{ "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": 1239, "categoryRank": 52, "methodology": "0.7", "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": "0.7", "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": 58, "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": 58 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/minicpm5-2b.json", "live": { "slug": "minicpm5-2b", "securityTxt": { "url": "https://openbmb.cn/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-30T15:38:20.960978766Z" }, "domain": { "domain": "openbmb.cn", "checkedAt": "2026-10-25T13:52:42.572890011Z" }, "pages": [ { "url": "https://huggingface.co/openbmb/MiniCPM5-2B/commits/main", "kind": "changelog", "status": 200, "checkedAt": "2026-10-30T05:42:44.052558223Z", "changedAt": "2026-10-30T05:42:44.052558223Z", "fingerprint": "1942efb1ed15" } ], "updatedAt": "2026-10-30T15:38:20.960978766Z" } }, "answer": "MiniCPM5-2B scores 60.2 (C) on agent readiness against Mistral Large 4's 54.6 (C), and leads in 2 of 5 scored categories. Mistral Large 4 leads on capability, risk and agent interface.", "b": { "slug": "mistral-large-4", "name": "Mistral Large 4", "vendor": "Mistral AI", "vendorUrl": "https://mistral.ai", "kind": "weights", "category": "open-weights", "summary": "Mistral Large 4 (\"Le Chonk\") is Mistral AI's open-weight mixture-of-experts model of about 1T parameters with 52B active, taking text and images, with three reasoning efforts and a 1M-token context, published in FP8 and NVFP4.", "url": "https://www.anchorterminal.com/tools/mistral-large-4", "markdownUrl": "https://www.anchorterminal.com/tools/mistral-large-4.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/mistral-large-4.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/mistral-large-4.json", "repo": "https://huggingface.co/mistralai/Mistral-Large-4-1T-A52B", "license": "Mistral Ecosystem Open-Weight License (modified MIT)", "transports": [], "packages": [ { "registry": "huggingface", "name": "mistralai/Mistral-Large-4-1T-A52B" }, { "registry": "huggingface", "name": "mistralai/Mistral-Large-4-1T-A52B-NVFP4" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Both repositories report gated false (checked 2026-10-30).", "pricing": "free", "pricingNotes": "Free to download. The Mistral Ecosystem Open-Weight License allows commercial use, except that a licensee or affiliate that operates a Model-as-a-Service business needs a separate commercial licence from Mistral before any commercial use; internal use and use through Mistral's own products are exempt. Mistral's API serves it as mistral-large-4 at $0.70 input, $0.07 cached input and $2.10 output per million tokens (checked 2026-10-30).", "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 2026-10-30).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-30" }, "docsUrl": "https://huggingface.co/mistralai/Mistral-Large-4-1T-A52B", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "multimodal", "frontier", "reasoning", "tool-calling", "long-context", "multilingual", "safetensors", "fp8", "nvfp4", "self-hosted" ], "lastRelease": "2026-10-29", "graded": true, "anchor": { "graded": true, "score": 54.6, "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": 1239, "categoryRank": 72, "methodology": "0.7", "run": "2026-10-01", "scores": { "capability": 32, "interface": 95, "reach": 50, "risk": 75, "upkeep": 64 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-30" }, "negative": 0, "verdict": "A frontier-sized open cousin for coding agents and defensive security, with strict JSON Schema output, parallel tool calls and three reasoning efforts. It needs a multi-GPU server, about 732 GB for the smallest 4-bit build, and vLLM and SGLang run it only from special images. The main risk is a licence that bars Model-as-a-Service businesses without a separate deal.", "bestFor": "Operators with an 8-GPU Blackwell or H200 node who want a frontier-sized open model for coding agents and defensive security, with a hosted twin on Mistral's API.", "strengths": [ "Safetensors only, loaded by Transformers' own code with a Jinja template, in Mistral's verified organisation with a hash on every file", "Tool calling documented end to end with a named parser, several calls a turn and strict JSON Schema output", "Reasoning effort budgeted per request, low, medium or high, with the reasoning returned apart from the answer", "FP8 and NVFP4 builds from Mistral, and Mistral's own API serves the same model for agents without