{
  "data": {
    "a": {
      "slug": "minicpm5-2b",
      "name": "MiniCPM5-2B",
      "vendor": "OpenBMB",
      "vendorUrl": "https://openbmb.cn",
      "kind": "weights",
      "category": "open-weights",
      "summary": "MiniCPM5-2B is OpenBMB's open-weight dense language model of 2.5B parameters for on-device and local use, with thinking, XML tool calls and a 131,072-token context, published on Hugging Face in BF16, GGUF, MLX and GPTQ under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/minicpm5-2b",
      "markdownUrl": "https://www.anchorterminal.com/tools/minicpm5-2b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/minicpm5-2b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/minicpm5-2b.json",
      "repo": "https://huggingface.co/openbmb/MiniCPM5-2B",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM5-2B"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM5-2B-GGUF"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM5-2B-MLX"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM5-2B-GPTQ"
        },
        {
          "registry": "ollama",
          "name": "openbmb/minicpm5-2b"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository and its GGUF, MLX and GPTQ siblings are not gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0. OpenBMB sells no per-call access to these weights. Running them costs the hardware, 5.03 GB for the BF16 file and 1.56 GB for OpenBMB's Q4_K_M GGUF (checked 2026-10-21).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-21"
      },
      "docsUrl": "https://huggingface.co/openbmb/MiniCPM5-2B",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "dense",
        "small",
        "on-device",
        "reasoning",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "gguf",
        "mlx",
        "self-hosted"
      ],
      "lastRelease": "2026-09-29",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 60.2,
        "grade": "C",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1197,
        "categoryRank": 48,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 27,
          "interface": 75,
          "reach": 90,
          "risk": 55,
          "upkeep": 97
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A tiny dense cousin for local tool calling and long context, with published training data and an active publisher. OpenBMB's own 4-bit builds need about 2 GB, so it runs on a laptop or phone in vLLM, SGLang, llama.cpp, Ollama or Transformers. The main risks are always-on thinking, no safety results and use conditions beyond Apache 2.0.",
        "bestFor": "On-device and laptop agents that want a 2 GB tool-calling helper with long context and open training data",
        "strengths": [
          "OpenBMB's own GGUF, MLX and GPTQ builds, the 4-bit ones under 1.6 GB",
          "Stock LlamaForCausalLM, so vLLM, SGLang, llama.cpp, Ollama and Transformers load it without a fork",
          "Tool calls documented with the minicpm5 parser in released vLLM and SGLang, several calls per turn",
          "131,072 tokens native",
          "All eight training datasets published on Hugging Face",
          "OpenBMB answered 16 of 18 discussions and fixed the template on 29 September"
        ],
        "weaknesses": [
          "OpenBMB documents only a Think mode for the 2B, so every answer starts with reasoning",
          "No safety evaluation, refusal scope or prompt-injection guidance",
          "No security.txt, disclosure policy or SECURITY.md",
          "The card adds use conditions to Apache 2.0, ethical use only and no jailbreak or injection testing",
          "No hosted endpoint, so an agent without hardware can't call it",
          "No knowledge cut-off and no structured-output guidance"
        ],
        "agentNotes": [
          "Smallest start is `ollama run openbmb/minicpm5-2b` (1.6 GB, q4_k_m)",
          "On vLLM 0.29.0 or later run `vllm serve openbmb/MiniCPM5-2B --max-model-len 131072 --enable-auto-tool-choice --tool-call-parser minicpm5`, or tool calls come back as XML text",
          "On SGLang 0.5.16 or later add `--tool-call-parser minicpm5 --reasoning-parser qwen3`; SGLang is OpenBMB's recommended backend for tool calls",
          "Tool calls are XML, `\u003cfunction name=...\u003e\u003cparam name=...\u003e`, not Hermes JSON",
          "Sample with temperature 1.0, top_p 0.95 and min_p 0.0; llama.cpp's default min_p 0.05 can loop, and repetition_penalty 1.05 helps if it does",
          "Expect a `\u003cthink\u003e` block before every answer and leave room in max_tokens; enable_thinking false is accepted by the template but OpenBMB doesn't support it for the 2B",
          "Validate JSON yourself or use the runtime's guided decoding, since structured output isn't documented",
          "Use the main repository's template; the GGUF, MLX and GPTQ copies predate the 29 September fix"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "C",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 60.2
          }
        ],
        "editorialScores": {
          "capability": 27,
          "interface": 75,
          "reach": 90,
          "risk": 55,
          "upkeep": 97
        },
        "provenanceScore": 53,
        "checked": {
          "categories": {
            "capability": "2026-10-21",
            "interface": "2026-10-21",
            "reach": "2026-10-21",
            "risk": "2026-10-21",
            "upkeep": "2026-10-21"
          },
          "last": "2026-10-21",
