MiscSubjects

Collection

MiniMax

19 model catalog entries

MiniMax: MiniMax M3.1 Flash
MiniMaxMiniMax M3.1 Flash
minimax/minimax-m3.1-flash
2026-10-19text+image+video->textreasoning: max / xhigh / high / medium / low
Intelligence index
29.1
Artificial Analysis
Input
$0.07
per 1M tokens
Output
$0.30
per 1M tokens
Cached input
$0.01
per 1M tokens
Context
1.0M
tokens it reads
Max output
524K
tokens it writes
MiniMax-M3.1-Flash is a multimodal model from MiniMax. Compared with M3, it delivers significant improvements across multiple benchmarks, particularly in complex agentic tasks, coding, and cybersecurity. It is built for complex,...
inspect — the catalog entry
{
  "id": "minimax/minimax-m3.1-flash",
  "canonical_slug": "minimax/minimax-m3.1-flash-20261019",
  "hugging_face_id": "MiniMaxAI/MiniMax-M3.1-Flash",
  "name": "MiniMax: MiniMax M3.1 Flash",
  "created": 1792379569,
  "description": "MiniMax-M3.1-Flash is a multimodal model from MiniMax. Compared with M3, it delivers significant improvements across multiple benchmarks, particularly in complex agentic tasks, coding, and cybersecurity. It is built for complex,...",
  "context_length": 1048576,
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    "supported_efforts": [
      "max",
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      "medium",
      "low"
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  }
}
MiniMax: MiniMax M3
MiniMaxMiniMax M3
minimax/minimax-m3
2026-05-31text+image+video->text
Intelligence index
18.9
Artificial Analysis
Coding index
58.6
Artificial Analysis
Agentic index
29.5
Artificial Analysis
Design Arena
1288 Elo · #3
pdf · 62.9% wins
Input
$0.30
per 1M tokens
Output
$1.20
per 1M tokens
Cached input
$0.06
per 1M tokens
Context
1.0M
tokens it reads
Max output
512K
tokens it writes
MiniMax-M3 is a multimodal foundation model from MiniMax. It supports text, image, and video inputs with text output, a 1M-token context window, and is suited for long-horizon agentic work, coding,...
inspect — the catalog entry
{
  "id": "minimax/minimax-m3",
  "canonical_slug": "minimax/minimax-m3-20260531",
  "hugging_face_id": "MiniMaxAI/Minimax-M3",
  "name": "MiniMax: MiniMax M3",
  "created": 1780245374,
  "description": "MiniMax-M3 is a multimodal foundation model from MiniMax. It supports text, image, and video inputs with text output, a 1M-token context window, and is suited for long-horizon agentic work, coding,...",
  "context_length": 1048576,
  "architecture": {
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  "links": {
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  "endpoints": [
    "/api/v1/chat/completions",
    "/api/v1/completions",
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  "benchmarks": {
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        "arena": "agents",
        "category": "agenticgamedev",
        "elo": 1114,
        "win_rate": 44.9,
        "rank": 18
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        "elo": 1197,
        "win_rate": 47.2,
        "rank": 19
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        "category": "htmlslides",
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        "win_rate": 46.7,
        "rank": 14
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        "win_rate": 46.4,
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        "elo": 1288,
        "win_rate": 62.9,
        "rank": 3
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        "win_rate": 47.5,
        "rank": 16
      },
      {
        "arena": "agents",
        "category": "spreadsheet",
        "elo": 1079,
        "win_rate": 45.8,
        "rank": 20
      },
      {
        "arena": "agents",
        "category": "webapps",
        "elo": 1193,
        "win_rate": 47.5,
        "rank": 24
      },
      {
        "arena": "models",
        "category": "3d",
        "elo": 1205,
        "win_rate": 50,
        "rank": 49
      },
      {
        "arena": "models",
        "category": "asciiart",
        "elo": 1155,
        "win_rate": 46.1,
        "rank": 43
      },
      {
        "arena": "models",
        "category": "codecategories",
        "elo": 1245,
        "win_rate": 50.6,
        "rank": 43
      },
      {
        "arena": "models",
        "category": "dataviz",
        "elo": 1234,
        "win_rate": 51.2,
        "rank": 45
      },
      {
        "arena": "models",
        "category": "gamedev",
        "elo": 1211,
        "win_rate": 45.6,
        "rank": 50
      },
      {
        "arena": "models",
        "category": "svg",
        "elo": 1157,
        "win_rate": 44.6,
        "rank": 46
      },
      {
        "arena": "models",
        "category": "uicomponent",
        "elo": 1241,
        "win_rate": 50.5,
        "rank": 44
      },
      {
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        "category": "website",
        "elo": 1256,
        "win_rate": 51.5,
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    ],
    "artificial_analysis": {
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}
MiniMax: MiniMax M2.7
MiniMaxMiniMax M2.7
minimax/minimax-m2.7
2026-03-18text->text
Coding index
52.6
Artificial Analysis
Agentic index
15.3
Artificial Analysis
Design Arena
1233 Elo · #46
dataviz · 52.3% wins
Input
$0.30
per 1M tokens
Output
$1.20
per 1M tokens
Cached input
$0.06
per 1M tokens
Context
205K
tokens it reads
Max output
131K
tokens it writes
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...