the hardware", "First among open-weight models on Cognition's FrontierCode 2.0 leaderboard, run in Mistral's own harness" ], "weaknesses": [ "The smallest 4-bit build needs about 732 GB, so nothing fits a single workstation or a 128 GB machine", "No vLLM or SGLang release supports it yet, only Docker images tagged mistral-large-4", "A Model-as-a-Service business needs a separate commercial licence from Mistral before any commercial use", "Safety results are Mistral's own with no settings to rerun them, and no limitations, training data sources or knowledge cut-off are published", "The 1M context comes from YaRN scaling with no stated trained length, and thinking can't be turned off" ], "agentNotes": [ "Serve the NVFP4 build on Blackwell with `vllm/vllm-openai:mistral-large-4 --model mistralai/Mistral-Large-4-1T-A52B-NVFP4 --tensor-parallel-size 8 --kv-cache-dtype fp8_ds_mla --tool-call-parser mistral --reasoning-parser mistral --enable-auto-tool-choice`; released vLLM doesn't load it", "On H200 use the FP8 build with tensor parallelism of 16 or 8 by 2 pipelines, per vLLM's recipe", "Pass `reasoning_effort` low, medium or high (default high); any other value makes the template raise an error, and there is no off switch", "Read the reasoning from `message.reasoning`; `max_completion_tokens` counts reasoning tokens too", "Use temperature 1.0 and top_p 0.95 at every effort, per the card", "Ask for JSON with `response_format` type json_schema and strict true; the template passes the schema to the model", "The template rejects a tool message straight after a user message and a conversation that doesn't start with a user or system message", "Add `--speculative-config '{\"method\": \"dspark\", \"num_speculative_tokens\": 3}'` to use the embedded draft head", "If you'll offer it to others as a hosted model, read the licence first; Model-as-a-Service use needs Mistral's commercial licence" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 54.6 } ], "editorialScores": { "capability": 32, "interface": 95, "reach": 50, "risk": 75, "upkeep": 64 }, "provenanceScore": 84, "checked": { "categories": { "capability": "2026-10-30", "interface": "2026-10-30", "reach": "2026-10-30", "risk": "2026-10-30", "upkeep": "2026-10-30" }, "last": "2026-10-30", "oldest": "2026-10-30", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "# NVFP4 on 4 or 8 Blackwell GPUs, with the card's vLLM image (no vLLM release supports it yet):\ndocker run --runtime nvidia --gpus all -v ~/.cache/huggingface:/root/.cache/huggingface -p 8000:8000 --ipc=host \\\n vllm/vllm-openai:mistral-large-4 --model mistralai/Mistral-Large-4-1T-A52B-NVFP4 \\\n --tensor-parallel-size 8 --kv-cache-dtype fp8_ds_mla --tool-call-parser mistral \\\n --reasoning-parser mistral --enable-auto-tool-choice --gpu-memory-utilization 0.85", "http": "curl http://localhost:8000/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\": \"mistralai/Mistral-Large-4-1T-A52B-NVFP4\", \"reasoning_effort\": \"medium\", \"temperature\": 1.0, \"top_p\": 0.95,\n \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/mistral-large-4" }, "sameCompany": [ "mistral-embeddings", "mistral-moderation", "mistral-voxtral-transcribe", "voxtral-mini-4b-realtime-2602", "mistral-ocr", "mistral-vibe-cli" ], "sameModel": [ "mistral-api" ], "weights": { "trainedBy": "Mistral AI", "params": "~1T total (1.05T per Mistral's docs), 52B active", "context": 1048576, "goodFor": "Frontier-sized multimodal model for coding agents, defensive security work and long documents, with tool calling, strict JSON Schema output and three reasoning efforts, for operators with a multi-GPU server.", "runtimes": [ "llama.cpp", "Transformers" ], "builds": [ { "name": "Mistral-Large-4-1T-A52B-NVFP4", "url": "https://huggingface.co/mistralai/Mistral-Large-4-1T-A52B-NVFP4", "who": "publisher", "precision": "nvfp4", "sizeGB": 610, "memoryGB": 1024, "format": "safetensors", "runsOn": [ "vLLM (mistral-large-4 image)", "SGLang (mistral-large-4 image)" ], "note": "NVFP4 experts with FP8 linears, for Blackwell GPUs; Mistral-format params.json only, no config.json, so not for Transformers" }, { "name": "ggml-org Mistral-Large-4-1T-A52B-GGUF Q4_K_M", "url": "https://huggingface.co/ggml-org/Mistral-Large-4-1T-A52B-GGUF", "who": "ggml-org (llama.cpp)", "precision": "q4_k_m", "sizeGB": 634.8, "memoryGB": 1024, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "llama.cpp's own organisation, linked from Mistral's card. Also BF16, Q8_0, Q2_K (380.7 GB) and