruct_type": null
  },
  "pricing": {
    "prompt": "0.0000007",
    "completion": "0.0000021",
    "input_cache_read": "0.00000007"
  },
  "top_provider": {
    "context_length": 1048576,
    "max_completion_tokens": 262144,
    "is_moderated": false
  },
  "per_request_limits": null,
  "supported_parameters": [
    "frequency_penalty",
    "include_reasoning",
    "logprobs",
    "max_tokens",
    "presence_penalty",
    "reasoning",
    "reasoning_effort",
    "response_format",
    "seed",
    "stop",
    "structured_outputs",
    "temperature",
    "tool_choice",
    "tools",
    "top_logprobs",
    "top_p"
  ],
  "default_parameters": {},
  "supported_voices": null,
  "knowledge_cutoff": null,
  "expiration_date": null,
  "links": {
    "details": "/api/v1/models/mistralai/mistral-large-4-0-20261006/endpoints"
  },
  "endpoints": [
    "/api/v1/chat/completions",
    "/api/v1/completions",
    "/api/v1/messages",
    "/api/v1/responses"
  ],
  "benchmarks": {
    "design_arena": [
      {
        "arena": "models",
        "category": "3d",
        "elo": 1250,
        "win_rate": 45.2,
        "rank": 34
      },
      {
        "arena": "models",
        "category": "asciiart",
        "elo": 1206,
        "win_rate": 43.5,
        "rank": 25
      },
      {
        "arena": "models",
        "category": "codecategories",
        "elo": 1258,
        "win_rate": 46.6,
        "rank": 40
      },
      {
        "arena": "models",
        "category": "dataviz",
        "elo": 1275,
        "win_rate": 51,
        "rank": 25
      },
      {
        "arena": "models",
        "category": "gamedev",
        "elo": 1225,
        "win_rate": 42.2,
        "rank": 45
      },
      {
        "arena": "models",
        "category": "svg",
        "elo": 1231,
        "win_rate": 45.3,
        "rank": 19
      },
      {
        "arena": "models",
        "category": "uicomponent",
        "elo": 1269,
        "win_rate": 47.6,
        "rank": 31
      },
      {
        "arena": "models",
        "category": "website",
        "elo": 1256,
        "win_rate": 47.3,
        "rank": 42
      }
    ],
    "artificial_analysis": {
      "intelligence_index": 26.1,
      "coding_index": null,
      "agentic_index": null
    }
  },
  "reasoning": {
    "mandatory": false,
    "default_enabled": true,
    "supported_efforts": [
      "high",
      "none"
    ],
    "default_effort": "high"
  }
}
Mistral: Mistral Medium 3.5
Mistral AIMistral Medium 3.5
mistralai/mistral-medium-3-5
2026-04-30text+image+file->textreasoning: high / none
Coding index
46.9
Artificial Analysis
Agentic index
7
Artificial Analysis
Input
$1.50
per 1M tokens
Output
$7.50
per 1M tokens
Context
262K
tokens it reads
Max output
210K
tokens it writes
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...