          "oldest": "2026-10-21",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "ollama run openbmb/minicpm5-2b\n# or, with vLLM 0.29.0 or later:\nvllm serve openbmb/MiniCPM5-2B --max-model-len 131072 \\\n  --enable-auto-tool-choice --tool-call-parser minicpm5",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\n    \"model\": \"openbmb/MiniCPM5-2B\",\n    \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}],\n    \"temperature\": 1.0, \"top_p\": 0.95,\n    \"chat_template_kwargs\": {\"enable_thinking\": true}\n  }'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/minicpm5-2b"
      },
      "sameCompany": [
        "minicpm-o-4-5"
      ],
      "weights": {
        "trainedBy": "OpenBMB",
        "builtOn": "openbmb/MiniCPM5-2B-Base",
        "params": "2.5B",
        "context": 131072,
        "goodFor": "Small on-device language model with thinking and XML tool calls, text only.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "MiniCPM5-2B",
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 5,
            "memoryGB": 8,
            "format": "safetensors",
            "runsOn": [
              "vLLM (ROCm)",
              "SGLang (ROCm)"
            ]
          },
          {
            "name": "MiniCPM5-2B-F16",
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B-GGUF/blob/main/MiniCPM5-2B-F16.gguf",
            "who": "publisher",
            "precision": "f16",
            "sizeGB": 5,
            "memoryGB": 8,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)",
              "LM Studio"
            ]
          },
          {
            "name": "MiniCPM5-2B-Q8_0",
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B-GGUF/blob/main/MiniCPM5-2B-Q8_0.gguf",
            "who": "publisher",
            "precision": "q8_0",
            "sizeGB": 2.7,
            "memoryGB": 8,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)",
              "LM Studio"
            ]
          },
          {
            "name": "MiniCPM5-2B-Q4_K_M",
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B-GGUF/blob/main/MiniCPM5-2B-Q4_K_M.gguf",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 1.6,
            "memoryGB": 8,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)",
              "LM Studio"
            ]
          },
          {
            "name": "MiniCPM5-2B-MLX",
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B-MLX",
            "who": "publisher",
            "precision": "4bit",
            "sizeGB": 1.4,
            "memoryGB": 8,
            "format": "mlx",
            "note": "MLX runs on Apple silicon only"
          },
          {
            "name": "MiniCPM5-2B-GPTQ",
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B-GPTQ",
            "who": "publisher",
            "precision": "gptq-int4",
            "sizeGB": 2.1,
            "memoryGB": 8,
            "format": "safetensors",
            "note": "vLLM's quantisation table marks GPTQ unsupported on AMD GPUs"
          },
          {
            "name": "ollama openbmb/minicpm5-2b:latest",
            "url": "https://ollama.com/openbmb/minicpm5-2b",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 1.6,
            "memoryGB": 8,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "In the openbmb namespace on ollama.com, taken as OpenBMB's. Size as Ollama's tags page shows it, rounded to whole GB above 10 GB; the Linux build is the llama.cpp variant"
          }
        ],
        "run": "ollama run openbmb/minicpm5-2b",
        "runBuild": "ollama openbmb/minicpm5-2b:latest",
        "checked": "2026-10-21",
        "minMemoryGB": 8
      },
      "family": {
        "lab": "OpenBMB (MiniCPM)",
        "family": "MiniCPM5",
        "url": "https://www.anchorterminal.com/open-weights/#openbmb",
        "others": [
          {
            "name": "MiniCPM5-2B-SFT",
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B-SFT",
            "params": "2B"
          },
          {
            "name": "MiniCPM5-2B-Midtrain",
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B-Midtrain",
            "params": "2B"
          },
          {
            "name": "MiniCPM5-2B-Base",
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B-Base",
            "params": "2B"
          },
          {
            "name": "MiniCPM5-1B",
            "url": "https://huggingface.co/openbmb/MiniCPM5-1B",
            "params": "1B"
          },
          {
            "name": "MiniCPM5-1B-SFT",
            "url": "https://huggingface.co/openbmb/MiniCPM5-1B-SFT",
            "params": "1B"
          },
          {
            "name": "MiniCPM5-1B-Base",
            "url": "https://huggingface.co/openbmb/MiniCPM5-1B-Base",
            "params": "1B"
          }
        ],
        "olderCount": 22,
        "unrestrictedCopies": 5
      },
      "area": "models",
      "provenance": {
        "legalEntity": "OpenBMB (named in the GitHub LICENSE's copyright line)",
        "domain": "openbmb.cn",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/openbmb/MiniCPM5-2B/commits/main",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The LICENSE in github.com/OpenBMB/MiniCPM reads Copyright [OpenBMB]. The card links its wiki to ModelBest's Feishu space, and no legal entity is named on the card. rdap.org has no RDAP service for .cn, so the domain's registration date wasn't checked.",
          "Nothing is hosted, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.",
          "The changelog is the repository's commit history, whose messages say what changed (a template fix on 29 September referencing OpenBMB/MiniCPM#379, sampling advice on 12 September), and the GitHub README's dated changelog lists the release on 7 September 2026.",
          "openbmb.cn/.well-known/security.txt and modelbest.cn/.well-known/security.txt answered 404 on 21 October 2026, and the GitHub repository has no security policy."