inspect — the catalog entry
{
  "id": "minimax/minimax-m2.7",
  "canonical_slug": "minimax/minimax-m2.7-20260318",
  "hugging_face_id": "MiniMaxAI/MiniMax-M2.7",
  "name": "MiniMax: MiniMax M2.7",
  "created": 1773836697,
  "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...",
  "context_length": 204800,
  "architecture": {
    "modality": "text->text",
    "input_modalities": [
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    "instruct_type": null
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  "supported_parameters": [
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  "default_parameters": {
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    "top_p": 0.95,
    "top_k": null,
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  "expiration_date": "2026-11-05",
  "links": {
    "details": "/api/v1/models/minimax/minimax-m2.7-20260318/endpoints"
  },
  "endpoints": [
    "/api/v1/chat/completions",
    "/api/v1/completions",
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  "benchmarks": {
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      {
        "arena": "models",
        "category": "3d",
        "elo": 1191,
        "win_rate": 49.9,
        "rank": 54
      },
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        "category": "asciiart",
        "elo": 1133,
        "win_rate": 46.2,
        "rank": 54
      },
      {
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        "win_rate": 50.7,
        "rank": 50
      },
      {
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        "win_rate": 52.3,
        "rank": 46
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        "win_rate": 49.2,
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      {
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        "win_rate": 46.9,
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      },
      {
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        "win_rate": 48.5,
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      "coding_index": 52.6,
      "agentic_index": 15.3
    }
  },
  "reasoning": {
    "mandatory": true
  }
}
MiniMax: MiniMax M2.5
MiniMaxMiniMax M2.5
minimax/minimax-m2.5
2026-02-12text->text
Design Arena
1146 Elo · #50
svg · 54.5% wins
Input
$0.27
per 1M tokens
Output
$0.95
per 1M tokens
Cached input
$0.03
per 1M tokens
Context
205K
tokens it reads
Max output
33K
tokens it writes
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...
inspect — the catalog entry
{
  "id": "minimax/minimax-m2.5",
  "canonical_slug": "minimax/minimax-m2.5-20260211",
  "hugging_face_id": "MiniMaxAI/MiniMax-M2.5",
  "name": "MiniMax: MiniMax M2.5",
  "created": 1770908502,
  "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...",
  "context_length": 204800,
  "architecture": {
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    "instruct_type": null
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  "top_provider": {
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  "per_request_limits": null,
  "supported_parameters": [
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        "win_rate": 51.2,
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    ]
  },
  "reasoning": {
    "mandatory": true
  }
}
MiniMax: MiniMax M2-her
MiniMaxMiniMax M2-her
minimax/minimax-m2-her
2026-01-23text->text
Input
$0.30
per 1M tokens
Output
$1.20
per 1M tokens
Cached input
$0.03
per 1M tokens
Context
66K
tokens it reads
Max output
2K
tokens it writes
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...
