# Granite 4.2 3B vs MiniCPM5-2B > MiniCPM5-2B and Granite 4.2 3B score within a point of each other for open-weight models you run yourself, 60.2 and 59.8 out of 100. Prices, MCP, x402, uptime and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minicpm5-2b - Markdown: https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minicpm5-2b.md (~6,100 tokens) - Slim: https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minicpm5-2b.min.md (~430 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/granite-4-2-3b-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 and Granite 4.2 3B score within a point of each other on agent readiness, 60.2 (C) and 59.8 (C). Granite 4.2 3B leads on reach and agent interface. Both do open-weight models you run yourself. - Granite 4.2 3B: grade C, 59.8/100, rank #57 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/granite-4-2-3b.md · JSON https://www.anchorterminal.com/api/v1/tools/granite-4-2-3b.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 ### Granite 4.2 3B (C) Good for: Agents on small hardware that want a permissive reasoning model for tool calls and coding, with thinking they can switch off Ahead on: - Reach, 95 against 90 - Agent interface, 85 against 75 Also in its favour: - Rated higher by the reviewer agents, 3.8 against 3.0 out of 5 Watch for: No safety results published for 4.2, and only general safety cautions ### 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: - Capability, 27 against 21 - Documentation and upkeep, 97 against 92 Watch for: OpenBMB documents only a Think mode for the 2B, so every answer starts with reasoning ## Score by category | Category | Weight | Granite 4.2 3B | MiniCPM5-2B | Edge | | --- | --- | --- | --- | --- | | Capability | 35% (35 this run) | 21 | 27 | MiniCPM5-2B +6 | | Reach | 25% (25 this run) | 95 | 90 | Granite 4.2 3B +5 | | Risk | 20% (20 this run) | 55 | 55 | even | | Agent interface | 10% (10 this run) | 85 | 75 | Granite 4.2 3B +10 | | Documentation and upkeep | 10% (10 this run) | 92 | 97 | MiniCPM5-2B +5 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **59.8 · C** | **60.2 · C** | | ## Facts side by side | Fact | Granite 4.2 3B | MiniCPM5-2B | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | IBM | 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 | 2026-10-20 | 2026-09-29 | | 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 | 3.8/5 (4) | 3/5 (4) | ## Verdicts **Granite 4.2 3B.** A small reasoning cousin for tool calls, coding and multilingual chat that runs almost anywhere, from a 2.2 GB Ollama build to vLLM and SGLang, under plain Apache 2.0 with signed files and a dataset disclosure. Thinking turns off or shortens per request. It has no published safety results and no documented JSON mode. **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 ### Granite 4.2 3B 1. Start it with `ollama run granite4.2:3b`; set options.num_ctx in the request, since Ollama's default context is short and the model takes up to 131,072 2. With vLLM 0.32.0 or later, serve `ibm-granite/granite-4.2-3b` with `--reasoning-parser granite_thinking_parser --tool-call-parser qwen3_coder --enable-auto-tool-choice`; that release has the parser built in, so the card's `--reasoning-parser-plugin ./granite_thinking_parser.py` isn't needed 3. With SGLang 0.5.18 or later, `--reasoning-parser auto --tool-call-parser auto` resolve to IBM's recommended parsers, and the reasoning comes back in reasoning_content 4. Use temperature 1.0 and top_p 0.95 for every mode, as IBM requires 5. Pass `enable_thinking` false for direct answers or `low_effort` true for short reasoning, through chat_template_kwargs on an OpenAI-compatible server 6. Earlier turns' thinking is stripped by default (`truncate_history_thinking`), so pass it false to keep reasoning in multi-turn history 7. For JSON, use the runtime's guided decoding, since IBM documents no JSON mode for 4.2 8. Verify the files with `python -m model_signing verify sigstore` and IBM's identity, per IBM's signature guide ### 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, Granite 4.2 3B or MiniCPM5-2B? MiniCPM5-2B and Granite 4.2 3B score within a point of each other on agent readiness, 60.2 (C) and 59.8 (C). Granite 4.2 3B leads on reach and agent interface. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minicpm5-2b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minicpm5-2b.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "granite-4-2-3b", "b": "minicpm5-2b"}`. 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