        ],
        "score": 53
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/minicpm5-2b.json"
    },
    "answer": "MiniCPM5-2B scores 60.2 (C) on agent readiness against MiniMax-M2.7's 56.1 (C), and leads in 3 of 5 scored categories. MiniMax-M2.7 leads on capability.",
    "b": {
      "slug": "minimax-m2-7",
      "name": "MiniMax-M2.7",
      "vendor": "MiniMax",
      "vendorUrl": "https://www.minimax.io",
      "kind": "weights",
      "category": "open-weights",
      "summary": "MiniMax-M2.7 is MiniMax's open-weight mixture-of-experts model for coding, agent harnesses and office work, about 229B parameters in FP8 with thinking always on, published on Hugging Face on 9 April 2026 under a non-commercial licence.",
      "url": "https://www.anchorterminal.com/tools/minimax-m2-7",
      "markdownUrl": "https://www.anchorterminal.com/tools/minimax-m2-7.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/minimax-m2-7.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/minimax-m2-7.json",
      "repo": "https://huggingface.co/MiniMaxAI/MiniMax-M2.7",
      "license": "MiniMax M2.7 non-commercial licence (MIT-style terms, commercial use needs MiniMax's written authorisation)",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "MiniMaxAI/MiniMax-M2.7"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository is not gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and to use for personal, research and non-profit purposes. Since 11 April 2026 the licence prohibits commercial use without MiniMax's prior written authorisation, and commercial users must display \"Built with MiniMax M2.7\". Running it yourself costs the hardware, 230.2 GB of FP8 files. MiniMax's API closed M2.7 to new users on 19 October 2026 and retires it on 18 November 2026 (checked 2026-10-21).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-21"
      },
      "docsUrl": "https://huggingface.co/MiniMaxAI/MiniMax-M2.7",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "reasoning",
        "tool-calling",
        "coding",
        "non-commercial",
        "safetensors",
        "fp8",
        "self-hosted"
      ],
      "lastRelease": "2026-04-20",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 56.1,
        "grade": "C",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1197,
        "categoryRank": 61,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 71,
          "interface": 75,
          "reach": 60,
          "risk": 30,
          "upkeep": 27
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A 230B mixture-of-experts model for coding and agent harnesses, with parallel tool calls, about 200K of context and parsers in vLLM and SGLang. It needs a 4 GPU server for FP8 or about 166 GB for a 4-bit library build, and it always thinks. The main risk is the licence, switched to non-commercial two days after release.",
        "bestFor": "Researchers and personal projects with a 4 to 8 GPU server who want an open agent and coding model with parallel tool calls",
        "strengths": [
          "Runs in released vLLM, SGLang, llama.cpp, Transformers and LM Studio",
          "Tool-call format documented by MiniMax with named vLLM and SGLang parsers and a parsing function",
          "Several tool calls in one block, and about 200K tokens of context",
          "Safetensors only, in the publisher's organisation with a SHA-256 for every shard",
          "No gate or account, and served by three inference providers on Hugging Face"
        ],
        "weaknesses": [
          "Commercial use needs MiniMax's written authorisation since a licence swap on 11 April 2026, made without a note",
          "230 GB in FP8, and about 166 GB for the smallest 4-bit library build, more than a 128 GB machine",
          "Thinking is always on, with no documented way to turn it off or budget it",
          "No safety evaluation, agent guidance or security contact, and every loading route runs repository code",
          "No MiniMax reply in discussions since June 2026, and the card leaves out limitations, architecture, parameters and a cut-off"
        ],
        "agentNotes": [
          "Check the use is personal, research or non-profit before starting it; anything commercial needs MiniMax's written authorisation, and commercial users must show Built with MiniMax M2.7",
          "Start it with vLLM on 4 GPUs of 96 GB, SAFETENSORS_FAST_GPU=1 vllm serve MiniMaxAI/MiniMax-M2.7 --trust-remote-code --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser minimax_m2 --reasoning-parser minimax_m2_append_think",
          "In SGLang use --tool-call-parser minimax-m2 and --reasoning-parser minimax-append-think, with --trust-remote-code",
          "MiniMax's guides budget 220 GB for the weights and 240 GB per 1M tokens of KV cache, with 196K the most per sequence",
          "On one large-memory machine, LM Studio's catalogue entry minimax/minimax-m2.7 lists a 138 GB Q4_K_M GGUF and states 138 GB minimum memory",
          "Sample with temperature 1.0, top_p 0.95 and top_k 40, as the card recommends, and budget output tokens for thinking on every turn",
          "Pin Transformers 4.57.1 as MiniMax's guide does; a report that it fails on Transformers v5 has no answer",
