# MiniCPM5-2B vs Olmo 3 7B Think > MiniCPM5-2B scores 60.2 (C) to Olmo 3 7B Think's 52.3 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/minicpm5-2b-vs-olmo-3-7b-think - Markdown: https://www.anchorterminal.com/compare/minicpm5-2b-vs-olmo-3-7b-think.md (~6,050 tokens) - Slim: https://www.anchorterminal.com/compare/minicpm5-2b-vs-olmo-3-7b-think.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/minicpm5-2b-vs-olmo-3-7b-think.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 Olmo 3 7B Think's 52.3 (D), and leads in 3 of 5 scored categories. Olmo 3 7B Think leads on risk. Both do open-weight models you run yourself. - 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 - Olmo 3 7B Think: grade D, 52.3/100, rank #86 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/olmo-3-7b-think.md · JSON https://www.anchorterminal.com/api/v1/tools/olmo-3-7b-think.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 ### 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 75 - Agent interface, 75 against 35 - Documentation and upkeep, 97 against 52 Watch for: OpenBMB documents only a Think mode for the 2B, so every answer starts with reasoning ### Olmo 3 7B Think (D) Good for: Researchers and agents that want a small fully open reasoning model for maths and code, with its training data on hand Ahead on: - Risk, 75 against 55 Watch for: Not trained for tool calling, and the tool format lives only in the template ## Score by category | Category | Weight | MiniCPM5-2B | Olmo 3 7B Think | Edge | | --- | --- | --- | --- | --- | | Capability | 35% (35 this run) | 27 | 28 | Olmo 3 7B Think +1 | | Reach | 25% (25 this run) | 90 | 75 | MiniCPM5-2B +15 | | Risk | 20% (20 this run) | 55 | 75 | Olmo 3 7B Think +20 | | Agent interface | 10% (10 this run) | 75 | 35 | MiniCPM5-2B +40 | | Documentation and upkeep | 10% (10 this run) | 97 | 52 | MiniCPM5-2B +45 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **60.2 · C** | **52.3 · D** | | ## Facts side by side | Fact | MiniCPM5-2B | Olmo 3 7B Think | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | OpenBMB | Ai2 (Allen Institute for AI) | | 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, with Ai2's Responsible Use Guidelines named on the card | | Read-only variant documented | no | no | | llms.txt | no | no | | Last release | 2026-09-29 | 2026-06-25 | | 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 | 3/5 (4) | 2.8/5 (4) | ## 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. **Olmo 3 7B Think.** A fully open 7B reasoning cousin for maths, code and step-by-step answers, with every dataset and checkpoint published and its safety results rerunnable. Ollama's 4-bit build needs about 5.4 GB. It always thinks, wasn't trained for tool calls, has 65K of context, and Ai2 hasn't answered its discussions. ## Before you call either ### 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 ### Olmo 3 7B Think 1. Quickest start is `ollama run olmo-3:7b-think`, about 4.5 GB 2. With vLLM, `vllm serve allenai/Olmo-3-7B-Think --max-model-len 65536`; vLLM runs it through its Transformers backend 3. Sample at temperature 0.6 and top_p 0.95 with up to 32,768 output tokens, as the card recommends, since thinking traces are long 4. Every reply starts with a think block; strip it yourself or use a reasoning parser that reads think tags 5. Pass your own system prompt; the template's default says the cut-off is November 2024 and that no functions are available 6. For tool calls use Olmo 3 7B Instruct instead, which Ai2 trained for function calling 7. A discussion reports endless reasoning loops when served with vLLM, unanswered, so cap max_tokens 8. Check the use against Ai2's Responsible Use Guidelines, which bar automated social-media posting and undisclosed automated content outside research ## Questions ### Which is better for AI agents, MiniCPM5-2B or Olmo 3 7B Think? MiniCPM5-2B scores 60.2 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 3 of 5 scored categories. Olmo 3 7B Think leads on risk. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/minicpm5-2b-vs-olmo-3-7b-think.json, and with the fewest tokens: https://www.anchorterminal.com/compare/minicpm5-2b-vs-olmo-3-7b-think.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "minicpm5-2b", "b": "olmo-3-7b-think"}`. 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