inspect — the catalog entry
{
  "id": "mistralai/mistral-medium-3-5",
  "canonical_slug": "mistralai/mistral-medium-3.5-20260430",
  "hugging_face_id": null,
  "name": "Mistral: Mistral Medium 3.5",
  "created": 1777570439,
  "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...",
  "context_length": 262144,
  "architecture": {
    "modality": "text+image+file->text",
    "input_modalities": [
      "text",
      "image",
      "file"
    ],
    "output_modalities": [
      "text"
    ],
    "tokenizer": "Mistral",
    "instruct_type": null
  },
  "pricing": {
    "prompt": "0.0000015",
    "completion": "0.0000075"
  },
  "top_provider": {
    "context_length": 262144,
    "max_completion_tokens": 209715,
    "is_moderated": false
  },
  "per_request_limits": null,
  "supported_parameters": [
    "frequency_penalty",
    "include_reasoning",
    "max_tokens",
    "presence_penalty",
    "reasoning",
    "reasoning_effort",
    "response_format",
    "seed",
    "stop",
    "structured_outputs",
    "temperature",
    "tool_choice",
    "tools",
    "top_p"
  ],
  "default_parameters": {
    "temperature": null,
    "top_p": null,
    "top_k": null,
    "frequency_penalty": null,
    "presence_penalty": null,
    "repetition_penalty": null
  },
  "supported_voices": null,
  "knowledge_cutoff": null,
  "expiration_date": null,
  "links": {
    "details": "/api/v1/models/mistralai/mistral-medium-3.5-20260430/endpoints"
  },
  "endpoints": [
    "/api/v1/chat/completions",
    "/api/v1/completions",
    "/api/v1/messages",
    "/api/v1/responses"
  ],
  "benchmarks": {
    "design_arena": [],
    "artificial_analysis": {
      "intelligence_index": null,
      "coding_index": 46.9,
      "agentic_index": 7
    }
  },
  "reasoning": {
    "mandatory": false,
    "supported_efforts": [
      "high",
      "none"
    ],
    "default_effort": "high"
  }
}
Mistral: Mistral Medium 3.5 (batch)
Mistral AIMistral Medium 3.5 (batch)
mistralai/mistral-medium-3-5:batch
2026-04-30text+image+file->textreasoning: high / none
Coding index
46.9
Artificial Analysis
Agentic index
7
Artificial Analysis
Input
$0.75
per 1M tokens
Output
$3.75
per 1M tokens
Context
262K
tokens it reads
Max output
210K
tokens it writes
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...
inspect — the catalog entry
{
  "id": "mistralai/mistral-medium-3-5:batch",
  "canonical_slug": "mistralai/mistral-medium-3.5-20260430",
  "hugging_face_id": null,
  "name": "Mistral: Mistral Medium 3.5 (batch)",
  "created": 1777570439,
  "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...",
  "context_length": 262144,
  "architecture": {
    "modality": "text+image+file->text",
    "input_modalities": [
      "text",
      "image",
      "file"
    ],
    "output_modalities": [
      "text"
    ],
    "tokenizer": "Mistral",
    "instruct_type": null
  },
  "pricing": {
    "prompt": "0.00000075",
    "completion": "0.00000375"
  },
  "top_provider": {
    "context_length": 262144,
    "max_completion_tokens": 209715,
    "is_moderated": false
  },
  "per_request_limits": null,
  "supported_parameters": [
    "frequency_penalty",
    "include_reasoning",
    "max_tokens",
    "presence_penalty",
    "reasoning",
    "reasoning_effort",
    "response_format",
    "seed",
    "stop",
    "structured_outputs",
    "temperature",
    "tool_choice",
    "tools",
    "top_p"
  ],
  "default_parameters": {
    "temperature": null,
    "top_p": null,
    "top_k": null,
    "frequency_penalty": null,
    "presence_penalty": null,
    "repetition_penalty": null
  },
  "supported_voices": null,
  "knowledge_cutoff": null,
  "expiration_date": null,
  "links": {
    "details": "/api/v1/models/mistralai/mistral-medium-3.5-20260430/endpoints"
  },
  "endpoints": [
    "/api/v1/batches"
  ],
  "benchmarks": {
    "design_arena": [],
    "artificial_analysis": {
      "intelligence_index": null,
      "coding_index": 46.9,
      "agentic_index": 7
    }
  },
  "reasoning": {
    "mandatory": false,
    "supported_efforts": [
      "high",
      "none"
    ],
    "default_effort": "high"
  }
}
Mistral: Mistral Small 4
Mistral AIMistral Small 4
mistralai/mistral-small-2603
2026-03-16text+image->textreasoning: high / none
Intelligence index
4.3
Artificial Analysis
Coding index
26.6
Artificial Analysis
Agentic index
0.8
Artificial Analysis
Input
$0.15
per 1M tokens
Output
$0.60
per 1M tokens
Cached input
$0.01
per 1M tokens
Context
262K
tokens it reads
Max output
210K
tokens it writes
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...
