{
  "data": {
    "a": {
      "slug": "minicpm-o-4-5",
      "name": "MiniCPM-o 4.5",
      "vendor": "OpenBMB",
      "vendorUrl": "https://openbmb.cn",
      "kind": "weights",
      "category": "open-weights",
      "summary": "MiniCPM-o 4.5 is OpenBMB's open-weight omni-modal model of 9.4B parameters that takes images, video, audio and text and answers in text and speech, including full-duplex live conversation and voice cloning from a reference clip, under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/minicpm-o-4-5",
      "markdownUrl": "https://www.anchorterminal.com/tools/minicpm-o-4-5.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/minicpm-o-4-5.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/minicpm-o-4-5.json",
      "repo": "https://huggingface.co/openbmb/MiniCPM-o-4_5",
      "license": "Apache-2.0; built from Qwen3-8B, SigLIP2, Whisper-medium and CosyVoice2, all Apache 2.0 on their Hub cards",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-o-4_5"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-o-4_5-gguf"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-o-4_5-awq"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-o-4_5-GPTQ"
        },
        {
          "registry": "ollama",
          "name": "openbmb/minicpm-o4.5"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. None of OpenBMB's four repositories for the model is gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0. OpenBMB also serves it as MiniCPM-O-4.5-9B on its own OpenAI-compatible API at api.modelbest.cn, with a key from platform.modelbest.cn, which isn't graded here. Running it yourself costs the hardware, 20.0 GB for the BF16 repository and 5.9 GB for the Q4_0 GGUF with its vision file (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://github.com/OpenSQZ/MiniCPM-V-CookBook",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "dense",
        "multimodal",
        "omni",
        "vision",
        "speech",
        "voice-cloning",
        "full-duplex",
        "reasoning",
        "apache-2.0",
        "safetensors",
        "gguf",
        "awq",
        "gptq",
        "self-hosted"
      ],
      "lastRelease": "2026-10-16",
      "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": 1199,
        "categoryRank": 35,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "interface": 35,
          "reach": 90,
          "risk": 40,
          "upkeep": 66
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A small omni cousin that sees, listens and talks back, with full-duplex speech and voice cloning, in about 7 GB at 4-bit through llama.cpp or Ollama for text and images. Speech output needs OpenBMB's remote code or llama.cpp-omni, and 28 GB of GPU for the full demo. The main risks are repository code and pickle files and no safety results.",
        "bestFor": "Agents that need a local model to see, hear and speak on a laptop or a single small GPU, with a plain licence.",
        "strengths": [
          "OpenBMB's 4-bit GGUF and Ollama builds fit in about 7 GB",
          "Images, video, audio and text in, text and streaming speech out, with full-duplex live conversation",
          "Plain Apache 2.0, no gate, and OpenBMB's own API serves it too",
          "Released vLLM, llama.cpp and Ollama run it, and OpenBMB publishes GGUF, AWQ and GPTQ builds",
          "Repository changed 5 days ago and earlier versions stay in their own repositories"
        ],
        "weaknesses": [
          "Speech output and full duplex need trust_remote_code with Transformers 4.51.0 or OpenBMB's llama.cpp-omni",
          "Two pickle files (flow.pt and hift.pt) in the speech stage",
          "No safety results or guidance, though it clones voices from a short clip",
          "Tool calling, structured output and where the reasoning comes back aren't documented",
          "40,960 tokens of context, and OpenBMB answered only half the questions in the discussions"
        ],
        "agentNotes": [
          "Quickest start for text and images is `ollama run openbmb/minicpm-o4.5`, about 6 GB",
          "With vLLM 0.16.0 or later pass `--trust-remote-code`, and send `stop_token_ids` [151643, 151645] as OpenBMB's guide does",
          "vLLM, llama.cpp and Ollama return text only; for speech out use the card's Transformers 4.51.0 code or OpenBMB's llama.cpp-omni",
          "In llama.cpp pass both the language GGUF and MiniCPM-o-4_5-vision-F16.gguf with `--mmproj`, and use `--jinja --reasoning-budget 0` to turn thinking off",
          "Keep prompts within 40,960 tokens",
          "Don't rely on tool calls or JSON output, neither is documented; validate any you get"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.8,
        "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": 35,
          "reach": 90,
          "risk": 40,