inspect — the catalog entry
{
  "id": "minimax/minimax-m2-her",
  "canonical_slug": "minimax/minimax-m2-her-20260123",
  "hugging_face_id": null,
  "name": "MiniMax: MiniMax M2-her",
  "created": 1769177239,
  "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...",
  "context_length": 65536,
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}
MiniMax: MiniMax M2.1
MiniMaxMiniMax M2.1
minimax/minimax-m2.1
2025-12-23text->text
Design Arena
1218 Elo · #53
uicomponent · 60.9% wins
Input
$0.30
per 1M tokens
Output
$1.20
per 1M tokens
Cached input
$0.03
per 1M tokens
Context
205K
tokens it reads
Max output
131K
tokens it writes
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...
inspect — the catalog entry
{
  "id": "minimax/minimax-m2.1",
  "canonical_slug": "minimax/minimax-m2.1",
  "hugging_face_id": "MiniMaxAI/MiniMax-M2.1",
  "name": "MiniMax: MiniMax M2.1",
  "created": 1766454997,
  "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...",
  "context_length": 204800,
  "architecture": {
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    "tokenizer": "Other",
    "instruct_type": null
  },
  "pricing": {
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  },
  "top_provider": {
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  "default_parameters": {
    "temperature": 1,
    "top_p": 0.9,
    "frequency_penalty": null
  },
  "supported_voices": null,
  "knowledge_cutoff": null,
  "expiration_date": "2026-11-05",
  "links": {
    "details": "/api/v1/models/minimax/minimax-m2.1/endpoints"
  },
  "endpoints": [
    "/api/v1/chat/completions",
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  "benchmarks": {
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      {
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        "category": "3d",
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      },
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      {
        "arena": "models",
        "category": "gamedev",
        "elo": 1134,
        "win_rate": 50.4,
        "rank": 85
      },
      {
        "arena": "models",
        "category": "svg",
        "elo": 1128,
        "win_rate": 55.4,
        "rank": 59
      },
      {
        "arena": "models",
        "category": "uicomponent",
        "elo": 1218,
        "win_rate": 60.9,
        "rank": 53
      },
      {
        "arena": "models",
        "category": "website",
        "elo": 1201,
        "win_rate": 55.4,
        "rank": 64
      }
    ]
  },
  "reasoning": {
    "mandatory": true
  }
}
MiniMax: MiniMax M2
MiniMaxMiniMax M2
minimax/minimax-m2
2025-10-23text->text
Design Arena
1096 Elo · #66
svg · 55.3% wins
Input
$0.26
per 1M tokens
Output
$1.02
per 1M tokens
Context
205K
tokens it reads
Max output
131K
tokens it writes
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,...
inspect — the catalog entry
{
  "id": "minimax/minimax-m2",
  "canonical_slug": "minimax/minimax-m2",
  "hugging_face_id": "MiniMaxAI/MiniMax-M2",
  "name": "MiniMax: MiniMax M2",
  "created": 1761252093,
  "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,...",
  "context_length": 204800,
  "architecture": {
    "modality": "text->text",
    "input_modalities": [
      "text"
    ],
    "output_modalities": [
      "text"
    ],
    "tokenizer": "Other",
    "instruct_type": null
  },
  "pricing": {
    "prompt": "0.000000255",
    "completion": "0.00000102"
  },
  "top_provider": {
    "context_length": 204800,
    "max_completion_tokens": 131072,
    "is_moderated": false
  },
  "per_request_limits": null,
  "supported_parameters": [
    "include_reasoning",
    "max_tokens",
    "reasoning",
    "temperature",
    "tool_choice",
    "tools",
    "top_p"
  ],
  "default_parameters": {
    "temperature": 1,
    "top_p": 0.95,
    "frequency_penalty": null
  },
  "supported_voices": null,
  "knowledge_cutoff": null,
  "expiration_date": "2026-11-05",
  "links": {
    "details": "/api/v1/models/minimax/minimax-m2/endpoints"
  },
  "endpoints": [
    "/api/v1/chat/completions",
    "/api/v1/completions",
    "/api/v1/messages",
    "/api/v1/responses"
  ],
  "benchmarks": {
    "design_arena": [
      {
        "arena": "models",
        "category": "3d",
        "elo": 1095,
        "win_rate": 48.3,
        "rank": 92
      },
      {
        "arena": "models",
        "category": "codecategories",
        "elo": 1133,
        "win_rate": 48.1,
        "rank": 99
      },
      {
        "arena": "models",
        "category": "dataviz",
        "elo": 1140,
        "win_rate": 50,
        "rank": 87
      },
      {
        "arena": "models",
        "category": "gamedev",
        "elo": 1118,
        "win_rate": 48.1,
        "rank": 91
      },
      {
        "arena": "models",
        "category": "svg",
        "elo": 1096,
        "win_rate": 55.3,
        "rank": 66
      },
      {
        "arena": "models",
        "category": "uicomponent",
        "elo": 1131,
        "win_rate": 49.2,
        "rank": 88
      },
      {
        "arena": "models",
        "category": "website",
        "elo": 1141,
        "win_rate": 48,
        "rank": 99
      }
    ]
  },
  "reasoning": {
    "mandatory": true
  }
}
MiniMax: MiniMax M1
MiniMaxMiniMax M1
minimax/minimax-m1
2025-06-17text->textknows up to 2024-06-30
Input
$0.55
per 1M tokens
Output
$2.20
per 1M tokens
Context
1M
tokens it reads
Max output
40K
tokens it writes
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...