IQ2_XXS (297.7 GB), plus an NVFP4 GGUF of 619.4 GB in a second repository; the 2-bit files are below the 4-bit line and aren't counted. Vision projector 3.4 GB extra" }, { "name": "Mistral-Large-4-1T-A52B", "url": "https://huggingface.co/mistralai/Mistral-Large-4-1T-A52B", "who": "publisher", "precision": "fp8", "sizeGB": 1060.6, "memoryGB": 2048, "format": "safetensors", "runsOn": [ "Transformers", "vLLM (mistral-large-4 image)", "SGLang (mistral-large-4 image)" ], "note": "Block-scaled FP8 (128 by 128), the release precision; vision tower, projector, output head and some attention projections kept in BF16. Includes the DSpark draft head" } ], "run": "docker run --runtime nvidia --gpus all -v ~/.cache/huggingface:/root/.cache/huggingface -p 8000:8000 --ipc=host vllm/vllm-openai:mistral-large-4 --model mistralai/Mistral-Large-4-1T-A52B-NVFP4 --tensor-parallel-size 8 --kv-cache-dtype fp8_ds_mla --tool-call-parser mistral --reasoning-parser mistral --enable-auto-tool-choice --gpu-memory-utilization 0.85", "runBuild": "Mistral-Large-4-1T-A52B-NVFP4", "checked": "2026-10-30", "minMemoryGB": 1024 }, "family": { "lab": "Mistral AI", "family": "Mistral Large 4", "url": "https://www.anchorterminal.com/open-weights/#mistral", "olderCount": 49 }, "area": "models", "provenance": { "legalEntity": "Mistral AI (RCS Paris 952 418 325)", "domain": "mistral.ai", "domainRegistered": "2019-05-15", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/mistralai/Mistral-Large-4-1T-A52B/commits/main", "securityTxt": "valid", "checked": "2026-10-30", "notes": [ "The files sit in Mistral's verified mistralai organisation, which the card, Mistral's announcement and its docs page for the model link to. Legal entity and domain registration are carried from the mistral-api listing.", "Nothing is hosted in this listing, so the licence stands in for terms of service and no privacy policy is scored. The hosted model is mistral-api.", "The changelog is the repositories' commit history, an initial release on 29 October 2026 and two card edits the same day, plus a merged evaluation figure on the NVFP4 card.", "mistral.ai/.well-known/security.txt answered on 30 October 2026 with a security contact, an expiry of 5 May 2027 and a HackerOne submission policy." ], "score": 84 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/mistral-large-4.json" }, "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "OpenBMB", "b": "Mistral AI", "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": "Mistral Ecosystem Open-Weight License (modified MIT)", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-09-29", "b": "2026-10-29", "name": "Last release" }, { "a": "no document linked", "b": "no document linked", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "", "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": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "MiniCPM5-2B scores 60.2 (C) on agent readiness against Mistral Large 4's 54.6 (C), and leads in 2 of 5 scored categories. Mistral Large 4 leads on capability, risk and agent interface.", "question": "Which is better for AI agents, MiniCPM5-2B or Mistral Large 4?" } ], "goodFor": [ { "aheadOn": [ "Reach, 90 against 50", "Documentation and upkeep, 97 against 64" ], "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": [ "Capability, 32 against 27", "Risk, 75 against 55", "Agent interface, 95 against 75" ], "also": null, "goodFor": "Operators with an 8-GPU Blackwell or H200 node who want a frontier-sized open model for coding agents and defensive security, with a hosted twin on Mistral's API.", "slug": "mistral-large-4", "watchFor": "The smallest 4-bit build needs about 732 GB, so nothing fits a single workstation or a 128 GB machine" } ], "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm5-2b.json", "title": "Agents-A1-4B vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-mistral-large-4.json", "title": "Agents-A1-4B vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm5-2b.json", "title": "Apertus v1.5 8B vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-mistral-large-4.json", "title": "Apertus v1.5 8B vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm5-2b.json", "title": "Apodex-1.1-mini vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-mistral-large-4.json", "title": "Apodex-1.1-mini vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm5-2b.json", "title": "BigBang-v1 vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-mistral-large-4.json", "title": "BigBang-v1 vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-minicpm5-2b.json", "title": "Carbon-X vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-mistral-large-4.json", "title": "Carbon-X vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm5-2b.json", "title": "Cosmos-Reason2-2B vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-mistral-large-4.json", "title": "Cosmos-Reason2-2B vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm5-2b.json", "title": "Darwin-36B-Opus vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-mistral-large-4.json", "title": "Darwin-36B-Opus vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm5-2b.json", "title": "DeepSeek-V3.2 vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-mistral-large-4.json", "title": "DeepSeek-V3.2 vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minicpm5-2b.json", "title": "DeepSeek V4.1 Flash vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-mistral-large-4.json", "title": "DeepSeek V4.1 Flash vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minicpm5-2b.json", "title": "DeepSeek-V4-Flash-0731 vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-mistral-large-4.json", "title": "DeepSeek-V4-Flash-0731 vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minicpm5-2b.json", "title": "DiffusionGemma 26B A4B IT vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-mistral-large-4.json", "title": "DiffusionGemma 26B A4B IT vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minicpm5-2b.json", "title": "Gemma 4 12B IT vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-mistral-large-4.json", "title": "Gemma 4 12B IT vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minicpm5-2b.json", "title": "Gemma 4 26B A4B IT vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-mistral-large-4.json", "title": "Gemma 4 26B A4B IT vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minicpm5-2b.json", "title": "Gemma 4 31B IT vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-mistral-large-4.json", "title": "Gemma 4 31B IT vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm5-2b.json", "title": "Gemma 4 E2B IT vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-mistral-large-4.json", "title": "Gemma 4 E2B IT vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minicpm5-2b.json", "title": "Gemma 4 E4B IT vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-mistral-large-4.json", "title": "Gemma 4 E4B IT vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-minicpm5-2b.json", "title": "GLM-4.5-Air vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-mistral-large-4.json", "title": "GLM-4.5-Air vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minicpm5-2b.json", "title": "GLM-4.7-Flash vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-mistral-large-4.json", "title": "GLM-4.7-Flash vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm5-2b.json", "title": "GLM-5.3-Flash vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-mistral-large-4.json", "title": "GLM-5.3-Flash vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm5-2b.json", "title": "GLM-5.3 vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-mistral-large-4.json", "title": "GLM-5.3 vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm5-2b.json", "title": "gpt-oss-120b vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-mistral-large-4.json", "title": "gpt-oss-120b vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minicpm5-2b.json", "title": "gpt-oss-20b vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-mistral-large-4.json", "title": "gpt-oss-20b vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minicpm5-2b.json", "title": "Granite 4.2 3B vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-mistral-large-4.json", "title": "Granite 4.2 3B vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-minicpm5-2b.json", "title": "Hy3 vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/hy3-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-mistral-large-4.json", "title": "Hy3 vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/hy3-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm5-2b.json", "title": "Inkling-Small vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-mistral-large-4.json", "title": "Inkling-Small vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-minicpm5-2b.json", "title": "Inkling vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/inkling-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-mistral-large-4.json", "title": "Inkling vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/inkling-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-minicpm5-2b.json", "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-mistral-large-4.json", "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-minicpm5-2b.json", "title": "Kimi K3 vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-mistral-large-4.json", "title": "Kimi K3 vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-minicpm5-2b.json", "title": "Kolibri-1 vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-mistral-large-4.json", "title": "Kolibri-1 vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/kronos-vs-minicpm5-2b.json", "title": "Kronos vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/kronos-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/kronos-vs-mistral-large-4.json", "title": "Kronos vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/kronos-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm5-2b.json", "title": "Laguna M.1 vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-mistral-large-4.json", "title": "Laguna M.1 vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minicpm5-2b.json", "title": "Laguna S 2.1 vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-mistral-large-4.json", "title": "Laguna S 2.1 vs Mistral Large 4", "url": 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{ "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-8-flash-next.json", "title": "MiniCPM5-2B vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-coder-30b-a3b-instruct.json", "title": "MiniCPM5-2B vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-coder-next.json", "title": "MiniCPM5-2B vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-omni-30b-a3b-instruct.json", "title": "MiniCPM5-2B vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-omni-30b-a3b-instruct" }, { "json": 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"https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-5-122b-a10b.json", "title": "Mistral Large 4 vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-5-2b.json", "title": "Mistral Large 4 vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-5-397b-a17b.json", "title": "Mistral Large 4 vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-5-4b.json", "title": "Mistral Large 4 vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-5-9b.json", "title": "Mistral Large 4 vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-6-27b.json", "title": "Mistral Large 4 vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-6-35b-a3b.json", "title": "Mistral Large 4 vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-8-27b.json", "title": "Mistral Large 4 vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-8-flash-next.json", "title": "Mistral Large 4 vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Mistral Large 4 vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-coder-next.json", "title": "Mistral Large 4 vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Mistral Large 4 vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-vl-2b-instruct.json", "title": "Mistral Large 4 vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-vl-30b-a3b-instruct.json", "title": "Mistral Large 4 vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-vl-32b-instruct.json", "title": "Mistral Large 4 vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-vl-4b-instruct.json", "title": "Mistral Large 4 vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-vl-8b-instruct.json", "title": "Mistral Large 4 vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwopus3-8-27b-flash-v2.json", "title": "Mistral Large 4 vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-recursive-flint.json", "title": "Mistral Large 4 vs Recursive Flint", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-recursive-flint" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-smollm3-3b.json", "title": "Mistral Large 4 vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-spark-x2-6-4b.json", "title": "Mistral Large 4 vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-swift-1-5-qwen3-8-27b.json", "title": "Mistral Large 4 vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Mistral Large 4 vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-thinkingcap-qwen3-8-27b.json", "title": "Mistral Large 4 vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-unlimited-ocr-2.json", "title": "Mistral