inspect — the catalog entry
{
  "id": "mistralai/mistral-small-2603",
  "canonical_slug": "mistralai/mistral-small-2603",
  "hugging_face_id": "mistralai/Mistral-Small-4-119B-2603",
  "name": "Mistral: Mistral Small 4",
  "created": 1773695685,
  "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...",
  "context_length": 262144,
  "architecture": {
    "modality": "text+image->text",
    "input_modalities": [
      "text",
      "image"
    ],
    "output_modalities": [
      "text"
    ],
    "tokenizer": "Mistral",
    "instruct_type": null
  },
  "pricing": {
    "prompt": "0.00000015",
    "completion": "0.0000006",
    "input_cache_read": "0.000000015"
  },
  "top_provider": {
    "context_length": 262144,
    "max_completion_tokens": 209715,
    "is_moderated": false
  },
  "per_request_limits": null,
  "supported_parameters": [
    "frequency_penalty",
    "include_reasoning",
    "max_tokens",
    "presence_penalty",
    "reasoning",
    "reasoning_effort",
    "response_format",
    "seed",
    "stop",
    "structured_outputs",
    "temperature",
    "tool_choice",
    "tools",
    "top_p"
  ],
  "default_parameters": {
    "temperature": null,
    "top_p": null,
    "top_k": null,
    "frequency_penalty": null,
    "presence_penalty": null,
    "repetition_penalty": null
  },
  "supported_voices": null,
  "knowledge_cutoff": null,
  "expiration_date": null,
  "links": {
    "details": "/api/v1/models/mistralai/mistral-small-2603/endpoints"
  },
  "endpoints": [
    "/api/v1/chat/completions",
    "/api/v1/completions",
    "/api/v1/messages",
    "/api/v1/responses"
  ],
  "benchmarks": {
    "design_arena": [],
    "artificial_analysis": {
      "intelligence_index": 4.3,
      "coding_index": 26.6,
      "agentic_index": 0.8
    }
  },
  "reasoning": {
    "mandatory": false,
    "default_enabled": false,
    "supported_efforts": [
      "high",
      "none"
    ],
    "default_effort": "high"
  }
}
Mistral: Devstral 2 2512
Mistral AIDevstral 2 2512
mistralai/devstral-2512
2025-12-09text+file->text
Coding index
31.3
Artificial Analysis
Agentic index
2.3
Artificial Analysis
Input
$0.40
per 1M tokens
Output
$2
per 1M tokens
Cached input
$0.04
per 1M tokens
Context
262K
tokens it reads
Max output
210K
tokens it writes
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...
inspect — the catalog entry
{
  "id": "mistralai/devstral-2512",
  "canonical_slug": "mistralai/devstral-2512",
  "hugging_face_id": "mistralai/Devstral-2-123B-Instruct-2512",
  "name": "Mistral: Devstral 2 2512",
  "created": 1765285419,
  "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...",
  "context_length": 262144,
  "architecture": {
    "modality": "text+file->text",
    "input_modalities": [
      "text",
      "file"
    ],
    "output_modalities": [
      "text"
    ],
    "tokenizer": "Mistral",
    "instruct_type": null
  },
  "pricing": {
    "prompt": "0.0000004",
    "completion": "0.000002",
    "input_cache_read": "0.00000004"
  },
  "top_provider": {
    "context_length": 262144,
    "max_completion_tokens": 209715,
    "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"
  ],
  "default_parameters": {
    "temperature": 0.3,
    "top_p": null,
    "frequency_penalty": null
  },
  "supported_voices": null,
  "knowledge_cutoff": null,
  "expiration_date": null,
  "links": {
    "details": "/api/v1/models/mistralai/devstral-2512/endpoints"
  },
  "endpoints": [
    "/api/v1/chat/completions",
    "/api/v1/completions",
    "/api/v1/messages",
    "/api/v1/responses"
  ],
  "benchmarks": {
    "design_arena": [],
    "artificial_analysis": {
      "intelligence_index": null,
      "coding_index": 31.3,
      "agentic_index": 2.3
    }
  },
  "reasoning": null
}
Mistral: Ministral 3 14B 2512
Mistral AIMinistral 3 14B 2512
mistralai/ministral-14b-2512
2025-12-02text+image->text
Coding index
14.4
Artificial Analysis
Agentic index
1.1
Artificial Analysis
Design Arena
987 Elo · #116
3d · 39.6% wins
Input
$0.20
per 1M tokens
Output
$0.20
per 1M tokens
Cached input
$0.02
per 1M tokens
Context
262K
tokens it reads
Max output
210K
tokens it writes
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...