inspect — the catalog entry
{
  "id": "minimax/minimax-m1",
  "canonical_slug": "minimax/minimax-m1",
  "hugging_face_id": null,
  "name": "MiniMax: MiniMax M1",
  "created": 1750200414,
  "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...",
  "context_length": 1000000,
  "architecture": {
    "modality": "text->text",
    "input_modalities": [
      "text"
    ],
    "output_modalities": [
      "text"
    ],
    "tokenizer": "Other",
    "instruct_type": null
  },
  "pricing": {
    "prompt": "0.00000055",
    "completion": "0.0000022"
  },
  "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"
  ],
  "default_parameters": {
    "temperature": null,
    "top_p": null,
    "frequency_penalty": null
  },
  "supported_voices": null,
  "knowledge_cutoff": "2024-06-30",
  "expiration_date": null,
  "links": {
    "details": "/api/v1/models/minimax/minimax-m1/endpoints"
  },
  "endpoints": [
    "/api/v1/chat/completions",
    "/api/v1/completions",
    "/api/v1/messages",
    "/api/v1/responses"
  ],
  "reasoning": {
    "mandatory": false
  },
  "benchmarks": null
}
MiniMax: MiniMax-01
MiniMaxMiniMax-01
minimax/minimax-01
2025-01-15text+image->textknows up to 2024-03-31
Input
$0.20
per 1M tokens
Output
$1.10
per 1M tokens
Context
1.0M
tokens it reads
Max output
900K
tokens it writes
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...
inspect — the catalog entry
{
  "id": "minimax/minimax-01",
  "canonical_slug": "minimax/minimax-01",
  "hugging_face_id": "MiniMaxAI/MiniMax-Text-01",
  "name": "MiniMax: MiniMax-01",
  "created": 1736915462,
  "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...",
  "context_length": 1000192,
  "architecture": {
    "modality": "text+image->text",
    "input_modalities": [
      "text",
      "image"
    ],
    "output_modalities": [
      "text"
    ],
    "tokenizer": "Other",
    "instruct_type": null
  },
  "pricing": {
    "prompt": "0.0000002",
    "completion": "0.0000011"
  },
  "top_provider": {
    "context_length": 1000192,
    "max_completion_tokens": 900172,
    "is_moderated": false
  },
  "per_request_limits": null,
  "supported_parameters": [
    "max_tokens",
    "temperature",
    "top_p"
  ],
  "default_parameters": {
    "temperature": null,
    "top_p": null,
    "frequency_penalty": null
  },
  "supported_voices": null,
  "knowledge_cutoff": "2024-03-31",
  "expiration_date": "2026-11-05",
  "links": {
    "details": "/api/v1/models/minimax/minimax-01/endpoints"
  },
  "endpoints": [
    "/api/v1/chat/completions",
    "/api/v1/completions",
    "/api/v1/messages",
    "/api/v1/responses"
  ],
  "benchmarks": null,
  "reasoning": null
}
minimax/minimax/m3.1-flash
MiniMaxminimax/minimax/m3.1-flash
minimax/minimax/m3.1-flash
inspect — the catalog entry
{
  "id": "minimax/minimax/m3.1-flash",
  "object": "model",
  "created_at": 1792602727,
  "cost_in": 1.5e-7,
