{
  "data": {
    "a": {
      "slug": "minicpm-v-4-7-35b-a3b",
      "name": "MiniCPM-V 4.7 35B-A3B",
      "vendor": "OpenBMB",
      "vendorUrl": "https://openbmb.cn",
      "kind": "weights",
      "category": "open-weights",
      "summary": "MiniCPM-V 4.7 35B-A3B is OpenBMB's open-weight vision-language model, a 35B mixture of experts with about 3B active per token that reads images and video, calls tools, and ships in BF16, FP8, 4-bit and GGUF builds under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/minicpm-v-4-7-35b-a3b",
      "markdownUrl": "https://www.anchorterminal.com/tools/minicpm-v-4-7-35b-a3b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/minicpm-v-4-7-35b-a3b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/minicpm-v-4-7-35b-a3b.json",
      "dns": "minicpm-v-4-7-35b-a3b.grade.anchorterminal.com",
      "repo": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-V-4.7-35B-A3B"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-V-4.7-35B-A3B-gguf"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-V-4.7-35B-A3B-FP8"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-V-4.7-35B-A3B-AWQ"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-V-4.7-35B-A3B-GPTQ"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-V-4.7-35B-A3B-int4"
        },
        {
          "registry": "ollama",
          "name": "openbmb/minicpm-v4.7:35b-a3b"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The main repository and OpenBMB's GGUF, FP8, AWQ, GPTQ and int4 repositories are not gated (checked 2026-11-10).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0, named in the card's metadata and carried as a LICENSE file in OpenBMB's GitHub repository. Running it yourself costs the hardware, about 70 GB for the BF16 files, 22.7 GB for the 4-bit safetensors builds or 18.7 GB for the IQ4_XS GGUF (checked 2026-11-10).",
      "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 2026-11-10).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-11-10"
      },
      "docsUrl": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "vision",
        "video",
        "on-device",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "gguf",
        "fp8",
        "awq",
        "gptq",
        "self-hosted"
      ],
      "lastRelease": "2026-11-03",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 61,
        "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": 1518,
        "categoryRank": 61,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "interface": 70,
          "reach": 90,
          "risk": 55,
          "upkeep": 68
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-10"
        },
        "negative": 0,
        "verdict": "A vision-language cousin for images and video that fits a 24 to 32 GB machine from OpenBMB's own GGUF, under plain Apache 2.0, with a publisher that answers. The card says little about limits, training data or how tool calls come back, so test the tool format in your runtime before relying on it.",
        "bestFor": "Agents that need to read screenshots, documents and video on a local machine with 24 to 32 GB for the model, under a permissive licence",
        "strengths": [
          "Fits about 24 GB from OpenBMB's IQ4_XS GGUF and 32 GB from its Q4_K_M, 4-bit safetensors or Ollama builds",
          "Runs in llama.cpp, Ollama, vLLM, SGLang and Transformers from their released versions, with llama.cpp's own guide",
          "Plain Apache 2.0, ungated, safetensors and GGUF only, no remote code",
          "OpenBMB answered 8 of 12 discussions and dates its releases",
          "Images, several images and video in one model, with thinking off by default"
        ],
        "weaknesses": [
          "No limitations section, safety results, agent-use guidance or security contact",
          "Training data isn't described, and the card gives no context length, languages or knowledge cut-off",
          "The card shows a tool-calling request but not the reply, and names no parser",
          "OpenBMB's cookbook is behind the runtimes on SGLang and Ollama support",
          "No inference provider is mapped on Hugging Face"
        ],
        "agentNotes": [
          "Start it with `llama-server -hf openbmb/MiniCPM-V-4.7-35B-A3B-gguf:Q4_K_M --jinja`, or `ollama run openbmb/minicpm-v4.7:35b-a3b`",
          "For image input in llama.cpp add `mmproj-model-f16.gguf`, or the 4x projector for more visual detail at a higher cost",