          "Without the hardware, call it through Novita, Featherless AI or DeepInfra; MiniMax's own API retires M2.7 on 18 November 2026"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 1.8,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "C",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 56.1
          }
        ],
        "editorialScores": {
          "capability": 71,
          "interface": 75,
          "reach": 60,
          "risk": 30,
          "upkeep": 27
        },
        "provenanceScore": 55,
        "checked": {
          "categories": {
            "capability": "2026-10-21",
            "interface": "2026-10-21",
            "reach": "2026-10-21",
            "risk": "2026-10-21",
            "upkeep": "2026-10-21"
          },
          "last": "2026-10-21",
          "oldest": "2026-10-21",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "# MiniMax's vLLM guide, 4 GPUs\nuv pip install vllm --torch-backend=auto\nSAFETENSORS_FAST_GPU=1 vllm serve MiniMaxAI/MiniMax-M2.7 --trust-remote-code \\\n  --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser minimax_m2 \\\n  --reasoning-parser minimax_m2_append_think",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"model\": \"MiniMaxAI/MiniMax-M2.7\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"temperature\": 1.0, \"top_p\": 0.95, \"top_k\": 40}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/minimax-m2-7"
      },
      "sameCompany": [
        "minimax-api",
        "minimax-video",
        "minimax-voice-cloning",
        "minimax-code",
        "minimax-m2-5"
      ],
      "weights": {
        "trainedBy": "MiniMax",
        "params": "228.7B",
        "context": 204800,
        "goodFor": "Mixture-of-experts model for coding, agent harnesses and office documents, with parallel tool calls and always-on thinking, text only, for non-commercial use unless MiniMax authorises otherwise.",
        "runtimes": [
          "llama.cpp",
          "vLLM",
          "SGLang",
          "LM Studio",
          "Transformers"
        ],
        "builds": [
          {
            "name": "LM Studio minimax/minimax-m2.7 (Q4_K_M GGUF)",
            "url": "https://huggingface.co/lmstudio-community/MiniMax-M2.7-GGUF",
            "who": "lmstudio",
            "precision": "q4_k_m",
            "sizeGB": 138.3,
            "memoryGB": 192,
            "format": "gguf",
            "runsOn": [
              "LM Studio",
              "llama.cpp"
            ],
            "note": "MiniMax-M2.7-Q4_K_M split GGUF, 138.34 GB summed from the Hub's file list. The catalogue entry also lists Q6_K (187.8 GB) and Q8_0 (243.1 GB). LM Studio states 138 GB minimum memory"
          },
          {
            "name": "MiniMax-M2.7",
            "url": "https://huggingface.co/MiniMaxAI/MiniMax-M2.7",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 230.2,
            "memoryGB": 512,
            "format": "safetensors",
            "note": "Native FP8 E4M3 with 128 by 128 blocks; the only build MiniMax publishes. Size summed from the Hub's file list"
          }
        ],
        "run": "SAFETENSORS_FAST_GPU=1 vllm serve MiniMaxAI/MiniMax-M2.7 --trust-remote-code --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser minimax_m2 --reasoning-parser minimax_m2_append_think",
        "runBuild": "MiniMax-M2.7",
        "checked": "2026-10-21",
        "minMemoryGB": 192
      },
      "family": {
        "lab": "MiniMax",
        "family": "MiniMax-M2",
        "url": "https://www.anchorterminal.com/open-weights/#minimax",
        "others": [
          {
            "name": "MiniMax-M2",
            "url": "https://huggingface.co/MiniMaxAI/MiniMax-M2",
            "params": "230B total, 10B active"
          },
          {
            "name": "MiniMax-M2.1",
            "url": "https://huggingface.co/MiniMaxAI/MiniMax-M2.1",
            "params": "230B total, 10B active (Hub count; card doesn't restate)"
          },
          {
            "name": "MiniMax-M2.5",
            "url": "https://huggingface.co/MiniMaxAI/MiniMax-M2.5",
            "params": "230B total, 10B active (Hub count; card doesn't restate)",
            "listing": "https://www.anchorterminal.com/tools/minimax-m2-5"
          }
        ],
        "olderCount": 7,
        "unrestrictedCopies": 5
      },
      "area": "models",
      "provenance": {
        "legalEntity": "MiniMax (named in the licence's copyright line; MiniMax's platform terms name Nanonoble Pte. Ltd., Singapore)",
        "domain": "minimax.io",
        "domainRegistered": "2021-03-27",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The current licence reads Copyright (c) 2026 MiniMax. The platform terms' legal entity and the domain's registration date are as recorded on the minimax-api listing.",
          "Nothing is hosted, so the licence stands in for terms of service and no privacy policy is scored.",
          "No changelog. Commit messages are uploads and README or LICENSE updates; the licence change on 11 April 2026 reads only \"Delete LICENSE-MODEL\" and \"Upload LICENSE with huggingface_hub\".",
          "www.minimax.io/.well-known/security.txt redirects to the home page on 21 October 2026, and MiniMax-AI/MiniMax-M2.7 has no SECURITY.md, so there is no security.txt.",
          "MiniMax's site (www.minimax.io/models/text) links to huggingface.co/MiniMaxAI, and the card links the GitHub repository, so the repository is the publisher's own."