inspect — the catalog entry
{
  "id": "mistralai/ministral-14b-2512",
  "canonical_slug": "mistralai/ministral-14b-2512",
  "hugging_face_id": "mistralai/Ministral-3-14B-Instruct-2512",
  "name": "Mistral: Ministral 3 14B 2512",
  "created": 1764681735,
  "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...",
  "context_length": 262144,
  "architecture": {
    "modality": "text+image->text",
    "input_modalities": [
      "text",
      "image"
    ],
    "output_modalities": [
      "text"
    ],
    "tokenizer": "Mistral",
    "instruct_type": null
  },
  "pricing": {
    "prompt": "0.0000002",
    "completion": "0.0000002",
    "input_cache_read": "0.00000002"
  },
  "top_provider": {
    "context_length": 262144,
    "max_completion_tokens": 209715,
    "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"
  ],
  "default_parameters": {
    "temperature": 0.3,
    "top_p": null,
    "frequency_penalty": null
  },
  "supported_voices": null,
  "knowledge_cutoff": null,
  "expiration_date": null,
  "links": {
    "details": "/api/v1/models/mistralai/ministral-14b-2512/endpoints"
  },
  "endpoints": [
    "/api/v1/chat/completions",
    "/api/v1/completions",
    "/api/v1/messages",
    "/api/v1/responses"
  ],
  "benchmarks": {
    "design_arena": [
      {
        "arena": "models",
        "category": "3d",
        "elo": 987,
        "win_rate": 39.6,
        "rank": 116
      },
      {
        "arena": "models",
        "category": "codecategories",
        "elo": 1063,
        "win_rate": 44,
        "rank": 116
      },
      {
        "arena": "models",
        "category": "gamedev",
        "elo": 1038,
        "win_rate": 43.6,
        "rank": 117
      },
      {
        "arena": "models",
        "category": "website",
        "elo": 1081,
        "win_rate": 44.8,
        "rank": 116
      }
    ],
    "artificial_analysis": {
      "intelligence_index": null,
      "coding_index": 14.4,
      "agentic_index": 1.1
    }
  },
  "reasoning": null
}
Mistral: Ministral 3 8B 2512
Mistral AIMinistral 3 8B 2512
mistralai/ministral-8b-2512
2025-12-02text+image->text
Coding index
9.7
Artificial Analysis
Agentic index
0.6
Artificial Analysis
Design Arena
1029 Elo · #111
3d · 46.2% wins
Input
$0.15
per 1M tokens
Output
$0.15
per 1M tokens
Cached input
$0.01
per 1M tokens
Context
262K
tokens it reads
Max output
210K
tokens it writes
A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.