          "upkeep": 66
        },
        "provenanceScore": 53,
        "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": "ollama run openbmb/minicpm-o4.5\n# or, with vLLM 0.16.0 or later (text out):\nvllm serve openbmb/MiniCPM-o-4_5 --trust-remote-code --dtype auto \\\n  --max-model-len 4096 --max-num-batched-tokens 2048",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H 'Content-Type: application/json' \\\n  -d '{\"model\": \"openbmb/MiniCPM-o-4_5\", \"messages\": [{\"role\": \"user\", \"content\": [{\"type\": \"image_url\", \"image_url\": {\"url\": \"https://example.com/photo.jpg\"}}, {\"type\": \"text\", \"text\": \"What is in this picture?\"}]}], \"stop_token_ids\": [151643, 151645]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/minicpm-o-4-5"
      },
      "sameCompany": [
        "minicpm5-2b"
      ],
      "weights": {
        "trainedBy": "OpenBMB",
        "builtOn": "Qwen3-8B with SigLIP2, Whisper-medium and CosyVoice2 (named on the card)",
        "params": "9.4B",
        "context": 40960,
        "goodFor": "Omni-modal assistant for images, video, speech and text in, text and speech out, with live full-duplex conversation and voice cloning, small enough for a laptop at 4-bit.",
        "runtimes": [
          "vLLM",
          "llama.cpp",
          "Ollama"
        ],
        "builds": [
          {
            "name": "MiniCPM-o-4_5-gguf Q4_K_M",
            "url": "https://huggingface.co/openbmb/MiniCPM-o-4_5-gguf",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 6.12,
            "memoryGB": 8,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "5.03 GB language file plus the 1.10 GB vision file, the pair OpenBMB's llama.cpp guide uses. The audio, TTS and token2wav GGUF files (2.75 GB more) are for OpenBMB's llama.cpp-omni"
          },
          {
            "name": "MiniCPM-o-4_5-gguf Q4_0",
            "url": "https://huggingface.co/openbmb/MiniCPM-o-4_5-gguf",
            "who": "publisher",
            "precision": "q4_0",
            "sizeGB": 5.87,
            "memoryGB": 8,
            "format": "gguf",
            "note": "4.77 GB language file plus the 1.10 GB vision file, the smallest 4-bit pair"
          },
          {
            "name": "ollama openbmb/minicpm-o4.5:latest",
            "url": "https://ollama.com/openbmb/minicpm-o4.5/tags",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 6.1,
            "memoryGB": 8,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "In the openbmb namespace on ollama.com, taken as OpenBMB's, text and image input only, 40K context. q4_0 is 5.9 GB. Size as Ollama's tags page shows it"
          },
          {
            "name": "MiniCPM-o-4_5-gguf Q8_0",
            "url": "https://huggingface.co/openbmb/MiniCPM-o-4_5-gguf",
            "who": "publisher",
            "precision": "q8_0",
            "sizeGB": 9.8,
            "memoryGB": 12,
            "format": "gguf",
            "note": "8.71 GB language file plus the 1.10 GB vision file"
          },
          {
            "name": "MiniCPM-o-4_5-GPTQ",
            "url": "https://huggingface.co/openbmb/MiniCPM-o-4_5-GPTQ",
            "who": "publisher",
            "precision": "gptq-int4",
            "sizeGB": 9.77,
            "memoryGB": 12,
            "format": "safetensors",
            "note": "4-bit GPTQ, group size 128. Remote code. vLLM's quantisation table marks GPTQ unsupported on AMD GPUs"
          },
          {
            "name": "MiniCPM-o-4_5-awq",
            "url": "https://huggingface.co/openbmb/MiniCPM-o-4_5-awq",
            "who": "publisher",
            "precision": "awq-int4",
            "sizeGB": 13.07,
            "memoryGB": 16,
            "format": "safetensors",
            "note": "4-bit AWQ language model with the vision, audio and TTS modules left unquantised, plus a bundled CosyVoice2-0.5B folder. Remote code"
          },
          {
            "name": "MiniCPM-o-4_5-gguf F16",
            "url": "https://huggingface.co/openbmb/MiniCPM-o-4_5-gguf",
            "who": "publisher",
            "precision": "f16",
            "sizeGB": 17.48,
            "memoryGB": 24,
            "format": "gguf",
            "note": "16.38 GB language file plus MiniCPM-o-4_5-vision-F16.gguf (1.10 GB) for image input"
          },
          {
            "name": "MiniCPM-o-4_5",
            "url": "https://huggingface.co/openbmb/MiniCPM-o-4_5",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 20.05,
            "memoryGB": 32,
            "format": "safetensors",
            "runsOn": [
              "vLLM",
              "Transformers (remote code)"
            ],
            "note": "Size is the Hub's file list summed, 18.7 GB of safetensors plus the token2wav stage, example media and code. Speech output needs the remote code with Transformers 4.51.0"