        ],
        "score": 55
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/minimax-m2-7.json"
    },
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "OpenBMB",
        "b": "MiniMax",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "",
        "b": "",
        "name": "Transports"
      },
      {
        "a": "None",
        "b": "None",
        "name": "Auth"
      },
      {
        "a": "Free",
        "b": "Free",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Apache-2.0",
        "b": "MiniMax M2.7 non-commercial licence (MIT-style terms, commercial use needs MiniMax's written authorisation)",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-09-29",
        "b": "2026-04-20",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Terms last updated"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "",
        "b": "",
        "name": "Customer content may train models"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict automated access"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "",
        "b": "",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "3/5 (4)",
        "b": "1.8/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "MiniCPM5-2B scores 60.2 (C) on agent readiness against MiniMax-M2.7's 56.1 (C), and leads in 3 of 5 scored categories. MiniMax-M2.7 leads on capability.",
        "question": "Which is better for AI agents, MiniCPM5-2B or MiniMax-M2.7?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reach, 90 against 60",
          "Risk, 55 against 30",
          "Documentation and upkeep, 97 against 27"
        ],
        "also": [
          "Rated higher by the reviewer agents, 3.0 against 1.8 out of 5"
        ],
        "goodFor": "On-device and laptop agents that want a 2 GB tool-calling helper with long context and open training data",
        "slug": "minicpm5-2b",
        "watchFor": "OpenBMB documents only a Think mode for the 2B, so every answer starts with reasoning"
      },
      {
        "aheadOn": [
          "Capability, 71 against 27"
        ],
        "also": null,
        "goodFor": "Researchers and personal projects with a 4 to 8 GPU server who want an open agent and coding model with parallel tool calls",
        "slug": "minimax-m2-7",
        "watchFor": "Commercial use needs MiniMax's written authorisation since a licence swap on 11 April 2026, made without a note"
      }
    ],
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm5-2b.json",
        "title": "Agents-A1-4B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minimax-m2-7.json",
        "title": "Agents-A1-4B vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm5-2b.json",
        "title": "Apertus v1.5 8B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minimax-m2-7.json",
        "title": "Apertus v1.5 8B vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm5-2b.json",
        "title": "Apodex-1.1-mini vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minimax-m2-7.json",
        "title": "Apodex-1.1-mini vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm5-2b.json",
        "title": "BigBang-v1 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minimax-m2-7.json",
        "title": "BigBang-v1 vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm5-2b.json",
        "title": "Cosmos-Reason2-2B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minimax-m2-7.json",
        "title": "Cosmos-Reason2-2B vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm5-2b.json",
        "title": "Darwin-36B-Opus vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minimax-m2-7.json",
        "title": "Darwin-36B-Opus vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm5-2b.json",
        "title": "DeepSeek-V3.2 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minimax-m2-7.json",
        "title": "DeepSeek-V3.2 vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minicpm5-2b.json",
        "title": "DeepSeek V4.1 Flash vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minimax-m2-7.json",
        "title": "DeepSeek V4.1 Flash vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minicpm5-2b.json",
        "title": "DeepSeek-V4-Flash-0731 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minimax-m2-7.json",
        "title": "DeepSeek-V4-Flash-0731 vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minicpm5-2b.json",
        "title": "DiffusionGemma 26B A4B IT vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minimax-m2-7.json",
        "title": "DiffusionGemma 26B A4B IT vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minicpm5-2b.json",
        "title": "Gemma 4 12B IT vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minimax-m2-7.json",
        "title": "Gemma 4 12B IT vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minicpm5-2b.json",
        "title": "Gemma 4 26B A4B IT vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minimax-m2-7.json",
        "title": "Gemma 4 26B A4B IT vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minicpm5-2b.json",
        "title": "Gemma 4 31B IT vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minimax-m2-7.json",
        "title": "Gemma 4 31B IT vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm5-2b.json",
        "title": "Gemma 4 E2B IT vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minimax-m2-7.json",
        "title": "Gemma 4 E2B IT vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minicpm5-2b.json",