Large 4 vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-unlimited-ocr-2" } ], "scores": [ { "by": 5, "edge": "mistral-large-4", "key": "capability", "minicpm5-2b": 27, "mistral-large-4": 32, "name": "Capability", "weight": 35 }, { "by": 40, "edge": "minicpm5-2b", "key": "reach", "minicpm5-2b": 90, "mistral-large-4": 50, "name": "Reach", "weight": 25 }, { "by": 20, "edge": "mistral-large-4", "key": "risk", "minicpm5-2b": 55, "mistral-large-4": 75, "name": "Risk", "weight": 20 }, { "by": 20, "edge": "mistral-large-4", "key": "interface", "minicpm5-2b": 75, "mistral-large-4": 95, "name": "Agent interface", "weight": 10 }, { "by": 33, "edge": "minicpm5-2b", "key": "upkeep", "minicpm5-2b": 97, "mistral-large-4": 64, "name": "Documentation and upkeep", "weight": 10 } ], "summary": "MiniCPM5-2B scores 60.2 (C) on agent readiness against Mistral Large 4's 54.6 (C), and leads in 2 of 5 scored categories. Mistral Large 4 leads on capability, risk and agent interface. 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.", "mistral-large-4": "A frontier-sized open cousin for coding agents and defensive security, with strict JSON Schema output, parallel tool calls and three reasoning efforts. It needs a multi-GPU server, about 732 GB for the smallest 4-bit build, and vLLM and SGLang run it only from special images. The main risk is a licence that bars Model-as-a-Service businesses without a separate deal." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-mistral-large-4", "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-mistral-large-4.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-mistral-large-4.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-mistral-large-4.min.md" }, "markdown": "MiniCPM5-2B scores 60.2 (C) on agent readiness against Mistral Large 4's 54.6 (C), and leads in 2 of 5 scored categories. Mistral Large 4 leads on capability, risk and agent interface. Both do open-weight models you run yourself.\n\n- MiniCPM5-2B: grade C, 60.2/100, rank #62 of 117 open-weight models. Markdown https://www.anchorterminal.com/tools/minicpm5-2b.md · JSON https://www.anchorterminal.com/api/v1/tools/minicpm5-2b.json\n- Mistral Large 4: grade C, 54.6/100, rank #92 of 117 open-weight models. Markdown https://www.anchorterminal.com/tools/mistral-large-4.md · JSON https://www.anchorterminal.com/api/v1/tools/mistral-large-4.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 3588 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 50\n- Documentation and upkeep, 97 against 64\n\nWatch for: OpenBMB documents only a Think mode for the 2B, so every answer starts with reasoning\n\n### Mistral Large 4 (C)\n\nGood for: Operators with an 8-GPU Blackwell or H200 node who want a frontier-sized open model for coding agents and defensive security, with a hosted twin on Mistral's API.\n\nAhead on:\n- Capability, 32 against 27\n- Risk, 75 against 55\n- Agent interface, 95 against 75\n\nWatch for: The smallest 4-bit build needs about 732 GB, so nothing fits a single workstation or a 128 GB machine\n\n\n## Score by category\n\n| Category | Weight | MiniCPM5-2B | Mistral Large 4 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35% (35 this run) | 27 | 32 | Mistral Large 4 +5 |\n| Reach | 25% (25 this run) | 90 | 50 | MiniCPM5-2B +40 |\n| Risk | 20% (20 this run) | 55 | 75 | Mistral Large 4 +20 |\n| Agent interface | 10% (10 this run) | 75 | 95 | Mistral Large 4 +20 |\n| Documentation and upkeep | 10% (10 this run) | 97 | 64 | MiniCPM5-2B +33 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **60.2 · C** | **54.6 · C** | |\n\n## Facts side by side\n\n| Fact | MiniCPM5-2B | Mistral Large 4 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | OpenBMB | Mistral AI |\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 | Mistral Ecosystem Open-Weight License (modified MIT) |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-09-29 | 2026-10-29 |\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) | none |\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**Mistral Large 4.** A frontier-sized open cousin for coding agents and defensive security, with strict JSON Schema output, parallel tool calls and three reasoning efforts. It needs a multi-GPU server, about 732 GB for the smallest 4-bit build, and vLLM and SGLang run it only from special images. The main risk is a licence that bars Model-as-a-Service businesses without a separate deal.