{
  "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": "SmolLM3-3B and MiniCPM5-2B score within a point of each other on agent readiness, 61 (C) and 60.2 (C). MiniCPM5-2B leads on reach and documentation and upkeep.",
    "b": {
      "slug": "smollm3-3b",
      "name": "SmolLM3-3B",
      "vendor": "Hugging Face",
      "vendorUrl": "https://huggingface.co",
      "kind": "weights",
      "category": "open-weights",
      "summary": "SmolLM3-3B is Hugging Face's open-weight dense 3B instruct model with switchable reasoning, tool calling and a 65,536-token native context, published in BF16 safetensors under Apache 2.0 with its training data and recipes.",
      "url": "https://www.anchorterminal.com/tools/smollm3-3b",
      "markdownUrl": "https://www.anchorterminal.com/tools/smollm3-3b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/smollm3-3b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/smollm3-3b.json",
      "repo": "https://huggingface.co/HuggingFaceTB/SmolLM3-3B",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "HuggingFaceTB/SmolLM3-3B"
        },
        {
          "registry": "huggingface",
          "name": "HuggingFaceTB/SmolLM3-3B-ONNX"
        }
      ],
      "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 use, commercial use included, under Apache 2.0. Running it yourself costs the hardware, 6.15 GB for the BF16 files (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/HuggingFaceTB/SmolLM3-3B",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "dense",
        "small",
        "reasoning",
        "tool-calling",
        "multilingual",
        "apache-2.0",
        "safetensors",
        "onnx",
        "self-hosted"
      ],
      "lastRelease": "2025-09-10",
      "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": 1197,
        "categoryRank": 40,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "interface": 80,
          "reach": 85,
          "risk": 65,
          "upkeep": 54
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A tiny, fully open cousin with documented tool calling and switchable thinking, for local subtasks and routing on laptops and CPUs. It needs about 8 GB in BF16, or under 3 GB in Hugging Face's 4-bit ONNX build for ONNX Runtime. The main risks are a 64K native context, no safety results and no repository changes since September 2025.",
        "bestFor": "Agents that want a small, fully transparent tool-calling cousin on a laptop, CPU or edge device",
        "strengths": [
          "Training data, mixture weights, configs and intermediate checkpoints all published",
          "Plain Apache 2.0, no gate, no account",
          "About 7.4 GB in BF16, with Hugging Face's own ONNX builds down to 4-bit for ONNX Runtime",
          "Tool-call format and vLLM parser documented on the card",
          "Thinking turns off per request",
          "Safetensors only, with a SHA-256 for each shard and a Jinja template"
        ],
        "weaknesses": [
          "65,536 tokens trained; 131,072 needs a YaRN edit to config.json",
          "No change to the files since 10 September 2025 and no publisher reply in discussions since November 2025",
          "No safety evaluation or agent-use guidance",
          "No structured-output documentation",
          "No Ollama or LM Studio catalogue entry and no hosted provider",
          "The chat template renders tool results as user turns and drops tool_calls from earlier assistant messages"
        ],
        "agentNotes": [
          "Start it with `vllm serve HuggingFaceTB/SmolLM3-3B --enable-auto-tool-choice --tool-call-parser=hermes`, or tool calls come back as text",
          "Pass `chat_template_kwargs` with `enable_thinking` false for short tasks, since thinking is on by default; a `/think` or `/no_think` flag in the system prompt overrides the kwarg",
          "Put earlier tool calls in the assistant message content, since the template ignores a `tool_calls` field when it renders history",
          "Add the YaRN `rope_scaling` block (factor 2.0, original 65536) to config.json before sending more than 65,536 tokens",
          "Use temperature 0.6 and top_p 0.95, the card's recommended sampling",
          "Needs Transformers v4.53.0 or later; for llama.cpp use a GGUF from ggml-org or another converter, since Hugging Face publishes none",
          "Validate JSON output yourself or use the runtime's guided decoding"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 3.3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "C",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 61
          }
        ],
        "editorialScores": {
          "interface": 80,
          "reach": 85,
          "risk": 65,
          "upkeep": 54
        },
        "provenanceScore": 67,