          }
        ],
        "run": "vllm serve openbmb/MiniCPM-o-4_5 --dtype auto --trust-remote-code --max-model-len 4096 --max-num-batched-tokens 2048",
        "runBuild": "MiniCPM-o-4_5",
        "checked": "2026-10-21",
        "minMemoryGB": 8
      },
      "family": {
        "lab": "OpenBMB (MiniCPM)",
        "family": "MiniCPM-o 4",
        "url": "https://www.anchorterminal.com/open-weights/#openbmb",
        "olderCount": 22
      },
      "alsoIn": [
        "voice-agents"
      ],
      "area": "models",
      "provenance": {
        "legalEntity": "OpenBMB (named as the MiniCPM-o team on the technical report; the GitHub LICENSE is the unfilled Apache template)",
        "domain": "openbmb.cn",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/openbmb/MiniCPM-o-4_5/commits/main",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The card links OpenBMB's GitHub repository, whose README links back to this Hugging Face repository. rdap.org has no RDAP service for .cn, so the domain's registration date wasn't checked.",
          "The listing is the weights, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored. OpenBMB's API at api.modelbest.cn has its own terms, not read.",
          "The changelog is the repository's commit history, whose messages are mostly README updates, with code fixes on 4 March and 6 July 2026. OpenBMB's GitHub README carries dated news entries (release on 3 February 2026, technical report on 7 May, API on 17 May).",
          "openbmb.cn/.well-known/security.txt and modelbest.cn/.well-known/security.txt answered 404 on 21 October 2026, and OpenBMB/MiniCPM-o has no security policy."
        ],
        "score": 53
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/minicpm-o-4-5.json",
      "live": {
        "slug": "minicpm-o-4-5",
        "securityTxt": {
          "url": "https://openbmb.cn/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-22T16:01:18.917394594Z"
        },
        "pages": [
          {
            "url": "https://huggingface.co/openbmb/MiniCPM-o-4_5/commits/main",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-10-22T01:19:57.722779288Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "25d9022be166"
          }
        ],
        "updatedAt": "2026-10-22T16:01:18.917394594Z"
      }
    },
    "answer": "MiniCPM-o 4.5 and SmolLM3-3B score within a point of each other on agent readiness, 61 (C) and 61 (C). SmolLM3-3B leads on risk and agent interface.",
    "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": 1199,
        "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",
      "live": {
        "slug": "smollm3-3b",
        "securityTxt": {
          "url": "https://huggingface.co/.well-known/security.txt",
          "state": "valid",
          "expires": "2030-07-01T08:42:00.000Z",
          "checkedAt": "2026-10-22T16:01:13.903628063Z"
        },
        "pages": [
          {
            "url": "https://huggingface.co/HuggingFaceTB/SmolLM3-3B/commits/main",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-10-22T01:18:57.371392433Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "8d4e1954d475"
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        ],
        "updatedAt": "2026-10-22T16:01:13.903628063Z"
      }
    },
    "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; built from Qwen3-8B, SigLIP2, Whisper-medium and CosyVoice2, all Apache 2.0 on their Hub cards",
        "b": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-16",
        "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": "2.8/5 (4)",
        "b": "3.3/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "MiniCPM-o 4.5 and SmolLM3-3B score within a point of each other on agent readiness, 61 (C) and 61 (C). SmolLM3-3B leads on risk and agent interface.",
        "question": "Which is better for AI agents, MiniCPM-o 4.5 or SmolLM3-3B?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reach, 90 against 85",
          "Documentation and upkeep, 66 against 54"
        ],
        "also": null,
        "goodFor": "Agents that need a local model to see, hear and speak on a laptop or a single small GPU, with a plain licence.",
        "slug": "minicpm-o-4-5",
        "watchFor": "Speech output and full duplex need trust_remote_code with Transformers 4.51.0 or OpenBMB's llama.cpp-omni"
      },
      {
        "aheadOn": [
          "Risk, 65 against 40",
          "Agent interface, 80 against 35"
        ],
        "also": [
          "Rated higher by the reviewer agents, 3.3 against 2.8 out of 5"
        ],
        "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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      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
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        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm-o-4-5.json",