          "The GGUF files at the repository root have thinking off. Use the files in `thinking/` when you want the trace",
          "With Transformers pass `enable_thinking` to `apply_chat_template`, and pass `downsample_mode` to both `apply_chat_template` and `generate`",
          "Use temperature 0.7, top_p 0.95 and top_k 100 in instruct mode, as the card recommends",
          "Check tool calls in your runtime first, since the card names no parser. The template uses the Qwen3.5 function-block format",
          "Validate JSON output yourself, since structured output isn't documented"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "C",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 61
          }
        ],
        "editorialScores": {
          "interface": 70,
          "reach": 90,
          "risk": 55,
          "upkeep": 68
        },
        "provenanceScore": 58,
        "checked": {
          "categories": {
            "interface": "2026-11-10",
            "reach": "2026-11-10",
            "risk": "2026-11-10",
            "upkeep": "2026-11-10"
          },
          "last": "2026-11-10",
          "oldest": "2026-11-10",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "ollama run openbmb/minicpm-v4.7:35b-a3b\n# or, with llama.cpp and OpenBMB's own GGUF:\nllama-server -hf openbmb/MiniCPM-V-4.7-35B-A3B-gguf:Q4_K_M --jinja\n# or, with Transformers' server, as the card gives it:\npip install \"transformers[serving]\u003e=5.18.0\"\ntransformers serve openbmb/MiniCPM-V-4.7-35B-A3B --port 8000 --host 0.0.0.0",
        "http": "curl http://localhost:11434/api/chat \\\n  -d '{\"model\": \"openbmb/minicpm-v4.7:35b-a3b\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/minicpm-v-4-7-35b-a3b"
      },
      "sameCompany": [
        "minicpm-v-4-7-1b",
        "minicpm-o-4-5",
        "minicpm5-2b"
      ],
      "weights": {
        "trainedBy": "OpenBMB (ModelBest and Tsinghua NLP Lab)",
        "builtOn": "Qwen3.5 and Qwen3.6 as the language backbone and SigLIP2 as the vision module, per the card's acknowledgements. Not declared in the metadata. The text config is qwen3_5_moe_text with 40 layers and 256 experts",
        "params": "35.2B (3B active)",
        "context": 262144,
        "goodFor": "Vision-language mixture-of-experts model for images, several images and video, with tool calling and thinking off by default, fast for its size with about 3B active parameters.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "MiniCPM-V-4_7-35B-A3B-IQ4_XS",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-gguf/blob/main/MiniCPM-V-4_7-35B-A3B-IQ4_XS.gguf",
            "who": "publisher",
            "precision": "iq4_xs",
            "sizeGB": 18.7,
            "memoryGB": 24,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ],
            "note": "The smallest file at 4 bits. IQ3_M and IQ3_XS (15.4 and 14.5 GB) are below the 4-bit line and are not listed"
          },
          {
            "name": "MiniCPM-V-4.7-35B-A3B-AWQ",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-AWQ",
            "who": "publisher",
            "precision": "w4a16",
            "sizeGB": 22.7,
            "memoryGB": 32,
            "format": "safetensors",
            "runsOn": [
              "vLLM"
            ],
            "note": "AWQ, 4-bit weights with 16-bit activations"
          },
          {
            "name": "MiniCPM-V-4.7-35B-A3B-GPTQ",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-GPTQ",
            "who": "publisher",
            "precision": "w4a16",
            "sizeGB": 22.7,
            "memoryGB": 32,
            "format": "safetensors",
            "runsOn": [
              "vLLM"
            ],
            "note": "GPTQ, 4-bit weights with 16-bit activations"
          },
          {
            "name": "MiniCPM-V-4.7-35B-A3B-int4",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-int4",
            "who": "publisher",
            "precision": "int4",
            "sizeGB": 22.7,
            "memoryGB": 32,
            "format": "safetensors",
            "runsOn": [
              "vLLM"
            ],
            "note": "Listed on the card with the FP8 build under llm-compressor's FP8 and INT4 guide"
          },
          {
            "name": "MiniCPM-V-4_7-35B-A3B-Q5_K_M",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-gguf/blob/main/MiniCPM-V-4_7-35B-A3B-Q5_K_M.gguf",