        "checked": {
          "categories": {
            "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": "pip install -U transformers vllm\nvllm serve HuggingFaceTB/SmolLM3-3B --enable-auto-tool-choice --tool-call-parser=hermes",
        "http": "curl http://localhost:8000/v1/chat/completions -H \"Content-Type: application/json\" -d '{\n  \"model\": \"HuggingFaceTB/SmolLM3-3B\",\n  \"messages\": [{\"role\": \"user\", \"content\": \"Give me a brief explanation of gravity in simple terms.\"}],\n  \"temperature\": 0.6,\n  \"top_p\": 0.95,\n  \"max_tokens\": 16384,\n  \"chat_template_kwargs\": {\"enable_thinking\": false}\n}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/smollm3-3b"
      },
      "sameCompany": [
        "hugging-face-inference-endpoints"
      ],
      "weights": {
        "trainedBy": "Hugging Face",
        "builtOn": "HuggingFaceTB/SmolLM3-3B-Base",
        "params": "3.08B",
        "context": 65536,
        "goodFor": "Small fully open instruct model with switchable reasoning and tool calling, text only, multilingual.",
        "runtimes": [
          "llama.cpp",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "SmolLM3-3B",
            "url": "https://huggingface.co/HuggingFaceTB/SmolLM3-3B",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 6.2,
            "memoryGB": 8,
            "format": "safetensors",
            "runsOn": [
              "vLLM (ROCm)",
              "SGLang (ROCm)"
            ]
          },
          {
            "name": "SmolLM3-3B-ONNX fp16",
            "url": "https://huggingface.co/HuggingFaceTB/SmolLM3-3B-ONNX/blob/main/onnx/model_fp16.onnx_data",
            "who": "publisher",
            "precision": "fp16",
            "sizeGB": 6.2,
            "memoryGB": 8,
            "format": "onnx",
            "note": "ONNX for Transformers.js and ONNX Runtime, none of the runtimes listed here"
          },
          {
            "name": "SmolLM3-3B-ONNX int8",
            "url": "https://huggingface.co/HuggingFaceTB/SmolLM3-3B-ONNX/blob/main/onnx/model_int8.onnx_data",
            "who": "publisher",
            "precision": "int8",
            "sizeGB": 3.1,
            "memoryGB": 8,
            "format": "onnx",
            "note": "ONNX for Transformers.js and ONNX Runtime, none of the runtimes listed here"
          },
          {
            "name": "SmolLM3-3B-ONNX uint8",
            "url": "https://huggingface.co/HuggingFaceTB/SmolLM3-3B-ONNX/blob/main/onnx/model_uint8.onnx_data",
            "who": "publisher",
            "precision": "uint8",
            "sizeGB": 3.1,
            "memoryGB": 8,
            "format": "onnx",
            "note": "ONNX for Transformers.js and ONNX Runtime, none of the runtimes listed here"
          },
          {
            "name": "SmolLM3-3B-ONNX q4",
            "url": "https://huggingface.co/HuggingFaceTB/SmolLM3-3B-ONNX/blob/main/onnx/model_q4.onnx_data",
            "who": "publisher",
            "precision": "q4",
            "sizeGB": 2.8,
            "memoryGB": 8,
            "format": "onnx",
            "note": "ONNX for Transformers.js and ONNX Runtime, none of the runtimes listed here"
          },
          {
            "name": "SmolLM3-3B-ONNX bnb4",
            "url": "https://huggingface.co/HuggingFaceTB/SmolLM3-3B-ONNX/blob/main/onnx/model_bnb4.onnx_data",
            "who": "publisher",
            "precision": "bnb4",
            "sizeGB": 2.7,
            "memoryGB": 8,
            "format": "onnx",
            "note": "ONNX for Transformers.js and ONNX Runtime, none of the runtimes listed here"
          },
          {
            "name": "SmolLM3-3B-ONNX q4f16",
            "url": "https://huggingface.co/HuggingFaceTB/SmolLM3-3B-ONNX/blob/main/onnx/model_q4f16.onnx_data",
            "who": "publisher",
            "precision": "q4f16",
            "sizeGB": 2.1,
            "memoryGB": 8,
            "format": "onnx",
            "note": "ONNX for Transformers.js and ONNX Runtime, none of the runtimes listed here"
          }
        ],
        "run": "vllm serve HuggingFaceTB/SmolLM3-3B --enable-auto-tool-choice --tool-call-parser=hermes",
        "runBuild": "SmolLM3-3B",
        "checked": "2026-10-21",
        "minMemoryGB": 8
      },
      "family": {
        "lab": "Hugging Face (SmolLM)",
        "family": "SmolLM3",
        "url": "https://www.anchorterminal.com/open-weights/#huggingface",
        "others": [
          {
            "name": "SmolLM3-3B-Base",
            "url": "https://huggingface.co/HuggingFaceTB/SmolLM3-3B-Base",
            "params": "3B"
          },
          {
            "name": "SmolLM3-3B-checkpoints",
            "url": "https://huggingface.co/HuggingFaceTB/SmolLM3-3B-checkpoints",