inspect — the catalog entry
{
  "id": "mistralai/ministral-8b-2512",
  "canonical_slug": "mistralai/ministral-8b-2512",
  "hugging_face_id": "mistralai/Ministral-3-8B-Instruct-2512",
  "name": "Mistral: Ministral 3 8B 2512",
  "created": 1764681654,
  "description": "A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.",
  "context_length": 262144,
  "architecture": {
    "modality": "text+image->text",
    "input_modalities": [
      "text",
      "image"
    ],
    "output_modalities": [
      "text"
    ],
    "tokenizer": "Mistral",
    "instruct_type": null
  },
  "pricing": {
    "prompt": "0.00000015",
    "completion": "0.00000015",
    "input_cache_read": "0.000000015"
  },
  "top_provider": {
    "context_length": 262144,
    "max_completion_tokens": 209715,
    "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"
  ],
  "default_parameters": {
    "temperature": 0.3,
    "top_p": null,
    "frequency_penalty": null
  },
  "supported_voices": null,
  "knowledge_cutoff": null,
  "expiration_date": null,
  "links": {
    "details": "/api/v1/models/mistralai/ministral-8b-2512/endpoints"
  },
  "endpoints": [
    "/api/v1/chat/completions",
    "/api/v1/completions",
    "/api/v1/messages",
    "/api/v1/responses"
  ],
  "benchmarks": {
    "design_arena": [
      {
        "arena": "models",
        "category": "3d",
        "elo": 1029,
        "win_rate": 46.2,
        "rank": 111
      },
      {
        "arena": "models",
        "category": "codecategories",
        "elo": 1051,
        "win_rate": 42.9,
        "rank": 118
      },
      {
        "arena": "models",
        "category": "gamedev",
        "elo": 990,
        "win_rate": 38.7,
        "rank": 125
      },
      {
        "arena": "models",
        "category": "website",
        "elo": 1063,
        "win_rate": 42.9,
        "rank": 118
      }
    ],
    "artificial_analysis": {
      "intelligence_index": null,
      "coding_index": 9.7,
      "agentic_index": 0.6
    }
  },
  "reasoning": null
}
Mistral: Ministral 3 3B 2512
Mistral AIMinistral 3 3B 2512
mistralai/ministral-3b-2512
2025-12-02text+image->text
Coding index
4.8
Artificial Analysis
Agentic index
0.8
Artificial Analysis
Design Arena
960 Elo · #121
3d · 35.9% wins
Input
$0.10
per 1M tokens
Output
$0.10
per 1M tokens
Cached input
$0.01
per 1M tokens
Context
131K
tokens it reads
Max output
105K
tokens it writes
The smallest model in the Ministral 3 family, Ministral 3 3B is a powerful, efficient tiny language model with vision capabilities.
inspect — the catalog entry
{
  "id": "mistralai/ministral-3b-2512",
  "canonical_slug": "mistralai/ministral-3b-2512",
  "hugging_face_id": "mistralai/Ministral-3-3B-Instruct-2512",
  "name": "Mistral: Ministral 3 3B 2512",
  "created": 1764681560,
  "description": "The smallest model in the Ministral 3 family, Ministral 3 3B is a powerful, efficient tiny language model with vision capabilities.",
  "context_length": 131072,
  "architecture": {
    "modality": "text+image->text",
    "input_modalities": [
      "text",
      "image"
    ],
    "output_modalities": [
      "text"
    ],
    "tokenizer": "Mistral",
    "instruct_type": null
  },
  "pricing": {
    "prompt": "0.0000001",
    "completion": "0.0000001",
    "input_cache_read": "0.00000001"
  },
  "top_provider": {
    "context_length": 131072,
    "max_completion_tokens": 104857,
    "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"
  ],
  "default_parameters": {
    "temperature": 0.3,
    "top_p": null,
    "frequency_penalty": null
  },
  "supported_voices": null,
  "knowledge_cutoff": null,
  "expiration_date": null,
  "links": {
    "details": "/api/v1/models/mistralai/ministral-3b-2512/endpoints"
  },
  "endpoints": [
    "/api/v1/chat/completions",
    "/api/v1/completions",
    "/api/v1/messages",
    "/api/v1/responses"
  ],
  "benchmarks": {
    "design_arena": [
      {
        "arena": "models",
        "category": "3d",
        "elo": 960,