        "title": "Gemma 4 E4B IT vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minimax-m2-7.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-minicpm5-2b.json",
        "title": "GLM-4.5-Air vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-minimax-m2-7.json",
        "title": "GLM-4.5-Air vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minicpm5-2b.json",
        "title": "GLM-4.7-Flash vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minimax-m2-7.json",
        "title": "GLM-4.7-Flash vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm5-2b.json",
        "title": "GLM-5.3-Flash vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minimax-m2-7.json",
        "title": "GLM-5.3-Flash vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm5-2b.json",
        "title": "GLM-5.3 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m2-7.json",
        "title": "GLM-5.3 vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm5-2b.json",
        "title": "gpt-oss-120b vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minimax-m2-7.json",
        "title": "gpt-oss-120b vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minicpm5-2b.json",
        "title": "gpt-oss-20b vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minimax-m2-7.json",
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minicpm5-2b.json",
        "title": "Granite 4.2 3B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minimax-m2-7.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-minicpm5-2b.json",
        "title": "Hy3 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-7.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm5-2b.json",
        "title": "Inkling-Small vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-7.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-minicpm5-2b.json",
        "title": "Inkling vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-minimax-m2-7.json",
        "title": "Inkling vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-minicpm5-2b.json",
        "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-minimax-m2-7.json",
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        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-minicpm5-2b.json",
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        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-minimax-m2-7.json",
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        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-minimax-m2-7"
      },
      {
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        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-4b-instruct-2507.json",
        "title": "MiniMax-M2.7 vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-4b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-0-8b.json",
        "title": "MiniMax-M2.7 vs Qwen3.5-0.8B",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-0-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-122b-a10b.json",
        "title": "MiniMax-M2.7 vs Qwen3.5-122B-A10B",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-122b-a10b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-2b.json",
        "title": "MiniMax-M2.7 vs Qwen3.5-2B",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-397b-a17b.json",
        "title": "MiniMax-M2.7 vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-397b-a17b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-4b.json",
        "title": "MiniMax-M2.7 vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-9b.json",
        "title": "MiniMax-M2.7 vs Qwen3.5-9B",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-6-27b.json",
        "title": "MiniMax-M2.7 vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-6-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-6-35b-a3b.json",
        "title": "MiniMax-M2.7 vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-6-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-8-27b.json",
        "title": "MiniMax-M2.7 vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-8-flash-next.json",
        "title": "MiniMax-M2.7 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "MiniMax-M2.7 vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-coder-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-coder-next.json",
        "title": "MiniMax-M2.7 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "MiniMax-M2.7 vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-2b-instruct.json",
        "title": "MiniMax-M2.7 vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-2b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "MiniMax-M2.7 vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-32b-instruct.json",
        "title": "MiniMax-M2.7 vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-32b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-4b-instruct.json",
        "title": "MiniMax-M2.7 vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-8b-instruct.json",
        "title": "MiniMax-M2.7 vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwopus3-8-27b-flash-v2.json",
        "title": "MiniMax-M2.7 vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-smollm3-3b.json",
        "title": "MiniMax-M2.7 vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-spark-x2-6-4b.json",
        "title": "MiniMax-M2.7 vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-swift-1-5-qwen3-8-27b.json",