            "params": "3B"
          },
          {
            "name": "SmolLM3-3B-GSM8K-SFT",
            "url": "https://huggingface.co/HuggingFaceTB/SmolLM3-3B-GSM8K-SFT",
            "params": "3B"
          }
        ],
        "olderCount": 20,
        "unrestrictedCopies": 5
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Hugging Face, Inc.",
        "domain": "huggingface.co",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/HuggingFaceTB/SmolLM3-3B/commits/main",
        "securityTxt": "valid",
        "checked": "2026-10-21",
        "notes": [
          "The model is published in HuggingFaceTB (Hugging Face Smol Models Research), the organisation Hugging Face's own launch post at huggingface.co/blog/smollm3 links to. Hugging Face's Terms of Service name Hugging Face, Inc.",
          "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. A few messages say what changed (an EOS token ID update on 8 July 2025, a template fix for vLLM on 9 July 2025); most read Update README.md.",
          "huggingface.co/.well-known/security.txt is valid, with a contact and an expiry of 1 July 2030.",
          "rdap.org has no RDAP service for .co domains, so the registration date wasn't checked."
        ],
        "score": 67
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/smollm3-3b.json"
    },
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "OpenBMB",
        "b": "Hugging Face",
        "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": "2026-09-29",
        "b": "2025-09-10",
        "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": "3.3/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "SmolLM3-3B and MiniCPM5-2B score within a point of each other on agent readiness, 61 (C) and 60.2 (C). MiniCPM5-2B leads on reach and documentation and upkeep.",
        "question": "Which is better for AI agents, MiniCPM5-2B or SmolLM3-3B?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reach, 90 against 85",
          "Documentation and upkeep, 97 against 54"
        ],
        "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"
      },
      {
        "aheadOn": [
          "Risk, 65 against 55",
          "Agent interface, 80 against 75"
        ],
        "also": null,
        "goodFor": "Agents that want a small, fully transparent tool-calling cousin on a laptop, CPU or edge device",
        "slug": "smollm3-3b",
        "watchFor": "65,536 tokens trained; 131,072 needs a YaRN edit to config.json"
      }
    ],
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      "name": "Open-weight models you run yourself"
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        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm5-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-smollm3-3b.json",
        "title": "Agents-A1-4B vs SmolLM3-3B",
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        "title": "Apertus v1.5 8B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-smollm3-3b"
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        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm5-2b"
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        "title": "Apodex-1.1-mini vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-smollm3-3b"
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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/bigbang-v1-vs-smollm3-3b.json",
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-smollm3-3b"
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-smollm3-3b"
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        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm5-2b"
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        "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"
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        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-smollm3-3b.json",
        "title": "DeepSeek V4.1 Flash vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-smollm3-3b"
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        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minicpm5-2b.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minicpm5-2b"
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        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-smollm3-3b"
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        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minicpm5-2b.json",
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        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minicpm5-2b"
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        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-smollm3-3b"