        "win_rate": 35.9,
        "rank": 121
      },
      {
        "arena": "models",
        "category": "codecategories",
        "elo": 1008,
        "win_rate": 37.3,
        "rank": 127
      },
      {
        "arena": "models",
        "category": "gamedev",
        "elo": 947,
        "win_rate": 33,
        "rank": 133
      },
      {
        "arena": "models",
        "category": "website",
        "elo": 1026,
        "win_rate": 38.2,
        "rank": 129
      }
    ],
    "artificial_analysis": {
      "intelligence_index": null,
      "coding_index": 4.8,
      "agentic_index": 0.8
    }
  },
  "reasoning": null
}
Mistral: Mistral Large 3 2512
Mistral AIMistral Large 3 2512
mistralai/mistral-large-2512
2025-12-01text+image+file->text
Coding index
20.1
Artificial Analysis
Agentic index
1
Artificial Analysis
Design Arena
1066 Elo · #69
asciiart · 40.3% wins
Input
$0.50
per 1M tokens
Output
$1.50
per 1M tokens
Cached input
$0.05
per 1M tokens
Context
262K
tokens it reads
Max output
210K
tokens it writes
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.
inspect — the catalog entry
{
  "id": "mistralai/mistral-large-2512",
  "canonical_slug": "mistralai/mistral-large-2512",
  "hugging_face_id": null,
  "name": "Mistral: Mistral Large 3 2512",
  "created": 1764624472,
  "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.",
  "context_length": 262144,
  "architecture": {
    "modality": "text+image+file->text",
    "input_modalities": [
      "text",
      "image",
      "file"
    ],
    "output_modalities": [
      "text"
    ],
    "tokenizer": "Mistral",
    "instruct_type": null
  },
  "pricing": {
    "prompt": "0.0000005",
    "completion": "0.0000015",
    "input_cache_read": "0.00000005"
  },
  "top_provider": {
    "context_length": 262144,
    "max_completion_tokens": 209715,
    "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"
  ],
  "default_parameters": {
    "temperature": 0.0645,
    "top_p": null,
    "frequency_penalty": null
  },
  "supported_voices": null,
  "knowledge_cutoff": null,
  "expiration_date": null,
  "links": {
    "details": "/api/v1/models/mistralai/mistral-large-2512/endpoints"
  },
  "endpoints": [
    "/api/v1/chat/completions",
    "/api/v1/completions",
    "/api/v1/messages",
    "/api/v1/responses"
  ],
  "benchmarks": {
    "design_arena": [
      {
        "arena": "models",
        "category": "3d",
        "elo": 1096,
        "win_rate": 46.9,
        "rank": 91
      },
      {
        "arena": "models",
        "category": "asciiart",
        "elo": 1066,
        "win_rate": 40.3,
        "rank": 69
      },
      {
        "arena": "models",
        "category": "codecategories",
        "elo": 1140,
        "win_rate": 47.6,
        "rank": 95
      },
      {
        "arena": "models",
        "category": "dataviz",
        "elo": 1136,
        "win_rate": 45.7,
        "rank": 88
      },
      {
        "arena": "models",
        "category": "gamedev",
        "elo": 1080,
        "win_rate": 41.5,
        "rank": 105
      },
      {
        "arena": "models",
        "category": "svg",
        "elo": 989,
        "win_rate": 38,
        "rank": 91
      },
      {
        "arena": "models",
        "category": "uicomponent",
        "elo": 1097,
        "win_rate": 43,
        "rank": 97
      },
      {
        "arena": "models",
        "category": "website",
        "elo": 1162,
        "win_rate": 49.5,
        "rank": 87
      }
    ],
    "artificial_analysis": {
      "intelligence_index": null,
      "coding_index": 20.1,
      "agentic_index": 1
    }
  },
  "reasoning": null
}
Mistral: Voxtral Small 24B 2507
Mistral AIVoxtral Small 24B 2507
mistralai/voxtral-small-24b-2507
2025-10-30text+file+audio->text
Input
$0.10
per 1M tokens
Output
$0.30
per 1M tokens
Cached input
$0.01
per 1M tokens
Context
33K
tokens it reads
Max output
26K
tokens it writes
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...
