# MiniCPM5-2B vs Qwopus3.8-27B-Flash-V2 > Qwopus3.8-27B-Flash-V2 and MiniCPM5-2B score within a point of each other for open-weight models you run yourself, 61 and 60.2 out of 100. Prices, MCP, x402, uptime and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwopus3-8-27b-flash-v2 - Markdown: https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwopus3-8-27b-flash-v2.md (~6,400 tokens) - Slim: https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwopus3-8-27b-flash-v2.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwopus3-8-27b-flash-v2.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 Qwopus3.8-27B-Flash-V2 and MiniCPM5-2B score within a point of each other on agent readiness, 61 (C) and 60.2 (C). MiniCPM5-2B leads on reach, risk, agent interface 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 - Qwopus3.8-27B-Flash-V2: grade C, 61/100, rank #46 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwopus3-8-27b-flash-v2.md · JSON https://www.anchorterminal.com/api/v1/tools/qwopus3-8-27b-flash-v2.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 85 - Risk, 55 against 50 - Agent interface, 75 against 60 - Documentation and upkeep, 97 against 56 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 ### Qwopus3.8-27B-Flash-V2 (C) Good for: Hobbyist and research agents that want a faster-finishing Qwen3.8-27B for local coding loops on a 24 GB GPU. Watch for: Published from a personal account, with no organisation, security contact or safety evaluation ## Score by category | Category | Weight | MiniCPM5-2B | Qwopus3.8-27B-Flash-V2 | Edge | | --- | --- | --- | --- | --- | | Capability | 35%, pending | pending | pending | not scored in this run | | Reach | 25% (25 this run) | 90 | 85 | MiniCPM5-2B +5 | | Risk | 20% (20 this run) | 55 | 50 | MiniCPM5-2B +5 | | Agent interface | 10% (10 this run) | 75 | 60 | MiniCPM5-2B +15 | | Documentation and upkeep | 10% (10 this run) | 97 | 56 | MiniCPM5-2B +41 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **60.2 · C** | **61 · C** | | ## Facts side by side | Fact | MiniCPM5-2B | Qwopus3.8-27B-Flash-V2 | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | OpenBMB | Jackrong | | 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 (metadata only, no LICENSE file); built on Qwen3.8-27B under Apache 2.0 | | Read-only variant documented | no | no | | llms.txt | no | no | | Last release | 2026-09-29 | 2026-09-21 | | 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) | 2.5/5 (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. **Qwopus3.8-27B-Flash-V2.** A Qwen3.8-27B cousin tuned to think less per turn in long agent loops, with an MTP head for speculative decoding in llama.cpp. It fits 24 GB with Jackrong's 4-bit GGUF. The risks are one person's experimental release with no safety work, training traces taken from Claude and GPT, and a tool format that differs from Qwen's. ## 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 ### Qwopus3.8-27B-Flash-V2 1. Quickest start is `llama-server -hf Jackrong/Qwopus3.8-27B-Flash-V2-GGUF:Q4_K_M --jinja`, about 17 GB, and add mmproj-F32.gguf for images 2. The card's tests used Q5_K_M with the bundled MTP head and `--spec-type draft-mtp` in llama.cpp 3. The template asks for tool calls as JSON inside tool_call tags, so use a Hermes-style parser (vLLM's hermes), not Qwen3.8's qwen3_coder 4. For coding the card recommends enable_thinking true, reasoning_effort xhigh and temperature 0.3, which you must pass yourself, since generation_config.json says 1.0 5. reasoning_effort takes xhigh (default), medium or low, and any other value makes the template raise an error 6. Earlier reasoning stays in the context unless preserve_thinking is false 7. Cap max_tokens, since a report says it loops more than V1 ## Questions ### Which is better for AI agents, MiniCPM5-2B or Qwopus3.8-27B-Flash-V2? Qwopus3.8-27B-Flash-V2 and MiniCPM5-2B score within a point of each other on agent readiness, 61 (C) and 60.2 (C). MiniCPM5-2B leads on reach, risk, agent interface and documentation and upkeep. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwopus3-8-27b-flash-v2.json, and with the fewest tokens: https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwopus3-8-27b-flash-v2.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "minicpm5-2b", "b": "qwopus3-8-27b-flash-v2"}`. 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