  "cost_out": 6e-7,
  "owned_by": "minimax",
  "name": "minimax/minimax/m3.1-flash",
  "description": "",
  "context_length": null
}
minimax/minimax/h3-max
MiniMaxminimax/minimax/h3-max
minimax/minimax/h3-max
inspect — the catalog entry
{
  "id": "minimax/minimax/h3-max",
  "object": "model",
  "created_at": 1789513767,
  "cost_in": 0,
  "cost_out": 0,
  "owned_by": "minimax",
  "name": "minimax/minimax/h3-max",
  "description": "",
  "context_length": null
}
minimax/minimax/h3
MiniMaxminimax/minimax/h3
minimax/minimax/h3
inspect — the catalog entry
{
  "id": "minimax/minimax/h3",
  "object": "model",
  "created_at": 1789513766,
  "cost_in": 0,
  "cost_out": 0,
  "owned_by": "minimax",
  "name": "minimax/minimax/h3",
  "description": "",
  "context_length": null
}
minimax/minimax/m3
MiniMaxminimax/minimax/m3
minimax/minimax/m3
inspect — the catalog entry
{
  "id": "minimax/minimax/m3",
  "object": "model",
  "created_at": 1780340590,
  "cost_in": 0,
  "cost_out": 0,
  "owned_by": "minimax",
  "name": "minimax/minimax/m3",
  "description": "",
  "context_length": null
}
minimax/minimax/hailuo-2.3
MiniMaxminimax/minimax/hailuo-2.3
minimax/minimax/hailuo-2.3
inspect — the catalog entry
{
  "id": "minimax/minimax/hailuo-2.3",
  "object": "model",
  "created_at": 1776299800,
  "cost_in": 0,
  "cost_out": 0,
  "owned_by": "minimax",
  "name": "minimax/minimax/hailuo-2.3",
  "description": "",
  "context_length": null
}
minimax/minimax/hailuo-2.3-fast
MiniMaxminimax/minimax/hailuo-2.3-fast
minimax/minimax/hailuo-2.3-fast
inspect — the catalog entry
{
  "id": "minimax/minimax/hailuo-2.3-fast",
  "object": "model",
  "created_at": 1776299800,
  "cost_in": 0,
  "cost_out": 0,
  "owned_by": "minimax",
  "name": "minimax/minimax/hailuo-2.3-fast",
  "description": "",
  "context_length": null
}
minimax/minimax/speech-2.8-turbo
MiniMaxminimax/minimax/speech-2.8-turbo
minimax/minimax/speech-2.8-turbo
inspect — the catalog entry
{
  "id": "minimax/minimax/speech-2.8-turbo",
  "object": "model",
  "created_at": 1776299799,
  "cost_in": 0,
  "cost_out": 0,
  "owned_by": "minimax",
  "name": "minimax/minimax/speech-2.8-turbo",
  "description": "",
  "context_length": null
}
minimax/minimax/speech-2.8-hd
MiniMaxminimax/minimax/speech-2.8-hd
minimax/minimax/speech-2.8-hd
inspect — the catalog entry
{
  "id": "minimax/minimax/speech-2.8-hd",
  "object": "model",
  "created_at": 1776299799,
  "cost_in": 0,
  "cost_out": 0,
  "owned_by": "minimax",
  "name": "minimax/minimax/speech-2.8-hd",
  "description": "",
  "context_length": null
}
minimax/minimax/m2.7
MiniMaxminimax/minimax/m2.7
minimax/minimax/m2.7
inspect — the catalog entry
{
  "id": "minimax/minimax/m2.7",
  "object": "model",
  "created_at": 1776299799,
  "cost_in": 3e-7,
  "cost_out": 0.0000012,
  "owned_by": "minimax",
  "name": "minimax/minimax/m2.7",
  "description": "",
  "context_length": null
}