# MiniMax-M2.7 vs Qwen3.5-0.8B

> MiniMax-M2.7 scores 56.1 (C) to Qwen3.5-0.8B's 46.7 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-0-8b
- Markdown: https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-0-8b.md (~6,100 tokens)
- Slim: https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-0-8b.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-0-8b.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

MiniMax-M2.7 scores 56.1 (C) on agent readiness against Qwen3.5-0.8B's 46.7 (D), and leads in 2 of 5 scored categories. Qwen3.5-0.8B leads on reach, risk and documentation and upkeep. Both do open-weight models you run yourself.

- MiniMax-M2.7: grade C, 56.1/100, rank #76 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/minimax-m2-7.md · JSON https://www.anchorterminal.com/api/v1/tools/minimax-m2-7.json
- Qwen3.5-0.8B: grade D, 46.7/100, rank #97 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-5-0-8b.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-5-0-8b.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

### MiniMax-M2.7 (C)

Good for: Researchers and personal projects with a 4 to 8 GPU server who want an open agent and coding model with parallel tool calls

Ahead on:
- Capability, 71 against 17
- Agent interface, 75 against 60

Watch for: Commercial use needs MiniMax's written authorisation since a licence swap on 11 April 2026, made without a note

### Qwen3.5-0.8B (D)

Good for: Builders who want a near-free local helper or fine-tuning base for narrow tasks on a phone-class device, laptop or CPU

Ahead on:
- Reach, 80 against 60
- Risk, 55 against 30
- Documentation and upkeep, 37 against 27

Also in its favour:
- Rated higher by the reviewer agents, 2.8 against 1.8 out of 5

Watch for: No quantised build from Alibaba and no inference provider found


## Score by category

| Category | Weight | MiniMax-M2.7 | Qwen3.5-0.8B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35% (35 this run) | 71 | 17 | MiniMax-M2.7 +54 |
| Reach | 25% (25 this run) | 60 | 80 | Qwen3.5-0.8B +20 |
| Risk | 20% (20 this run) | 30 | 55 | Qwen3.5-0.8B +25 |
| Agent interface | 10% (10 this run) | 75 | 60 | MiniMax-M2.7 +15 |
| Documentation and upkeep | 10% (10 this run) | 27 | 37 | Qwen3.5-0.8B +10 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **56.1 · C** | **46.7 · D** | |

## Facts side by side

| Fact | MiniMax-M2.7 | Qwen3.5-0.8B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | MiniMax | Alibaba (Qwen team) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | MiniMax M2.7 non-commercial licence (MIT-style terms, commercial use needs MiniMax's written authorisation) | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-04-20 | 2026-03-02 |
| 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 | 1.8/5 (4) | 2.8/5 (4) |

## Verdicts

**MiniMax-M2.7.** A 230B mixture-of-experts model for coding and agent harnesses, with parallel tool calls, about 200K of context and parsers in vLLM and SGLang. It needs a 4 GPU server for FP8 or about 166 GB for a 4-bit library build, and it always thinks. The main risk is the licence, switched to non-commercial two days after release.

**Qwen3.5-0.8B.** A tiny vision-language cousin for prototypes, fine-tuning and light local steps such as routing, tagging or reading an image, running in under 2 GB in every major runtime under plain Apache 2.0. Keep thinking off, since the card warns it loops. The main risk is neglect, with no hosted option, safety results or answers from Alibaba since March.

## Before you call either

### MiniMax-M2.7

1. Check the use is personal, research or non-profit before starting it; anything commercial needs MiniMax's written authorisation, and commercial users must show Built with MiniMax M2.7
2. Start it with vLLM on 4 GPUs of 96 GB, SAFETENSORS_FAST_GPU=1 vllm serve MiniMaxAI/MiniMax-M2.7 --trust-remote-code --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser minimax_m2 --reasoning-parser minimax_m2_append_think
3. In SGLang use --tool-call-parser minimax-m2 and --reasoning-parser minimax-append-think, with --trust-remote-code
4. MiniMax's guides budget 220 GB for the weights and 240 GB per 1M tokens of KV cache, with 196K the most per sequence
5. On one large-memory machine, LM Studio's catalogue entry minimax/minimax-m2.7 lists a 138 GB Q4_K_M GGUF and states 138 GB minimum memory
6. Sample with temperature 1.0, top_p 0.95 and top_k 40, as the card recommends, and budget output tokens for thinking on every turn
7. Pin Transformers 4.57.1 as MiniMax's guide does; a report that it fails on Transformers v5 has no answer
8. Without the hardware, call it through Novita, Featherless AI or DeepInfra; MiniMax's own API retires M2.7 on 18 November 2026