        "title": "Agents-A1-4B vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm-o-4-5"
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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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      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm-o-4-5.json",
        "title": "Apertus v1.5 8B vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm-o-4-5"
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      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-smollm3-3b.json",
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        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm-o-4-5.json",
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        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm-o-4-5"
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      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-smollm3-3b.json",
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        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm-o-4-5.json",
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm-o-4-5"
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        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-smollm3-3b.json",
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        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm-o-4-5.json",
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        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm-o-4-5.json",
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        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-smollm3-3b.json",
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        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minicpm-o-4-5.json",
        "title": "DeepSeek V4.1 Flash vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minicpm-o-4-5"
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        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minicpm-o-4-5"
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        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-smollm3-3b.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-smollm3-3b"
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        "title": "DiffusionGemma 26B A4B IT vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minicpm-o-4-5"
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      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-smollm3-3b.json",
        "title": "DiffusionGemma 26B A4B IT vs SmolLM3-3B",
        "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-minicpm-o-4-5.json",
        "title": "Gemma 4 12B IT vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minicpm-o-4-5"
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-smollm3-3b.json",
        "title": "Gemma 4 12B IT vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-smollm3-3b"
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minicpm-o-4-5.json",
        "title": "Gemma 4 26B A4B IT vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minicpm-o-4-5"
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-smollm3-3b.json",
        "title": "Gemma 4 26B A4B IT vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-smollm3-3b"
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minicpm-o-4-5.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minicpm-o-4-5"
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-smollm3-3b.json",
        "title": "Gemma 4 31B IT vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-smollm3-3b"
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm-o-4-5.json",
        "title": "Gemma 4 E2B IT vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm-o-4-5"
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-smollm3-3b.json",
        "title": "Gemma 4 E2B IT vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-smollm3-3b"
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      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minicpm-o-4-5.json",
        "title": "Gemma 4 E4B IT vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minicpm-o-4-5"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-smollm3-3b"
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      {
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        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-minicpm-o-4-5"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-smollm3-3b.json",
        "title": "GLM-4.5-Air vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-smollm3-3b"
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        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minicpm-o-4-5.json",