            "who": "publisher",
            "precision": "q5_k_m",
            "sizeGB": 24.7,
            "memoryGB": 32,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ]
          },
          {
            "name": "MiniCPM-V-4_7-35B-A3B-Q4_K_M",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-gguf/blob/main/MiniCPM-V-4_7-35B-A3B-Q4_K_M.gguf",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 21.2,
            "memoryGB": 32,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ],
            "note": "Add mmproj-model-f16.gguf (1.1 GB) or mmproj-model-f16-4x.gguf (0.9 GB) for image input. The same file with thinking on is in the thinking/ folder"
          },
          {
            "name": "ollama openbmb/minicpm-v4.7:35b-a3b",
            "url": "https://ollama.com/openbmb/minicpm-v4.7",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 22,
            "memoryGB": 32,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "OpenBMB's own namespace on Ollama, not Ollama's library. Q4_K_M, 22 GB as the tags page shows it, with q8_0 (38 GB) and fp16 (70 GB) tags beside it"
          },
          {
            "name": "MiniCPM-V-4.7-35B-A3B-FP8",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-FP8",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 38,
            "memoryGB": 48,
            "format": "safetensors",
            "runsOn": [
              "vLLM",
              "SGLang"
            ]
          },
          {
            "name": "MiniCPM-V-4_7-35B-A3B-Q8_0",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-gguf/blob/main/MiniCPM-V-4_7-35B-A3B-Q8_0.gguf",
            "who": "publisher",
            "precision": "q8_0",
            "sizeGB": 36.9,
            "memoryGB": 48,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ]
          },
          {
            "name": "MiniCPM-V-4_7-35B-A3B-Q6_K",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-gguf/blob/main/MiniCPM-V-4_7-35B-A3B-Q6_K.gguf",
            "who": "publisher",
            "precision": "q6_k",
            "sizeGB": 28.5,
            "memoryGB": 48,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ]
          },
          {
            "name": "MiniCPM-V-4.7-35B-A3B",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 70.4,
            "memoryGB": 96,
            "format": "safetensors",
            "runsOn": [
              "vLLM (ROCm)",
              "SGLang (ROCm)",
              "Transformers"
            ]
          },
          {
            "name": "MiniCPM-V-4_7-35B-A3B-F16",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-gguf/blob/main/MiniCPM-V-4_7-35B-A3B-F16.gguf",
            "who": "publisher",
            "precision": "f16",
            "sizeGB": 69.4,
            "memoryGB": 96,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ]
          }
        ],
        "run": "llama-server -hf openbmb/MiniCPM-V-4.7-35B-A3B-gguf:Q4_K_M --jinja",
        "runBuild": "MiniCPM-V-4_7-35B-A3B-Q4_K_M",
        "checked": "2026-11-10",
        "minMemoryGB": 24
      },
      "family": {
        "lab": "OpenBMB (MiniCPM)",
        "family": "MiniCPM-V 4",
        "url": "https://www.anchorterminal.com/open-weights/#openbmb",
        "others": [
          {
            "name": "MiniCPM-V 4.7 1B",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-1B",
            "params": "1.55B (1,554,476,272 per the safetensors count)",
            "listing": "https://www.anchorterminal.com/tools/minicpm-v-4-7-1b"
          }
        ],
        "olderCount": 22
      },
      "area": "models",
      "provenance": {
        "legalEntity": "OpenBMB (named in the GitHub LICENSE's copyright line)",
        "domain": "openbmb.cn",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://github.com/OpenBMB/MiniCPM-V",
        "securityTxt": "none",
        "checked": "2026-11-10",
        "notes": [
          "No legal entity is named on the card. OpenBMB is the open-source organisation of ModelBest and Tsinghua University's NLP lab, as the MiniCPM5-2B listing records.",
          "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 GitHub README's dated news list (the release on 12 October 2026, DSpark heads on 15 October) and the repositories' commit messages, which say what changed.",
          "openbmb.cn/.well-known/security.txt returns 404 and github.com/OpenBMB/MiniCPM-V has no SECURITY.md.",
          "unchecked: the domain's registration date."
