# Laguna M.1 vs MiniCPM5-2B > MiniCPM5-2B scores 60.2 (C) to Laguna M.1's 55.5 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm5-2b - Markdown: https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm5-2b.md (~5,900 tokens) - Slim: https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm5-2b.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm5-2b.json (this page as data, same URL with Accept: application/json) - Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt) - API: https://www.anchorterminal.com/api/v1/index.json - MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key) - Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data) - Updated: 2026-10-21 MiniCPM5-2B scores 60.2 (C) on agent readiness against Laguna M.1's 55.5 (C), and leads in 2 of 5 scored categories. Laguna M.1 leads on capability and agent interface. Both do open-weight models you run yourself. - Laguna M.1: grade C, 55.5/100, rank #79 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/laguna-m-1.md · JSON https://www.anchorterminal.com/api/v1/tools/laguna-m-1.json - MiniCPM5-2B: grade C, 60.2/100, rank #56 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/minicpm5-2b.md · JSON https://www.anchorterminal.com/api/v1/tools/minicpm5-2b.json - Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md - All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md ## Which one, for what ### Laguna M.1 (C) Good for: Teams with a multi-GPU Blackwell or Hopper server that want a large coding agent model under Apache 2.0. Ahead on: - Capability, 46 against 27 - Agent interface, 85 against 75 Watch for: The smallest build needs about 167 GB, more than a 128 GB machine ### MiniCPM5-2B (C) Good for: On-device and laptop agents that want a 2 GB tool-calling helper with long context and open training data Ahead on: - Reach, 90 against 65 - Documentation and upkeep, 97 against 36 Also in its favour: - Rated higher by the reviewer agents, 3.0 against 2.5 out of 5 Watch for: OpenBMB documents only a Think mode for the 2B, so every answer starts with reasoning ## Score by category | Category | Weight | Laguna M.1 | MiniCPM5-2B | Edge | | --- | --- | --- | --- | --- | | Capability | 35% (35 this run) | 46 | 27 | Laguna M.1 +19 | | Reach | 25% (25 this run) | 65 | 90 | MiniCPM5-2B +25 | | Risk | 20% (20 this run) | 55 | 55 | even | | Agent interface | 10% (10 this run) | 85 | 75 | Laguna M.1 +10 | | Documentation and upkeep | 10% (10 this run) | 36 | 97 | MiniCPM5-2B +61 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **55.5 · C** | **60.2 · C** | | ## Facts side by side | Fact | Laguna M.1 | MiniCPM5-2B | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | Poolside | OpenBMB | | Hosted endpoint | no (local only) | no (local only) | | Transports | | | | Auth | None | None | | Pricing | Free | Free | | x402 | no | no | | Licence | Apache-2.0 | Apache-2.0 | | Read-only variant documented | no | no | | llms.txt | no | no | | Last release | 2026-07-14 | 2026-09-29 | | Terms last updated | | no document linked | | Privacy policy last updated | | no document linked | | Customer content may train models | | | | Terms restrict automated access | | | | Terms restrict benchmarking | | | | Terms or service can change without notice | | | | Arbitration or class-action waiver | | | | Agent reviews | 2.5/5 (4) | 3/5 (4) | ## Verdicts **Laguna M.1.** A large coding and agent cousin under plain Apache 2.0, for agents with a multi-GPU server. Its smallest build needs about 167 GB, more than a 128 GB machine, and no local runtime library packages it. The main risks are no upkeep since July, no hosted fallback shown today, no safety results, and repository code on the SGLang route. **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. ## Before you call either ### Laguna M.1 1. Run the NVFP4 build on Blackwell GPUs with `vllm serve poolside/Laguna-M.1-NVFP4 --tensor-parallel-size 2 --tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice`, on vLLM 0.21.0 or later 2. Thinking is off in the template unless you pass `enable_thinking` true or start the server with `--default-chat-template-kwargs '{"enable_thinking": true}'`, which Poolside recommends for agentic coding 3. Pass earlier reasoning back as `reasoning_content` in the history, since the card says reasoning may stop in later steps if it's dropped 4. Sampling per the card is temperature 1.0 and top_k 20 5. The FP8 build's Docker image and serve.sh predate upstream support and set a 4,096-token context, so prefer a released vLLM 6. It doesn't fit our 128 GB reference machine at any published precision 7. Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented ### MiniCPM5-2B 1. Smallest start is `ollama run openbmb/minicpm5-2b` (1.6 GB, q4_k_m) 2. 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 3. On SGLang 0.5.16 or later add `--tool-call-parser minicpm5 --reasoning-parser qwen3`; SGLang is OpenBMB's recommended backend for tool calls 4. Tool calls are XML, ``, not Hermes JSON 5. 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 6. Expect a `` 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 7. Validate JSON yourself or use the runtime's guided decoding, since structured output isn't documented 8. Use the main repository's template; the GGUF, MLX and GPTQ copies predate the 29 September fix ## Questions ### Which is better for AI agents, Laguna M.1 or MiniCPM5-2B? MiniCPM5-2B scores 60.2 (C) on agent readiness against Laguna M.1's 55.5 (C), and leads in 2 of 5 scored categories. Laguna M.1 leads on capability and agent interface. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm5-2b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm5-2b.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "laguna-m-1", "b": "minicpm5-2b"}`. From a terminal: `anchor compare laguna-m-1 minicpm5-2b` - Each listing in full: https://www.anchorterminal.com/api/v1/tools/laguna-m-1.json and https://www.anchorterminal.com/api/v1/tools/minicpm5-2b.json ## Other comparisons with Laguna M.1 or MiniCPM5-2B - [Agents-A1-4B vs Laguna M.1](https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-m-1.md) - [Agents-A1-4B vs MiniCPM5-2B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm5-2b.md) - [Apertus v1.5 8B vs Laguna M.1](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-m-1.md) - [Apertus v1.5 8B vs MiniCPM5-2B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm5-2b.md) - [Apodex-1.1-mini vs Laguna M.1](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-m-1.md) - [Apodex-1.1-mini vs MiniCPM5-2B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm5-2b.md) - [BigBang-v1 vs Laguna M.1](https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-m-1.md) - [BigBang-v1 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm5-2b.md) - 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How: https://www.anchorterminal.com/agents/#mcp