\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### Mistral Large 4\n\n1. Serve the NVFP4 build on Blackwell with `vllm/vllm-openai:mistral-large-4 --model mistralai/Mistral-Large-4-1T-A52B-NVFP4 --tensor-parallel-size 8 --kv-cache-dtype fp8_ds_mla --tool-call-parser mistral --reasoning-parser mistral --enable-auto-tool-choice`; released vLLM doesn't load it\n2. On H200 use the FP8 build with tensor parallelism of 16 or 8 by 2 pipelines, per vLLM's recipe\n3. Pass `reasoning_effort` low, medium or high (default high); any other value makes the template raise an error, and there is no off switch\n4. Read the reasoning from `message.reasoning`; `max_completion_tokens` counts reasoning tokens too\n5. Use temperature 1.0 and top_p 0.95 at every effort, per the card\n6. Ask for JSON with `response_format` type json_schema and strict true; the template passes the schema to the model\n7. The template rejects a tool message straight after a user message and a conversation that doesn't start with a user or system message\n8. Add `--speculative-config '{\"method\": \"dspark\", \"num_speculative_tokens\": 3}'` to use the embedded draft head\n9. If you'll offer it to others as a hosted model, read the licence first; Model-as-a-Service use needs Mistral's commercial licence\n\n## Questions\n\n### Which is better for AI agents, MiniCPM5-2B or Mistral Large 4?\n\nMiniCPM5-2B scores 60.2 (C) on agent readiness against Mistral Large 4's 54.6 (C), and leads in 2 of 5 scored categories. Mistral Large 4 leads on capability, risk and agent interface.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/minicpm5-2b-vs-mistral-large-4.json, and with the fewest tokens: https://www.anchorterminal.com/compare/minicpm5-2b-vs-mistral-large-4.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"minicpm5-2b\", \"b\": \"mistral-large-4\"}`. From a terminal: `anchor compare minicpm5-2b mistral-large-4`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/minicpm5-2b.json and https://www.anchorterminal.com/api/v1/tools/mistral-large-4.json\n\n## Other comparisons with MiniCPM5-2B or Mistral Large 4\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 Mistral Large 4](https://www.anchorterminal.com/compare/agents-a1-4b-vs-mistral-large-4.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 Mistral Large 4](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-mistral-large-4.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 Mistral Large 4](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-mistral-large-4.md)\n- [BigBang-v1 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm5-2b.md)\n- [BigBang-v1 vs Mistral Large 4](https://www.anchorterminal.com/compare/bigbang-v1-vs-mistral-large-4.md)\n- [Carbon-X vs MiniCPM5-2B](https://www.anchorterminal.com/compare/carbon-x-vs-minicpm5-2b.md)\n- [Carbon-X vs Mistral Large 4](https://www.anchorterminal.com/compare/carbon-x-vs-mistral-large-4.md)\n- [Cosmos-Reason2-2B vs MiniCPM5-2B](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm5-2b.md)\n- [Cosmos-Reason2-2B vs Mistral Large 4](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-mistral-large-4.md)\n- [Darwin-36B-Opus vs MiniCPM5-2B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm5-2b.md)\n- [Darwin-36B-Opus vs Mistral Large 4](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-mistral-large-4.md)\n- [DeepSeek-V3.2 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm5-2b.md)\n- [DeepSeek-V3.2 vs Mistral Large 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vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/mistral-large-4-vs-thinkingcap-qwen3-8-27b.md)\n- [Mistral Large 4 vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/mistral-large-4-vs-unlimited-ocr-2.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-31", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "MiniCPM5-2B vs Mistral Large 4", "url": "" } ], "description": "MiniCPM5-2B scores 60.2 (C) to Mistral Large 4's 54.6 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "MiniCPM5-2B C 60.2", "Mistral Large 4 C 54.6", "scores" ], "h1": "MiniCPM5-2B vs Mistral Large 4", "image": "https://www.anchorterminal.com/assets/og/compare-minicpm5-2b-vs-mistral-large-4.png", "path": "/compare/minicpm5-2b-vs-mistral-large-4", "published": "2026-10-01", "section": "tools", "title": "MiniCPM5-2B vs Mistral Large 4 for AI agents (2026) | Anchor Terminal", "toc": null, "updated": "2026-10-30", "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-mistral-large-4" }, "tokens": { "markdown": 6700, "slim": 480 }, "version": 1 }