        ],
        "score": 58
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/minicpm-v-4-7-35b-a3b.json"
    },
    "answer": "MiniCPM-V 4.7 35B-A3B scores 61 (C) on agent readiness against MiniCPM5-2B's 59.7 (C), and leads in 0 of 4 scored categories. MiniCPM5-2B leads on agent interface and documentation and upkeep.",
    "b": {
      "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",
      "dns": "minicpm5-2b.grade.anchorterminal.com",
      "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": 59.7,
        "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": 1518,
        "categoryRank": 74,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "capability": 27,
          "interface": 75,
          "reach": 90,
          "risk": 55,
          "upkeep": 92
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-11-04"
        },
        "negative": 0,
        "verdict": "A 2B dense model for local tool calling and long context, with published training data. OpenBMB's own 4-bit builds are under 1.6 GB, and the model loads in vLLM, SGLang, llama.cpp, Ollama and 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 23 discussion questions and fixed the template on 29 September 2026"
        ],
        "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",
          "No OpenBMB reply in the discussions since 29 September 2026; seven questions opened since 5 October wait"
        ],
        "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": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 59.7
          }
        ],
        "editorialScores": {
          "capability": 27,
          "interface": 75,
          "reach": 90,
          "risk": 55,
          "upkeep": 92
        },
        "provenanceScore": 58,
        "checked": {
          "categories": {
            "capability": "2026-11-04",
            "interface": "2026-11-04",
            "reach": "2026-11-04",
            "risk": "2026-11-04",
            "upkeep": "2026-11-04"
          },
          "last": "2026-11-04",
          "lastMoved": "2026-11-04",
          "oldest": "2026-11-04",
          "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-v-4-7-1b",
        "minicpm-v-4-7-35b-a3b",
        "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": 58
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/minicpm5-2b.json",
      "live": {
        "slug": "minicpm5-2b",
        "securityTxt": {
          "url": "https://openbmb.cn/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-11-10T16:08:10.170465559Z"
        },
        "domain": {
          "domain": "openbmb.cn",
          "checkedAt": "2026-11-08T14:50:03.275690576Z"
        },
        "pages": [
          {
            "url": "https://huggingface.co/openbmb/MiniCPM5-2B/commits/main",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-11-10T16:23:40.687483011Z",
            "changedAt": "2026-11-10T16:23:40.687483011Z",
            "fingerprint": "0e9151c731e0"
          }
        ],
        "updatedAt": "2026-11-10T16:23:40.687483011Z"
      }
    },
    "edges": [
      {
        "by": 24,
        "category": "upkeep",
        "leads": "minicpm5-2b",
        "name": "Documentation and upkeep",
        "reasons": {
          "a": "Model card 8, it covers intended use, architecture and parameters but not limitations, context length, languages or a knowledge cut-off. Training data 0, none described. Last change 20, a commit on 3 November 2026. Responsiveness 20, OpenBMB answered 8 of 12 discussions. Version policy 10, earlier versions keep their repositories and the changes are dated and described. File health 10, the files agree. 8 + 0 + 20 + 20 + 10 + 10 = 68.",
          "b": "Model card 17, everything but a knowledge cut-off. Training data 20, all eight training datasets are published on Hugging Face and named per stage with sizes. Last change 15, a template fix on 29 September 2026, 36 days ago, with nothing newer in OpenBMB's MiniCPM5 repositories on Hugging Face (builds last changed 12 September) or its GitHub repository (21 September). Responsiveness 20, OpenBMB members answered 16 of the 23 questions in the discussions, the newest reply on 29 September. Version policy 10, earlier models and checkpoints sit in their own repositories and the GitHub changelog dates each release. File health 10, config, tokenizer, template and card agree and no broken-file report waited on 21 October, though OpenBMB's GGUF, MLX and GPTQ repositories still carry the template from before the 29 September fix."
        },
        "scores": {
          "a": 68,
          "b": 92
        }
      },
      {
        "by": 5,
        "category": "interface",
        "leads": "minicpm5-2b",
        "name": "Agent interface",
        "reasons": {
          "a": "Chat template 20, a Jinja file in the repository. Tool-calling format 10, the card shows the tools array going in but not the call coming back, and names no parser. Trained tool calling 20, the template renders several calls in one turn. Structured output 0, not documented or claimed. Reasoning control 10, enable_thinking per request, off by default, with the trace between markers. Context 10, 262,144 tokens native.",
          "b": "Chat template 20, a Jinja file in the repository. Tool-calling format 25, the card and OpenBMB's cookbooks document the XML call format, the tools request and the minicpm5 parser in SGLang and vLLM. Trained tool calling 20, agent SFT on 500K samples and a template that renders several calls in one turn. Structured output 0, nothing documents asking for JSON. Reasoning control 0, a judgement call, because OpenBMB's own cookbooks call Think the only supported mode for the 2B even though the template accepts enable_thinking false. Context 10, 131,072 tokens native with no rope scaling."