inspect — the catalog entry
{
  "id": "mistralai/voxtral-small-24b-2507",
  "canonical_slug": "mistralai/voxtral-small-24b-2507",
  "hugging_face_id": "mistralai/Voxtral-Small-24B-2507",
  "name": "Mistral: Voxtral Small 24B 2507",
  "created": 1761835144,
  "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...",
  "context_length": 32768,
  "architecture": {
    "modality": "text+file+audio->text",
    "input_modalities": [
      "text",
      "audio",
      "file"
    ],
    "output_modalities": [
      "text"
    ],
    "tokenizer": "Mistral",
    "instruct_type": null
  },
  "pricing": {
    "prompt": "0.0000001",
    "completion": "0.0000003",
    "audio": "0.0001",
    "input_cache_read": "0.00000001"
  },
  "top_provider": {
    "context_length": 32768,
    "max_completion_tokens": 26214,
    "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"
  ],
  "default_parameters": {
    "temperature": 0.2,
    "top_p": 0.95,
    "frequency_penalty": null
  },
  "supported_voices": null,
  "knowledge_cutoff": null,
  "expiration_date": null,
  "links": {
    "details": "/api/v1/models/mistralai/voxtral-small-24b-2507/endpoints"
  },
  "endpoints": [
    "/api/v1/chat/completions",
    "/api/v1/completions",
    "/api/v1/messages",
    "/api/v1/responses"
  ],
  "benchmarks": null,
  "reasoning": null
}
Mistral: Mistral Medium 3.1
Mistral AIMistral Medium 3.1
mistralai/mistral-medium-3.1
2025-08-13text+image+file->textknows up to 2025-06-30
Coding index
20.5
Artificial Analysis
Agentic index
1.9
Artificial Analysis
Design Arena
995 Elo · #73
asciiart · 30.8% wins
Input
$0.40
per 1M tokens
Output
$2
per 1M tokens
Cached input
$0.04
per 1M tokens
Context
131K
tokens it reads
Max output
105K
tokens it writes
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...
inspect — the catalog entry
{
  "id": "mistralai/mistral-medium-3.1",
  "canonical_slug": "mistralai/mistral-medium-3.1",
  "hugging_face_id": null,
  "name": "Mistral: Mistral Medium 3.1",
  "created": 1755095639,
  "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...",
  "context_length": 131072,
  "architecture": {
    "modality": "text+image+file->text",
    "input_modalities": [
      "text",
      "image",
      "file"
    ],
    "output_modalities": [
      "text"
    ],
    "tokenizer": "Mistral",
    "instruct_type": null
  },
  "pricing": {
    "prompt": "0.0000004",
    "completion": "0.000002",
    "input_cache_read": "0.00000004"
  },
  "top_provider": {
    "context_length": 131072,
    "max_completion_tokens": 104857,
    "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"
  ],
  "default_parameters": {
    "temperature": 0.3
  },
  "supported_voices": null,
  "knowledge_cutoff": "2025-06-30",
  "expiration_date": null,
  "links": {
    "details": "/api/v1/models/mistralai/mistral-medium-3.1/endpoints"
  },
  "endpoints": [
    "/api/v1/chat/completions",
    "/api/v1/completions",
    "/api/v1/messages",
    "/api/v1/responses"
  ],
  "benchmarks": {
    "design_arena": [
      {
        "arena": "models",
        "category": "3d",
        "elo": 1078,
        "win_rate": 44.6,
        "rank": 99
      },
      {
        "arena": "models",
        "category": "asciiart",
        "elo": 995,
        "win_rate": 30.8,
        "rank": 73
      },
      {
        "arena": "models",
        "category": "codecategories",
        "elo": 1118,
        "win_rate": 45.1,
        "rank": 100
      },
      {
        "arena": "models",
        "category": "dataviz",
        "elo": 1144,