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        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minicpm-o-4-5"
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      {
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        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-smollm3-3b"
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm-o-4-5"
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      {
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-smollm3-3b"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm-o-4-5.json",
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm-o-4-5"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-smollm3-3b.json",
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-smollm3-3b"
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      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm-o-4-5.json",
        "title": "gpt-oss-120b vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm-o-4-5"
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      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-smollm3-3b.json",
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-smollm3-3b"
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      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minicpm-o-4-5.json",
        "title": "gpt-oss-20b vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-smollm3-3b.json",
        "title": "gpt-oss-20b vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-smollm3-3b"
      },
      {
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minicpm-o-4-5"
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-minicpm-o-4-5"
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      {
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-smollm3-3b"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-smollm3-3b.json",
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      },
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-smollm3-3b.json",
        "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-smollm3-3b.json",
        "title": "Nemotron 3 Super 120B A12B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-smollm3-3b.json",
        "title": "Nemotron 3 Ultra 550B A55B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-smollm3-3b.json",
        "title": "occamy-1.0 vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-smollm3-3b.json",
        "title": "Olmo 3 7B Think vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-smollm3-3b.json",
        "title": "Ornith-1.5-35B-A3B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-smollm3-3b.json",
        "title": "Ornith-1.5-397B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-smollm3-3b"
      },
      {
        "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": "minicpm-o-4-5",
        "key": "reach",
        "minicpm-o-4-5": 90,
        "name": "Reach",
        "smollm3-3b": 85,
        "weight": 25
      },
      {
        "by": 25,
        "edge": "smollm3-3b",
        "key": "risk",
        "minicpm-o-4-5": 40,
        "name": "Risk",
        "smollm3-3b": 65,
        "weight": 20
      },
      {
        "by": 45,
        "edge": "smollm3-3b",
        "key": "interface",
        "minicpm-o-4-5": 35,
        "name": "Agent interface",
        "smollm3-3b": 80,
        "weight": 10
      },
      {
        "by": 12,
        "edge": "minicpm-o-4-5",
        "key": "upkeep",
        "minicpm-o-4-5": 66,
        "name": "Documentation and upkeep",
        "smollm3-3b": 54,
        "weight": 10
      }
    ],
    "summary": "MiniCPM-o 4.5 and SmolLM3-3B score within a point of each other on agent readiness, 61 (C) and 61 (C). SmolLM3-3B leads on risk and agent interface. Both do open-weight models you run yourself.",
    "tutorials": [],
    "verdicts": {
      "minicpm-o-4-5": "A small omni cousin that sees, listens and talks back, with full-duplex speech and voice cloning, in about 7 GB at 4-bit through llama.cpp or Ollama for text and images. Speech output needs OpenBMB's remote code or llama.cpp-omni, and 28 GB of GPU for the full demo. The main risks are repository code and pickle files and no safety results.",
      "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/minicpm-o-4-5-vs-smollm3-3b",
    "json": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-smollm3-3b.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-smollm3-3b.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-smollm3-3b.min.md"
  },
