# MiniCPM5-2B vs Nemotron 3 Ultra 550B A55B > Nemotron 3 Ultra 550B A55B scores 68.8 (B) to MiniCPM5-2B's 60.2 (C) 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-nemotron-3-ultra-550b-a55b - Markdown: https://www.anchorterminal.com/compare/minicpm5-2b-vs-nemotron-3-ultra-550b-a55b.md (~6,550 tokens) - Slim: https://www.anchorterminal.com/compare/minicpm5-2b-vs-nemotron-3-ultra-550b-a55b.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/minicpm5-2b-vs-nemotron-3-ultra-550b-a55b.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 Nemotron 3 Ultra 550B A55B scores 68.8 (B) on agent readiness against MiniCPM5-2B's 60.2 (C), and leads in 3 of 5 scored categories. MiniCPM5-2B leads on reach and documentation and upkeep. 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 - Nemotron 3 Ultra 550B A55B: grade B, 68.8/100, rank #9 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/nemotron-3-ultra-550b-a55b.md · JSON https://www.anchorterminal.com/api/v1/tools/nemotron-3-ultra-550b-a55b.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 55 - Documentation and upkeep, 97 against 65 Watch for: OpenBMB documents only a Think mode for the 2B, so every answer starts with reasoning ### Nemotron 3 Ultra 550B A55B (B) Good for: Agents with a multi-GPU Blackwell or Hopper node, or using a hosted endpoint, that want NVIDIA's strongest open model for long agent runs Ahead on: - Capability, 73 against 27 - Risk, 70 against 55 - Agent interface, 90 against 75 Watch for: The smallest build is 352 GB and needs at least four B200-class GPUs ## Score by category | Category | Weight | MiniCPM5-2B | Nemotron 3 Ultra 550B A55B | Edge | | --- | --- | --- | --- | --- | | Capability | 35% (35 this run) | 27 | 73 | Nemotron 3 Ultra 550B A55B +46 | | Reach | 25% (25 this run) | 90 | 55 | MiniCPM5-2B +35 | | Risk | 20% (20 this run) | 55 | 70 | Nemotron 3 Ultra 550B A55B +15 | | Agent interface | 10% (10 this run) | 75 | 90 | Nemotron 3 Ultra 550B A55B +15 | | Documentation and upkeep | 10% (10 this run) | 97 | 65 | MiniCPM5-2B +32 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **60.2 · C** | **68.8 · B** | | ## Facts side by side | Fact | MiniCPM5-2B | Nemotron 3 Ultra 550B A55B | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | OpenBMB | NVIDIA | | Hosted endpoint | no (local only) | no (local only) | | Transports | | | | Auth | None | None | | Pricing | Free | Free | | x402 | no | no | | Licence | Apache-2.0 | OpenMDW-1.1 | | Read-only variant documented | no | no | | llms.txt | no | no | | Last release | 2026-09-29 | 2026-06-04 | | Terms last updated | no document linked | no document linked | | Privacy policy last updated | no document linked | 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. **Nemotron 3 Ultra 550B A55B.** NVIDIA's frontier-scale agent cousin with trained parallel tool calls, up to a 1M-token context and training against prompt injection through tool output. It needs at least four Blackwell GPUs for the 352 GB NVFP4 build, so most agents will use NVIDIA's API or a provider. The main risks are serving commands that run repository code and no published safety results. ## 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 ### Nemotron 3 Ultra 550B A55B 1. It doesn't fit the 128 GB reference machine at any precision. Call NVIDIA's API (model nvidia/nemotron-3-ultra-550b-a55b) or a provider instead 2. With vLLM serve the NVFP4 build with `--trust-remote-code --reasoning-parser nemotron_v3 --enable-auto-tool-choice --tool-call-parser qwen3_coder` on 4 × B200 or more 3. With SGLang use `--reasoning-parser nemotron_3`, not the BF16 card's `nemotron_v3`, which SGLang doesn't register 4. On SGLang with tools, pass `chat_template_kwargs` with `enable_thinking` true and `force_nonempty_content` true, as the card says, or reasoning and calls won't both parse 5. Thinking is on by default. Pass `enable_thinking: false` for short tasks or `medium_effort: true` to cut reasoning tokens 6. Use `temperature=1.0` and `top_p=0.95`, as the generation config sets ## Questions ### Which is better for AI agents, MiniCPM5-2B or Nemotron 3 Ultra 550B A55B? Nemotron 3 Ultra 550B A55B scores 68.8 (B) on agent readiness against MiniCPM5-2B's 60.2 (C), and leads in 3 of 5 scored categories. MiniCPM5-2B leads on reach and documentation and upkeep. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/minicpm5-2b-vs-nemotron-3-ultra-550b-a55b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/minicpm5-2b-vs-nemotron-3-ultra-550b-a55b.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "minicpm5-2b", "b": "nemotron-3-ultra-550b-a55b"}`. 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