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        "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minicpm5-2b.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minicpm5-2b"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-smollm3-3b"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minicpm5-2b"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minicpm5-2b"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm5-2b"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minicpm5-2b"
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      },
      {
        "json": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-smollm3-3b.json",
        "title": "Ornith-1.5-9B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-smollm3-3b.json",
        "title": "Qwen3-30B-A3B-Instruct-2507 vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-smollm3-3b.json",
        "title": "Qwen3-4B-Instruct-2507 vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-smollm3-3b.json",
        "title": "Qwen3.5-0.8B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-smollm3-3b.json",
        "title": "Qwen3.5-122B-A10B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-smollm3-3b.json",
        "title": "Qwen3.5-2B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-smollm3-3b.json",
        "title": "Qwen3.5-397B-A17B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-smollm3-3b.json",
        "title": "Qwen3.5-4B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-smollm3-3b.json",
        "title": "Qwen3.5-9B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-smollm3-3b.json",
        "title": "Qwen3.6-27B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-smollm3-3b.json",
        "title": "Qwen3.6-35B-A3B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-smollm3-3b.json",
        "title": "Qwen3.8-27B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-smollm3-3b.json",
        "title": "Qwen3.8-Flash-Next vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-smollm3-3b.json",
        "title": "Qwen3-Coder-30B-A3B-Instruct vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-smollm3-3b.json",
        "title": "Qwen3-Coder-Next vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-smollm3-3b.json",
        "title": "Qwen3-Omni-30B-A3B-Instruct vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-smollm3-3b.json",
        "title": "Qwen3-VL-2B-Instruct vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-smollm3-3b.json",
        "title": "Qwen3-VL-30B-A3B-Instruct vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-smollm3-3b.json",
        "title": "Qwen3-VL-32B-Instruct vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-smollm3-3b.json",
        "title": "Qwen3-VL-4B-Instruct vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-smollm3-3b.json",
        "title": "Qwen3-VL-8B-Instruct vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-smollm3-3b.json",
        "title": "Qwopus3.8-27B-Flash-V2 vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/smollm3-3b-vs-spark-x2-6-4b.json",
        "title": "SmolLM3-3B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/smollm3-3b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/smollm3-3b-vs-swift-1-5-qwen3-8-27b.json",
        "title": "SmolLM3-3B vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/smollm3-3b-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/smollm3-3b-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "SmolLM3-3B vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/smollm3-3b-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/smollm3-3b-vs-thinkingcap-qwen3-8-27b.json",
        "title": "SmolLM3-3B vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/smollm3-3b-vs-thinkingcap-qwen3-8-27b"
      }
    ],
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 5,
        "edge": "minicpm5-2b",
        "key": "reach",
        "minicpm5-2b": 90,
        "name": "Reach",
        "smollm3-3b": 85,
        "weight": 25
      },
      {
        "by": 10,
        "edge": "smollm3-3b",
        "key": "risk",
        "minicpm5-2b": 55,
        "name": "Risk",
        "smollm3-3b": 65,
        "weight": 20
      },
      {
        "by": 5,
        "edge": "smollm3-3b",
        "key": "interface",
        "minicpm5-2b": 75,
        "name": "Agent interface",
        "smollm3-3b": 80,
        "weight": 10
      },
      {
        "by": 43,
        "edge": "minicpm5-2b",
        "key": "upkeep",
        "minicpm5-2b": 97,
        "name": "Documentation and upkeep",
        "smollm3-3b": 54,
        "weight": 10
      }
    ],
    "summary": "SmolLM3-3B and MiniCPM5-2B score within a point of each other on agent readiness, 61 (C) and 60.2 (C). MiniCPM5-2B leads on reach and documentation and upkeep. 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.",