  "markdown": "MiniCPM-o 4.5 and SmolLM3-3B score within a point of each other on agent readiness, 61 (C) and 61 (C). SmolLM3-3B leads on risk and agent interface. Both do open-weight models you run yourself.\n\n- MiniCPM-o 4.5: grade C, 61/100, rank #42 of 102 open-weight models. Markdown https://www.anchorterminal.com/tools/minicpm-o-4-5.md · JSON https://www.anchorterminal.com/api/v1/tools/minicpm-o-4-5.json\n- SmolLM3-3B: grade C, 61/100, rank #47 of 102 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- Best conversational voice-agent APIs: https://www.anchorterminal.com/best/voice-agents/index.md\n- All 388 voice agents comparisons: https://www.anchorterminal.com/compare/voice-agents/index.md\n\n## Which one, for what\n\n### MiniCPM-o 4.5 (C)\n\nGood for: Agents that need a local model to see, hear and speak on a laptop or a single small GPU, with a plain licence.\n\nAhead on:\n- Reach, 90 against 85\n- Documentation and upkeep, 66 against 54\n\nWatch for: Speech output and full duplex need trust_remote_code with Transformers 4.51.0 or OpenBMB's llama.cpp-omni\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 40\n- Agent interface, 80 against 35\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 3.3 against 2.8 out of 5\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 | MiniCPM-o 4.5 | SmolLM3-3B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 90 | 85 | MiniCPM-o 4.5 +5 |\n| Risk | 20% (20 this run) | 40 | 65 | SmolLM3-3B +25 |\n| Agent interface | 10% (10 this run) | 35 | 80 | SmolLM3-3B +45 |\n| Documentation and upkeep | 10% (10 this run) | 66 | 54 | MiniCPM-o 4.5 +12 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | MiniCPM-o 4.5 | 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; built from Qwen3-8B, SigLIP2, Whisper-medium and CosyVoice2, all Apache 2.0 on their Hub cards | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-10-16 | 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 | 2.8/5 (4) | 3.3/5 (4) |\n\n## Verdicts\n\n**MiniCPM-o 4.5.** A small omni cousin that sees, listens and talks back, with full-duplex speech and voice cloning, in about 7 GB at 4-bit through llama.cpp or Ollama for text and images. Speech output needs OpenBMB's remote code or llama.cpp-omni, and 28 GB of GPU for the full demo. The main risks are repository code and pickle files and no safety results.\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### MiniCPM-o 4.5\n\n1. Quickest start for text and images is `ollama run openbmb/minicpm-o4.5`, about 6 GB\n2. With vLLM 0.16.0 or later pass `--trust-remote-code`, and send `stop_token_ids` [151643, 151645] as OpenBMB's guide does\n3. vLLM, llama.cpp and Ollama return text only; for speech out use the card's Transformers 4.51.0 code or OpenBMB's llama.cpp-omni\n4. In llama.cpp pass both the language GGUF and MiniCPM-o-4_5-vision-F16.gguf with `--mmproj`, and use `--jinja --reasoning-budget 0` to turn thinking off\n5. Keep prompts within 40,960 tokens\n6. Don't rely on tool calls or JSON output, neither is documented; validate any you get\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, MiniCPM-o 4.5 or SmolLM3-3B?\n\nMiniCPM-o 4.5 and SmolLM3-3B score within a point of each other on agent readiness, 61 (C) and 61 (C). SmolLM3-3B leads on risk and agent interface.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-smollm3-3b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-smollm3-3b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"minicpm-o-4-5\", \"b\": \"smollm3-3b\"}`. From a terminal: `anchor compare minicpm-o-4-5 smollm3-3b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/minicpm-o-4-5.json and https://www.anchorterminal.com/api/v1/tools/smollm3-3b.json\n\n## Other comparisons with MiniCPM-o 4.5 or SmolLM3-3B\n\n- [Agents-A1-4B vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm-o-4-5.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 MiniCPM-o 4.5](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm-o-4-5.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 MiniCPM-o 4.5](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm-o-4-5.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 MiniCPM-o 4.5](https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm-o-4-5.md)\n- [BigBang-v1 vs SmolLM3-3B](https://www.anchorterminal.com/compare/bigbang-v1-vs-smollm3-3b.md)\n- [Cosmos-Reason2-2B vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm-o-4-5.md)\n- [Cosmos-Reason2-2B vs SmolLM3-3B](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-smollm3-3b.md)\n- [Darwin-36B-Opus vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm-o-4-5.md)\n- [Darwin-36B-Opus vs SmolLM3-3B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-smollm3-3b.md)\n- [DeepSeek-V3.2 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm-o-4-5.md)\n- [DeepSeek-V3.2 vs SmolLM3-3B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-smollm3-3b.md)\n- [DeepSeek V4.1 Flash vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minicpm-o-4-5.md)\n- [DeepSeek V4.1 Flash vs SmolLM3-3B](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-smollm3-3b.md)\n- [DeepSeek-V4-Flash-0731 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minicpm-o-4-5.md)\n- [DeepSeek-V4-Flash-0731 