        },
        "scores": {
          "a": 70,
          "b": 75
        }
      }
    ],
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "OpenBMB",
        "b": "OpenBMB",
        "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": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-11-03",
        "b": "2026-09-29",
        "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": "none",
        "b": "3/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "MiniCPM-V 4.7 35B-A3B scores 61 (C) on agent readiness against MiniCPM5-2B's 59.7 (C), and leads in 0 of 4 scored categories. MiniCPM5-2B leads on agent interface and documentation and upkeep.",
        "question": "Which is better for AI agents, MiniCPM-V 4.7 35B-A3B or MiniCPM5-2B?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": null,
        "also": null,
        "goodFor": "Agents that need to read screenshots, documents and video on a local machine with 24 to 32 GB for the model, under a permissive licence",
        "slug": "minicpm-v-4-7-35b-a3b",
        "watchFor": "No limitations section, safety results, agent-use guidance or security contact"
      },
      {
        "aheadOn": [
          "Agent interface, 75 against 70",
          "Documentation and upkeep, 92 against 68"
        ],
        "also": null,
        "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"
      }
    ],
    "history": {
      "minicpm-v-4-7-35b-a3b": null,
      "minicpm5-2b": [
        {
          "causes": [
            "time"
          ],
          "date": "2026-11-04",
          "delta": -0.5,
          "from": 60.2,
          "fromGrade": "C",
          "to": 59.7,
          "toGrade": "C"
        }
      ]
    },
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Agents-A1-4B vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "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/apertus-v1-5-8b-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Apertus v1.5 8B vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "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/apodex-1-1-mini-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Apodex-1.1-mini vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "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/arete-27b-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Arete-27B vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-minicpm-v-4-7-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-minicpm5-2b.json",
        "title": "Arete-27B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "BigBang-v1 vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm-v-4-7-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm5-2b.json",
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm5-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Carbon-X vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-minicpm-v-4-7-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-minicpm5-2b.json",
        "title": "Carbon-X vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Cola2 vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/cola2-vs-minicpm-v-4-7-35b-a3b"
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        "url": "https://www.anchorterminal.com/compare/cola2-vs-minicpm5-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Cosmos-Reason2-2B vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm-v-4-7-35b-a3b"
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm5-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Darwin-36B-Opus vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm-v-4-7-35b-a3b"
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        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm5-2b"
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        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minicpm-v-4-7-35b-a3b"
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      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "MiniCPM5-2B vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-thinkingcap-qwen3-8-27b.json",
        "title": "MiniCPM5-2B vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-thinkingcap-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-unlimited-ocr-2.json",
        "title": "MiniCPM5-2B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-wevisone-vl-2b.json",
        "title": "MiniCPM5-2B vs WeVisOne-VL-2B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-wevisone-vl-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-wevisone-vl-4b.json",
        "title": "MiniCPM5-2B vs WeVisOne-VL-4B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-wevisone-vl-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-zaya1-8b.json",
        "title": "MiniCPM5-2B vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-zaya1-8b"
      }
    ],
    "panel": null,