      "smollm3-3b": "A tiny, fully open cousin with documented tool calling and switchable thinking, for local subtasks and routing on laptops and CPUs. It needs about 8 GB in BF16, or under 3 GB in Hugging Face's 4-bit ONNX build for ONNX Runtime. The main risks are a 64K native context, no safety results and no repository changes since September 2025."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-smollm3-3b",
    "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-smollm3-3b.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-smollm3-3b.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-smollm3-3b.min.md"
  },
  "markdown": "SmolLM3-3B and MiniCPM5-2B score within a point of each other on agent readiness, 61 (C) and 60.2 (C). MiniCPM5-2B leads on reach and documentation and upkeep. 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- SmolLM3-3B: grade C, 61/100, rank #47 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/smollm3-3b.md · JSON https://www.anchorterminal.com/api/v1/tools/smollm3-3b.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 85\n- Documentation and upkeep, 97 against 54\n\nWatch for: OpenBMB documents only a Think mode for the 2B, so every answer starts with reasoning\n\n### SmolLM3-3B (C)\n\nGood for: Agents that want a small, fully transparent tool-calling cousin on a laptop, CPU or edge device\n\nAhead on:\n- Risk, 65 against 55\n- Agent interface, 80 against 75\n\nWatch for: 65,536 tokens trained; 131,072 needs a YaRN edit to config.json\n\n\n## Score by category\n\n| Category | Weight | MiniCPM5-2B | SmolLM3-3B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 90 | 85 | MiniCPM5-2B +5 |\n| Risk | 20% (20 this run) | 55 | 65 | SmolLM3-3B +10 |\n| Agent interface | 10% (10 this run) | 75 | 80 | SmolLM3-3B +5 |\n| Documentation and upkeep | 10% (10 this run) | 97 | 54 | MiniCPM5-2B +43 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **60.2 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | MiniCPM5-2B | SmolLM3-3B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | OpenBMB | Hugging Face |\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 | 2026-09-29 | 2025-09-10 |\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) | 3.3/5 (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**SmolLM3-3B.** A tiny, fully open cousin with documented tool calling and switchable thinking, for local subtasks and routing on laptops and CPUs. It needs about 8 GB in BF16, or under 3 GB in Hugging Face's 4-bit ONNX build for ONNX Runtime. The main risks are a 64K native context, no safety results and no repository changes since September 2025.\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### SmolLM3-3B\n\n1. Start it with `vllm serve HuggingFaceTB/SmolLM3-3B --enable-auto-tool-choice --tool-call-parser=hermes`, or tool calls come back as text\n2. Pass `chat_template_kwargs` with `enable_thinking` false for short tasks, since thinking is on by default; a `/think` or `/no_think` flag in the system prompt overrides the kwarg\n3. Put earlier tool calls in the assistant message content, since the template ignores a `tool_calls` field when it renders history\n4. Add the YaRN `rope_scaling` block (factor 2.0, original 65536) to config.json before sending more than 65,536 tokens\n5. Use temperature 0.6 and top_p 0.95, the card's recommended sampling\n6. Needs Transformers v4.53.0 or later; for llama.cpp use a GGUF from ggml-org or another converter, since Hugging Face publishes none\n7. Validate JSON output yourself or use the runtime's guided decoding\n\n## Questions\n\n### Which is better for AI agents, MiniCPM5-2B or SmolLM3-3B?\n\nSmolLM3-3B and MiniCPM5-2B score within a point of each other on agent readiness, 61 (C) and 60.2 (C). MiniCPM5-2B leads on reach and documentation and upkeep.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/minicpm5-2b-vs-smollm3-3b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/minicpm5-2b-vs-smollm3-3b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"minicpm5-2b\", \"b\": \"smollm3-3b\"}`. From a terminal: `anchor compare minicpm5-2b smollm3-3b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/minicpm5-2b.json and https://www.anchorterminal.com/api/v1/tools/smollm3-3b.json\n\n## Other comparisons with MiniCPM5-2B or SmolLM3-3B\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 SmolLM3-3B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-smollm3-3b.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 SmolLM3-3B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-smollm3-3b.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 SmolLM3-3B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-smollm3-3b.md)\n- [BigBang-v1 vs 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