        "win_rate": 47.2,
        "rank": 84
      },
      {
        "arena": "models",
        "category": "gamedev",
        "elo": 1074,
        "win_rate": 40.8,
        "rank": 108
      },
      {
        "arena": "models",
        "category": "svg",
        "elo": 989,
        "win_rate": 38.2,
        "rank": 92
      },
      {
        "arena": "models",
        "category": "uicomponent",
        "elo": 1094,
        "win_rate": 43.6,
        "rank": 99
      },
      {
        "arena": "models",
        "category": "website",
        "elo": 1131,
        "win_rate": 46,
        "rank": 101
      }
    ],
    "artificial_analysis": {
      "intelligence_index": null,
      "coding_index": 20.5,
      "agentic_index": 1.9
    }
  },
  "reasoning": null
}
Mistral: Codestral 2508
Mistral AICodestral 2508
mistralai/codestral-2508
2025-08-01text+file->textknows up to 2025-03-31
Design Arena
1017 Elo · #112
3d · 45.4% wins
Input
$0.30
per 1M tokens
Output
$0.90
per 1M tokens
Cached input
$0.03
per 1M tokens
Context
256K
tokens it reads
Max output
205K
tokens it writes
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. [Blog Post](https://mistral.ai/news/codestral-25-08)
inspect — the catalog entry
{
  "id": "mistralai/codestral-2508",
  "canonical_slug": "mistralai/codestral-2508",
  "hugging_face_id": null,
  "name": "Mistral: Codestral 2508",
  "created": 1754079630,
  "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)",
  "context_length": 256000,
  "architecture": {
    "modality": "text+file->text",
    "input_modalities": [
      "text",
      "file"
    ],
    "output_modalities": [
      "text"
    ],
    "tokenizer": "Mistral",
    "instruct_type": null
  },
  "pricing": {
    "prompt": "0.0000003",
    "completion": "0.0000009",
    "input_cache_read": "0.00000003"
  },
  "top_provider": {
    "context_length": 256000,
    "max_completion_tokens": 204800,
    "is_moderated": false
  },
  "per_request_limits": null,
  "supported_parameters": [
    "frequency_penalty",
    "max_tokens",
    "prediction",
    "presence_penalty",
    "response_format",
    "seed",
    "stop",
    "structured_outputs",
    "temperature",
    "tool_choice",
    "tools",
    "top_p"
  ],
  "default_parameters": {
    "temperature": 0.3
  },
  "supported_voices": null,
  "knowledge_cutoff": "2025-03-31",
  "expiration_date": null,
  "links": {
    "details": "/api/v1/models/mistralai/codestral-2508/endpoints"
  },
  "endpoints": [
    "/api/v1/chat/completions",
    "/api/v1/completions",
    "/api/v1/messages",
    "/api/v1/responses"
  ],
  "benchmarks": {
    "design_arena": [
      {
        "arena": "models",
        "category": "codecategories",
        "elo": 1005,
        "win_rate": 38.5,
        "rank": 128
      },
      {
        "arena": "models",
        "category": "dataviz",
        "elo": 1017,
        "win_rate": 41.1,
        "rank": 115
      },
      {
        "arena": "models",
        "category": "gamedev",
        "elo": 966,
        "win_rate": 36.3,
        "rank": 129
      },
      {
        "arena": "models",
        "category": "uicomponent",
        "elo": 1012,
        "win_rate": 46.7,
        "rank": 117
      },
      {
        "arena": "models",
        "category": "website",
        "elo": 1011,
        "win_rate": 37.8,
        "rank": 131
      },
      {
        "arena": "models",
        "category": "3d",
        "elo": 1017,
        "win_rate": 45.4,
        "rank": 112
      }
    ]
  },
  "reasoning": null
}