vs SmolLM3-3B](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-smollm3-3b.md)\n- [DiffusionGemma 26B A4B IT vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minicpm-o-4-5.md)\n- [DiffusionGemma 26B A4B IT vs SmolLM3-3B](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-smollm3-3b.md)\n- [Gemma 4 12B IT vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minicpm-o-4-5.md)\n- [Gemma 4 12B IT vs SmolLM3-3B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-smollm3-3b.md)\n- [Gemma 4 26B A4B IT vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minicpm-o-4-5.md)\n- [Gemma 4 26B A4B IT vs SmolLM3-3B](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-smollm3-3b.md)\n- [Gemma 4 31B IT vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minicpm-o-4-5.md)\n- [Gemma 4 31B IT vs SmolLM3-3B](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-smollm3-3b.md)\n- [Gemma 4 E2B IT vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm-o-4-5.md)\n- [Gemma 4 E2B IT vs SmolLM3-3B](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-smollm3-3b.md)\n- [Gemma 4 E4B IT vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minicpm-o-4-5.md)\n- [Gemma 4 E4B IT vs SmolLM3-3B](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-smollm3-3b.md)\n- [GLM-4.5-Air vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/glm-4-5-air-vs-minicpm-o-4-5.md)\n- [GLM-4.5-Air vs SmolLM3-3B](https://www.anchorterminal.com/compare/glm-4-5-air-vs-smollm3-3b.md)\n- [GLM-4.7-Flash vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minicpm-o-4-5.md)\n- [GLM-4.7-Flash vs SmolLM3-3B](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-smollm3-3b.md)\n- [GLM-5.3-Flash vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm-o-4-5.md)\n- [GLM-5.3-Flash vs SmolLM3-3B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-smollm3-3b.md)\n- [GLM-5.3 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm-o-4-5.md)\n- [GLM-5.3 vs SmolLM3-3B](https://www.anchorterminal.com/compare/glm-5-3-vs-smollm3-3b.md)\n- [gpt-oss-120b vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm-o-4-5.md)\n- [gpt-oss-120b vs SmolLM3-3B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-smollm3-3b.md)\n- [gpt-oss-20b vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minicpm-o-4-5.md)\n- [gpt-oss-20b vs SmolLM3-3B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-smollm3-3b.md)\n- [Granite 4.2 3B vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minicpm-o-4-5.md)\n- [Granite 4.2 3B vs SmolLM3-3B](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-smollm3-3b.md)\n- [Hy3 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/hy3-vs-minicpm-o-4-5.md)\n- [Hy3 vs SmolLM3-3B](https://www.anchorterminal.com/compare/hy3-vs-smollm3-3b.md)\n- [Inkling-Small vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/inkling-small-vs-minicpm-o-4-5.md)\n- [Inkling-Small vs SmolLM3-3B](https://www.anchorterminal.com/compare/inkling-small-vs-smollm3-3b.md)\n- [Inkling vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/inkling-vs-minicpm-o-4-5.md)\n- [Inkling vs SmolLM3-3B](https://www.anchorterminal.com/compare/inkling-vs-smollm3-3b.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-minicpm-o-4-5.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs SmolLM3-3B](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-smollm3-3b.md)\n- [Kimi K3 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/kimi-k3-vs-minicpm-o-4-5.md)\n- [Kimi K3 vs SmolLM3-3B](https://www.anchorterminal.com/compare/kimi-k3-vs-smollm3-3b.md)\n- [Kolibri-1 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/kolibri-1-vs-minicpm-o-4-5.md)\n- [Kolibri-1 vs SmolLM3-3B](https://www.anchorterminal.com/compare/kolibri-1-vs-smollm3-3b.md)\n- [Laguna M.1 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm-o-4-5.md)\n- [Laguna M.1 vs SmolLM3-3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-smollm3-3b.md)\n- [Laguna S 2.1 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minicpm-o-4-5.md)\n- [Laguna S 2.1 vs SmolLM3-3B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-smollm3-3b.md)\n- [Laguna XS 2.1 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minicpm-o-4-5.md)\n- [Laguna XS 2.1 vs SmolLM3-3B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-smollm3-3b.md)\n- [LFM2.5-2.6B vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-minicpm-o-4-5.md)\n- [LFM2.5-2.6B vs SmolLM3-3B](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-smollm3-3b.md)\n- [Ling-3.0-tiny vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-minicpm-o-4-5.md)\n- [Ling-3.0-tiny vs SmolLM3-3B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-smollm3-3b.md)\n- [MiMo-V2.6 Distill Qwen 9B vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-minicpm-o-4-5.md)\n- [MiMo-V2.6 Distill Qwen 9B vs