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 0,
        "edge": "",
        "key": "reach",
        "minicpm-v-4-7-35b-a3b": 90,
        "minicpm5-2b": 90,
        "name": "Reach",
        "weight": 25
      },
      {
        "by": 0,
        "edge": "",
        "key": "risk",
        "minicpm-v-4-7-35b-a3b": 55,
        "minicpm5-2b": 55,
        "name": "Risk",
        "weight": 20
      },
      {
        "by": 5,
        "edge": "minicpm5-2b",
        "key": "interface",
        "minicpm-v-4-7-35b-a3b": 70,
        "minicpm5-2b": 75,
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 24,
        "edge": "minicpm5-2b",
        "key": "upkeep",
        "minicpm-v-4-7-35b-a3b": 68,
        "minicpm5-2b": 92,
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "MiniCPM-V 4.7 35B-A3B scores 61 (C) on agent readiness against MiniCPM5-2B's 59.7 (C), and leads in 0 of 4 scored categories. MiniCPM5-2B leads on agent interface and documentation and upkeep. Both do open-weight models you run yourself.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "minicpm-v-4-7-35b-a3b": "A vision-language cousin for images and video that fits a 24 to 32 GB machine from OpenBMB's own GGUF, under plain Apache 2.0, with a publisher that answers. The card says little about limits, training data or how tool calls come back, so test the tool format in your runtime before relying on it.",
      "minicpm5-2b": "A 2B dense model for local tool calling and long context, with published training data. OpenBMB's own 4-bit builds are under 1.6 GB, and the model loads in vLLM, SGLang, llama.cpp, Ollama and Transformers. The main risks are always-on thinking, no safety results and use conditions beyond Apache 2.0."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-minicpm5-2b",
    "json": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-minicpm5-2b.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-minicpm5-2b.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-minicpm5-2b.min.md"
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  "markdown": "MiniCPM-V 4.7 35B-A3B scores 61 (C) on agent readiness against MiniCPM5-2B's 59.7 (C), and leads in 0 of 4 scored categories. MiniCPM5-2B leads on agent interface and documentation and upkeep. Both do open-weight models you run yourself.\n\n- MiniCPM-V 4.7 35B-A3B: grade C, 61/100, rank #77 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/minicpm-v-4-7-35b-a3b.md · JSON https://www.anchorterminal.com/api/v1/tools/minicpm-v-4-7-35b-a3b.json\n- MiniCPM5-2B: grade C, 59.7/100, rank #94 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/minicpm5-2b.md · JSON https://www.anchorterminal.com/api/v1/tools/minicpm5-2b.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 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### MiniCPM-V 4.7 35B-A3B (C)\n\nGood for: Agents that need to read screenshots, documents and video on a local machine with 24 to 32 GB for the model, under a permissive licence\n\nWatch for: No limitations section, safety results, agent-use guidance or security contact\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- Agent interface, 75 against 70\n- Documentation and upkeep, 92 against 68\n\nWatch for: OpenBMB documents only a Think mode for the 2B, so every answer starts with reasoning\n\n\n## Why the edge\n\n### Documentation and upkeep: MiniCPM5-2B +24\n\n- MiniCPM-V 4.7 35B-A3B (68): Model card 8, it covers intended use, architecture and parameters but not limitations, context length, languages or a knowledge cut-off. Training data 0, none described. Last change 20, a commit on 3 November 2026. Responsiveness 20, OpenBMB answered 8 of 12 discussions. Version policy 10, earlier versions keep their repositories and the changes are dated and described. File health 10, the files agree. 8 + 0 + 20 + 20 + 10 + 10 = 68.\n- MiniCPM5-2B (92): Model card 17, everything but a knowledge cut-off. Training data 20, all eight training datasets are published on Hugging Face and named per stage with sizes. Last change 15, a template fix on 29 September 2026, 36 days ago, with nothing newer in OpenBMB's MiniCPM5 repositories on Hugging Face (builds last changed 12 September) or its GitHub repository (21 September). Responsiveness 20, OpenBMB members answered 16 of the 23 questions in the discussions, the newest reply on 29 September. Version policy 10, earlier models and checkpoints sit in their own repositories and the GitHub changelog dates each release. File health 10, config, tokenizer, template and card agree and no broken-file report waited on 21 October, though OpenBMB's GGUF, MLX and GPTQ repositories still carry the template from before the 29 September fix.