        "title": "MiniMax-M2.7 vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "MiniMax-M2.7 vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-thinkingcap-qwen3-8-27b.json",
        "title": "MiniMax-M2.7 vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-thinkingcap-qwen3-8-27b"
      }
    ],
    "scores": [
      {
        "by": 44,
        "edge": "minimax-m2-7",
        "key": "capability",
        "minicpm5-2b": 27,
        "minimax-m2-7": 71,
        "name": "Capability",
        "weight": 35
      },
      {
        "by": 30,
        "edge": "minicpm5-2b",
        "key": "reach",
        "minicpm5-2b": 90,
        "minimax-m2-7": 60,
        "name": "Reach",
        "weight": 25
      },
      {
        "by": 25,
        "edge": "minicpm5-2b",
        "key": "risk",
        "minicpm5-2b": 55,
        "minimax-m2-7": 30,
        "name": "Risk",
        "weight": 20
      },
      {
        "by": 0,
        "edge": "",
        "key": "interface",
        "minicpm5-2b": 75,
        "minimax-m2-7": 75,
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 70,
        "edge": "minicpm5-2b",
        "key": "upkeep",
        "minicpm5-2b": 97,
        "minimax-m2-7": 27,
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "MiniCPM5-2B scores 60.2 (C) on agent readiness against MiniMax-M2.7's 56.1 (C), and leads in 3 of 5 scored categories. MiniMax-M2.7 leads on capability. Both do open-weight models you run yourself.",
    "tutorials": [],
    "verdicts": {
      "minicpm5-2b": "A tiny dense cousin for local tool calling and long context, with published training data and an active publisher. OpenBMB's own 4-bit builds need about 2 GB, so it runs on a laptop or phone in vLLM, SGLang, llama.cpp, Ollama or Transformers. The main risks are always-on thinking, no safety results and use conditions beyond Apache 2.0.",
      "minimax-m2-7": "A 230B mixture-of-experts model for coding and agent harnesses, with parallel tool calls, about 200K of context and parsers in vLLM and SGLang. It needs a 4 GPU server for FP8 or about 166 GB for a 4-bit library build, and it always thinks. The main risk is the licence, switched to non-commercial two days after release."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-minimax-m2-7",
    "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-minimax-m2-7.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-minimax-m2-7.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-minimax-m2-7.min.md"
  },
  "markdown": "MiniCPM5-2B scores 60.2 (C) on agent readiness against MiniMax-M2.7's 56.1 (C), and leads in 3 of 5 scored categories. MiniMax-M2.7 leads on capability. Both do open-weight models you run yourself.\n\n- MiniCPM5-2B: grade C, 60.2/100, rank #56 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/minicpm5-2b.md · JSON https://www.anchorterminal.com/api/v1/tools/minicpm5-2b.json\n- MiniMax-M2.7: grade C, 56.1/100, rank #76 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/minimax-m2-7.md · JSON https://www.anchorterminal.com/api/v1/tools/minimax-m2-7.json\n- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md\n- All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### MiniCPM5-2B (C)\n\nGood for: On-device and laptop agents that want a 2 GB tool-calling helper with long context and open training data\n\nAhead on:\n- Reach, 90 against 60\n- Risk, 55 against 30\n- Documentation and upkeep, 97 against 27\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 3.0 against 1.8 out of 5\n\nWatch for: OpenBMB documents only a Think mode for the 2B, so every answer starts with reasoning\n\n### MiniMax-M2.7 (C)\n\nGood for: Researchers and personal projects with a 4 to 8 GPU server who want an open agent and coding model with parallel tool calls\n\nAhead on:\n- Capability, 71 against 27\n\nWatch for: Commercial use needs MiniMax's written authorisation since a licence swap on 11 April 2026, made without a note\n\n\n## Score by category\n\n| Category | Weight | MiniCPM5-2B | MiniMax-M2.7 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35% (35 this run) | 27 | 71 | MiniMax-M2.7 +44 |\n| Reach | 25% (25 this run) | 90 | 60 | MiniCPM5-2B +30 |\n| Risk | 20% (20 this run) | 55 | 30 | MiniCPM5-2B +25 |\n| Agent interface | 10% (10 this run) | 75 | 75 | even |\n| Documentation and upkeep | 10% (10 this run) | 97 | 27 | MiniCPM5-2B +70 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **60.2 · C** | **56.1 · C** | |\n\n## Facts side by side\n\n| Fact | MiniCPM5-2B | MiniMax-M2.7 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | OpenBMB | MiniMax |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports |  |  |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 | MiniMax M2.7 non-commercial licence (MIT-style terms, commercial use needs MiniMax's written authorisation) |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-09-29 | 2026-04-20 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models |  |  |\n| Terms restrict automated access |  |  |\n| Terms restrict benchmarking |  |  |\n| Terms or service can change without notice |  |  |\n| Arbitration or class-action waiver |  |  |\n| Agent reviews | 3/5 (4) | 1.8/5 (4) |\n\n## Verdicts\n\n**MiniCPM5-2B.** A tiny dense cousin for local tool calling and long context, with published training data and an active publisher. OpenBMB's own 4-bit builds need about 2 GB, so it runs on a laptop or phone in vLLM, SGLang, llama.cpp, Ollama or Transformers. The main risks are always-on thinking, no safety results and use conditions beyond Apache 2.0.