SmolLM3-3B](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-smollm3-3b.md)\n- [MiniCPM-o 4.5 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-minicpm5-2b.md)\n- [MiniCPM-o 4.5 vs MiniMax-M2.5](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-minimax-m2-5.md)\n- [MiniCPM-o 4.5 vs MiniMax-M2.7](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-minimax-m2-7.md)\n- [MiniCPM-o 4.5 vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-muse-glimmer-30b.md)\n- [MiniCPM-o 4.5 vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [MiniCPM-o 4.5 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-nemotron-3-nano-30b-a3b.md)\n- [MiniCPM-o 4.5 vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-nemotron-3-nano-4b.md)\n- [MiniCPM-o 4.5 vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [MiniCPM-o 4.5 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-nemotron-3-super-120b-a12b.md)\n- [MiniCPM-o 4.5 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-nemotron-3-ultra-550b-a55b.md)\n- [MiniCPM-o 4.5 vs occamy-1.0](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-occamy-1-0.md)\n- [MiniCPM-o 4.5 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-olmo-3-7b-think.md)\n- [MiniCPM-o 4.5 vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-ornith-1-5-35b-a3b.md)\n- [MiniCPM-o 4.5 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-ornith-1-5-397b.md)\n- [MiniCPM-o 4.5 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-ornith-1-5-9b.md)\n- [MiniCPM-o 4.5 vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-30b-a3b-instruct-2507.md)\n- [MiniCPM-o 4.5 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-4b-instruct-2507.md)\n- [MiniCPM-o 4.5 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-5-0-8b.md)\n- [MiniCPM-o 4.5 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-5-122b-a10b.md)\n- [MiniCPM-o 4.5 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-5-2b.md)\n- [MiniCPM-o 4.5 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-5-397b-a17b.md)\n- [MiniCPM-o 4.5 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-5-4b.md)\n- [MiniCPM-o 4.5 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-5-9b.md)\n- [MiniCPM-o 4.5 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-6-27b.md)\n- [MiniCPM-o 4.5 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-6-35b-a3b.md)\n- [MiniCPM-o 4.5 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-8-27b.md)\n- [MiniCPM-o 4.5 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-8-flash-next.md)\n- [MiniCPM-o 4.5 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-coder-30b-a3b-instruct.md)\n- [MiniCPM-o 4.5 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-coder-next.md)\n- [MiniCPM-o 4.5 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-omni-30b-a3b-instruct.md)\n- [MiniCPM-o 4.5 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-vl-2b-instruct.md)\n- [MiniCPM-o 4.5 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-vl-30b-a3b-instruct.md)\n- [MiniCPM-o 4.5 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-vl-32b-instruct.md)\n- [MiniCPM-o 4.5 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-vl-4b-instruct.md)\n- [MiniCPM-o 4.5 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-vl-8b-instruct.md)\n- [MiniCPM-o 4.5 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwopus3-8-27b-flash-v2.md)\n- [MiniCPM-o 4.5 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-spark-x2-6-4b.md)\n- [MiniCPM-o 4.5 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-swift-1-5-qwen3-8-27b.md)\n- [MiniCPM-o 4.5 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-swift-1-5-qwen3-8-flash-next.md)\n- [MiniCPM-o 4.5 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-thinkingcap-qwen3-8-27b.md)\n- [MiniCPM5-2B vs SmolLM3-3B](https://www.anchorterminal.com/compare/minicpm5-2b-vs-smollm3-3b.md)\n- [MiniMax-M2.5 vs SmolLM3-3B](https://www.anchorterminal.com/compare/minimax-m2-5-vs-smollm3-3b.md)\n- [MiniMax-M2.7 vs SmolLM3-3B](https://www.anchorterminal.com/compare/minimax-m2-7-vs-smollm3-3b.md)\n- [Muse Glimmer 30B vs SmolLM3-3B](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-smollm3-3b.md)\n- [Nemotron 3.5 Lightning 30B A3B vs SmolLM3-3B](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-smollm3-3b.md)\n- [Nemotron 3 Nano 30B A3B vs SmolLM3-3B](https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-smollm3-3b.md)\n- [Nemotron 3 Nano 4B vs SmolLM3-3B](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-smollm3-3b.md)\n- [Nemotron 3 Nano Omni 30B A3B Reasoning vs SmolLM3-3B](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-smollm3-3b.md)\n- [Nemotron 3 Super 120B A12B vs SmolLM3-3B](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-smollm3-3b.md)\n- [Nemotron 3 Ultra 550B A55B vs 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