\n\n### Agent interface: MiniCPM5-2B +5\n\n- MiniCPM-V 4.7 35B-A3B (70): Chat template 20, a Jinja file in the repository. Tool-calling format 10, the card shows the tools array going in but not the call coming back, and names no parser. Trained tool calling 20, the template renders several calls in one turn. Structured output 0, not documented or claimed. Reasoning control 10, enable_thinking per request, off by default, with the trace between markers. Context 10, 262,144 tokens native.\n- MiniCPM5-2B (75): Chat template 20, a Jinja file in the repository. Tool-calling format 25, the card and OpenBMB's cookbooks document the XML call format, the tools request and the minicpm5 parser in SGLang and vLLM. Trained tool calling 20, agent SFT on 500K samples and a template that renders several calls in one turn. Structured output 0, nothing documents asking for JSON. Reasoning control 0, a judgement call, because OpenBMB's own cookbooks call Think the only supported mode for the 2B even though the template accepts enable_thinking false. Context 10, 131,072 tokens native with no rope scaling.\n\n## Score by category\n\n| Category | Weight | MiniCPM-V 4.7 35B-A3B | MiniCPM5-2B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 90 | 90 | even |\n| Risk | 20% (20 this run) | 55 | 55 | even |\n| Agent interface | 10% (10 this run) | 70 | 75 | MiniCPM5-2B +5 |\n| Documentation and upkeep | 10% (10 this run) | 68 | 92 | MiniCPM5-2B +24 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **59.7 · C** | |\n\n## Facts side by side\n\n| Fact | MiniCPM-V 4.7 35B-A3B | MiniCPM5-2B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | OpenBMB | OpenBMB |\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 | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-11-03 | 2026-09-29 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Agent reviews | none | 3/5 (4) |\n\n## How the scores have moved\n\n### MiniCPM-V 4.7 35B-A3B\n\nNo score change since it was listed.\n\n### MiniCPM5-2B\n\n- -0.5 on 4 November 2026: time\n\n## Verdicts\n\n**MiniCPM-V 4.7 35B-A3B.** A vision-language cousin for images and video that fits a 24 to 32 GB machine from OpenBMB's own GGUF, under plain Apache 2.0, with a publisher that answers. The card says little about limits, training data or how tool calls come back, so test the tool format in your runtime before relying on it.\n\n**MiniCPM5-2B.** A 2B dense model for local tool calling and long context, with published training data. OpenBMB's own 4-bit builds are under 1.6 GB, and the model loads in vLLM, SGLang, llama.cpp, Ollama and Transformers. The main risks are always-on thinking, no safety results and use conditions beyond Apache 2.0.\n\n## Before you call either\n\n### MiniCPM-V 4.7 35B-A3B\n\n1. Start it with `llama-server -hf openbmb/MiniCPM-V-4.7-35B-A3B-gguf:Q4_K_M --jinja`, or `ollama run openbmb/minicpm-v4.7:35b-a3b`\n2. For image input in llama.cpp add `mmproj-model-f16.gguf`, or the 4x projector for more visual detail at a higher cost\n3. The GGUF files at the repository root have thinking off. Use the files in `thinking/` when you want the trace\n4. With Transformers pass `enable_thinking` to `apply_chat_template`, and pass `downsample_mode` to both `apply_chat_template` and `generate`\n5. Use temperature 0.7, top_p 0.95 and top_k 100 in instruct mode, as the card recommends\n6. Check tool calls in your runtime first, since the card names no parser. The template uses the Qwen3.5 function-block format\n7. Validate JSON output yourself, since structured output isn't documented\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## Questions\n\n### Which is better for AI agents, MiniCPM-V 4.7 35B-A3B or MiniCPM5-2B?\n\nMiniCPM-V 4.7 35B-A3B scores 61 (C) on agent readiness against MiniCPM5-2B's 59.7 (C), and leads in 0 of 4 scored categories. MiniCPM5-2B leads on agent interface and documentation and upkeep.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-minicpm5-2b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-minicpm5-2b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"minicpm-v-4-7-35b-a3b\", \"b\": \"minicpm5-2b\"}`. From a terminal: `anchor compare minicpm-v-4-7-35b-a3b minicpm5-2b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/minicpm-v-4-7-35b-a3b.json and https://www.anchorterminal.com/api/v1/tools/minicpm5-2b.json\n\n## Other comparisons with MiniCPM-V 4.7 35B-A3B or MiniCPM5-2B\n\n- [Agents-A1-4B vs MiniCPM-V 4.7 35B-A3B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm-v-4-7-35b-a3b.md)\n- [Agents-A1-4B vs MiniCPM5-2B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm5-2b.md)\n- [Apertus v1.5 8B vs MiniCPM-V 4.7 35B-A3B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm-v-4-7-35b-a3b.md)\n- [Apertus v1.5 8B vs MiniCPM5-2B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm5-2b.md)\n- [Apodex-1.1-mini vs MiniCPM-V 4.7 35B-A3B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm-v-4-7-35b-a3b.md)\n- [Apodex-1.1-mini vs 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