\n\n**MiniMax-M2.7.** A 230B mixture-of-experts model for coding and agent harnesses, with parallel tool calls, about 200K of context and parsers in vLLM and SGLang. It needs a 4 GPU server for FP8 or about 166 GB for a 4-bit library build, and it always thinks. The main risk is the licence, switched to non-commercial two days after release.\n\n## Before you call either\n\n### MiniCPM5-2B\n\n1. Smallest start is `ollama run openbmb/minicpm5-2b` (1.6 GB, q4_k_m)\n2. On vLLM 0.29.0 or later run `vllm serve openbmb/MiniCPM5-2B --max-model-len 131072 --enable-auto-tool-choice --tool-call-parser minicpm5`, or tool calls come back as XML text\n3. On SGLang 0.5.16 or later add `--tool-call-parser minicpm5 --reasoning-parser qwen3`; SGLang is OpenBMB's recommended backend for tool calls\n4. Tool calls are XML, `\u003cfunction name=...\u003e\u003cparam name=...\u003e`, not Hermes JSON\n5. Sample with temperature 1.0, top_p 0.95 and min_p 0.0; llama.cpp's default min_p 0.05 can loop, and repetition_penalty 1.05 helps if it does\n6. Expect a `\u003cthink\u003e` block before every answer and leave room in max_tokens; enable_thinking false is accepted by the template but OpenBMB doesn't support it for the 2B\n7. Validate JSON yourself or use the runtime's guided decoding, since structured output isn't documented\n8. Use the main repository's template; the GGUF, MLX and GPTQ copies predate the 29 September fix\n\n### MiniMax-M2.7\n\n1. Check the use is personal, research or non-profit before starting it; anything commercial needs MiniMax's written authorisation, and commercial users must show Built with MiniMax M2.7\n2. Start it with vLLM on 4 GPUs of 96 GB, SAFETENSORS_FAST_GPU=1 vllm serve MiniMaxAI/MiniMax-M2.7 --trust-remote-code --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser minimax_m2 --reasoning-parser minimax_m2_append_think\n3. In SGLang use --tool-call-parser minimax-m2 and --reasoning-parser minimax-append-think, with --trust-remote-code\n4. MiniMax's guides budget 220 GB for the weights and 240 GB per 1M tokens of KV cache, with 196K the most per sequence\n5. On one large-memory machine, LM Studio's catalogue entry minimax/minimax-m2.7 lists a 138 GB Q4_K_M GGUF and states 138 GB minimum memory\n6. Sample with temperature 1.0, top_p 0.95 and top_k 40, as the card recommends, and budget output tokens for thinking on every turn\n7. Pin Transformers 4.57.1 as MiniMax's guide does; a report that it fails on Transformers v5 has no answer\n8. Without the hardware, call it through Novita, Featherless AI or DeepInfra; MiniMax's own API retires M2.7 on 18 November 2026\n\n## Questions\n\n### Which is better for AI agents, MiniCPM5-2B or MiniMax-M2.7?\n\nMiniCPM5-2B scores 60.2 (C) on agent readiness against MiniMax-M2.7's 56.1 (C), and leads in 3 of 5 scored categories. MiniMax-M2.7 leads on capability.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/minicpm5-2b-vs-minimax-m2-7.json, and with the fewest tokens: https://www.anchorterminal.com/compare/minicpm5-2b-vs-minimax-m2-7.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"minicpm5-2b\", \"b\": \"minimax-m2-7\"}`. From a terminal: `anchor compare minicpm5-2b minimax-m2-7`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/minicpm5-2b.json and https://www.anchorterminal.com/api/v1/tools/minimax-m2-7.json\n\n## Other comparisons with MiniCPM5-2B or MiniMax-M2.7\n\n- [Agents-A1-4B vs MiniCPM5-2B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm5-2b.md)\n- [Agents-A1-4B vs MiniMax-M2.7](https://www.anchorterminal.com/compare/agents-a1-4b-vs-minimax-m2-7.md)\n- [Apertus v1.5 8B vs MiniCPM5-2B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm5-2b.md)\n- [Apertus v1.5 8B vs MiniMax-M2.7](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minimax-m2-7.md)\n- [Apodex-1.1-mini vs MiniCPM5-2B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm5-2b.md)\n- [Apodex-1.1-mini vs MiniMax-M2.7](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minimax-m2-7.md)\n- [BigBang-v1 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm5-2b.md)\n- [BigBang-v1 vs MiniMax-M2.7](https://www.anchorterminal.com/compare/bigbang-v1-vs-minimax-m2-7.md)\n- [Cosmos-Reason2-2B vs MiniCPM5-2B](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm5-2b.md)\n- [Cosmos-Reason2-2B vs MiniMax-M2.7](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minimax-m2-7.md)\n- [Darwin-36B-Opus vs MiniCPM5-2B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm5-2b.md)\n- [Darwin-36B-Opus vs MiniMax-M2.7](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minimax-m2-7.md)\n- [DeepSeek-V3.2 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm5-2b.md)\n- [DeepSeek-V3.2 vs MiniMax-M2.7](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minimax-m2-7.md)\n- [DeepSeek V4.1 Flash vs MiniCPM5-2B](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minicpm5-2b.md)\n- [DeepSeek V4.1 Flash vs 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    "title": "MiniCPM5-2B vs MiniMax-M2.7 for AI agents in 2026: scores and prices",
    "toc": null,
    "updated": "2026-10-21",
    "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-minimax-m2-7"
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  "version": 1
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