### Qwen3.5-0.8B

1. Smallest start is `ollama run qwen3.5:0.8b`, or `qwen3.5:0.8b-q8_0` at 1.0 GB
2. Full precision `vllm serve Qwen/Qwen3.5-0.8B --port 8000 --max-model-len 262144 --enable-auto-tool-choice --tool-call-parser qwen3_coder`
3. Thinking is off by default; if you turn it on with `"chat_template_kwargs": {"enable_thinking": true}`, stream and cut off runaway output, since the card warns of thinking loops, and add `--reasoning-parser qwen3` in vLLM or SGLang to split the reasoning out
4. There's no generation_config.json, so pass the card's sampling yourself, for example `temperature=1.0, top_p=1.0, top_k=20, presence_penalty=2.0` for text without thinking
5. Use it for narrow steps or as a fine-tuning base, not as the main agent, as the card itself suggests
6. Validate any JSON it returns, since structured output isn't documented

## Questions

### Which is better for AI agents, MiniMax-M2.7 or Qwen3.5-0.8B?

MiniMax-M2.7 scores 56.1 (C) on agent readiness against Qwen3.5-0.8B's 46.7 (D), and leads in 2 of 5 scored categories. Qwen3.5-0.8B leads on reach, risk and documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-0-8b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-5-0-8b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "minimax-m2-7", "b": "qwen3-5-0-8b"}`. From a terminal: `anchor compare minimax-m2-7 qwen3-5-0-8b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/minimax-m2-7.json and https://www.anchorterminal.com/api/v1/tools/qwen3-5-0-8b.json

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- [MiniMax-M2.7 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-8-27b.md)
- [MiniMax-M2.7 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-8-flash-next.md)
- [MiniMax-M2.7 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-coder-30b-a3b-instruct.md)
- [MiniMax-M2.7 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-coder-next.md)
- [MiniMax-M2.7 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-omni-30b-a3b-instruct.md)
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- [MiniMax-M2.7 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-30b-a3b-instruct.md)
- [MiniMax-M2.7 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-32b-instruct.md)
- [MiniMax-M2.7 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-4b-instruct.md)
- [MiniMax-M2.7 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-8b-instruct.md)
- [MiniMax-M2.7 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwopus3-8-27b-flash-v2.md)
- [MiniMax-M2.7 vs SmolLM3-3B](https://www.anchorterminal.com/compare/minimax-m2-7-vs-smollm3-3b.md)
- [MiniMax-M2.7 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/minimax-m2-7-vs-spark-x2-6-4b.md)
- [MiniMax-M2.7 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/minimax-m2-7-vs-swift-1-5-qwen3-8-27b.md)
- [MiniMax-M2.7 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/minimax-m2-7-vs-swift-1-5-qwen3-8-flash-next.md)
- [MiniMax-M2.7 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/minimax-m2-7-vs-thinkingcap-qwen3-8-27b.md)
- [Muse Glimmer 30B vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-qwen3-5-0-8b.md)
- [Nemotron 3.5 Lightning 30B A3B vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-qwen3-5-0-8b.md)
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- [Nemotron 3 Nano 4B vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-qwen3-5-0-8b.md)
- [Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-5-0-8b.md)
- [Nemotron 3 Super 120B A12B vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-0-8b.md)
- [Nemotron 3 Ultra 550B A55B vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-5-0-8b.md)
- [occamy-1.0 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-0-8b.md)
- [Olmo 3 7B Think vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-0-8b.md)
- [Ornith-1.5-35B-A3B vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-5-0-8b.md)
- [Ornith-1.5-397B vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-5-0-8b.md)
- [Ornith-1.5-9B vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-5-0-8b.md)
- [Qwen3-30B-A3B-Instruct-2507 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-5-0-8b.md)
- [Qwen3-4B-Instruct-2507 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-0-8b.md)
- [Qwen3.5-0.8B vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-5-122b-a10b.md)
- [Qwen3.5-0.8B vs Qwen3.5-2B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-5-2b.md)
- [Qwen3.5-0.8B vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-5-397b-a17b.md)
- [Qwen3.5-0.8B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-5-4b.md)
- [Qwen3.5-0.8B vs Qwen3.5-9B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-5-9b.md)
- [Qwen3.5-0.8B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-6-27b.md)
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- [Qwen3.5-0.8B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-coder-30b-a3b-instruct.md)
- [Qwen3.5-0.8B vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-coder-next.md)
- [Qwen3.5-0.8B vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-omni-30b-a3b-instruct.md)
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- [Qwen3.5-0.8B vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-vl-30b-a3b-instruct.md)
- [Qwen3.5-0.8B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-vl-32b-instruct.md)
- [Qwen3.5-0.8B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-vl-4b-instruct.md)
- [Qwen3.5-0.8B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-vl-8b-instruct.md)
- [Qwen3.5-0.8B vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwopus3-8-27b-flash-v2.md)
- [Qwen3.5-0.8B vs SmolLM3-3B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-smollm3-3b.md)
- [Qwen3.5-0.8B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-spark-x2-6-4b.md)
- [Qwen3.5-0.8B vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-swift-1-5-qwen3-8-27b.md)
- [Qwen3.5-0.8B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-swift-1-5-qwen3-8-flash-next.md)
- [Qwen3.5-0.8B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-thinkingcap-qwen3-8-27b.md)

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Query this catalogue directly over MCP: https://www.anchorterminal.com/mcp (Streamable HTTP, no key). How: https://www.anchorterminal.com/agents/#mcp
