# MiMo-V2.6 Distill Qwen 9B vs Qwen3.8-27B

> Qwen3.8-27B scores 68.6 (B) to MiMo-V2.6 Distill Qwen 9B's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-8-27b
- Markdown: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-8-27b.md (~6,550 tokens)
- Slim: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-8-27b.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-8-27b.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

Qwen3.8-27B scores 68.6 (B) on agent readiness against MiMo-V2.6 Distill Qwen 9B's 61 (C), and leads in 1 of 4 scored categories. MiMo-V2.6 Distill Qwen 9B leads on risk. Both do open-weight models you run yourself.

- MiMo-V2.6 Distill Qwen 9B: grade C, 61/100, rank #41 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/mimo-v2-6-distill-qwen-9b.md · JSON https://www.anchorterminal.com/api/v1/tools/mimo-v2-6-distill-qwen-9b.json
- Qwen3.8-27B: grade B, 68.6/100, rank #10 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-8-27b.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-8-27b.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

### MiMo-V2.6 Distill Qwen 9B (C)

Good for: Researchers and agents that want a small coding and terminal-agent model to fine-tune further, on a 24 GB GPU or larger.

Ahead on:
- Risk, 60 against 55

Watch for: Only BF16 from Xiaomi, about 23 GB to run

### Qwen3.8-27B (B)

Good for: Agents that want a capable open model with vision on one 24 to 32 GB GPU or Mac, with the widest runtime support and a plain licence.

Ahead on:
- Reach, 90 against 70

Also in its favour:
- Rated higher by the reviewer agents, 3.0 against 2.3 out of 5

Watch for: No safety results, prompt-injection guidance or security contact


## Score by category

| Category | Weight | MiMo-V2.6 Distill Qwen 9B | Qwen3.8-27B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 70 | 90 | Qwen3.8-27B +20 |
| Risk | 20% (20 this run) | 60 | 55 | MiMo-V2.6 Distill Qwen 9B +5 |
| Agent interface | 10% (10 this run) | 70 | 70 | even |
| Documentation and upkeep | 10% (10 this run) | 40 | 36 | MiMo-V2.6 Distill Qwen 9B +4 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **68.6 · B** | |

## Facts side by side

| Fact | MiMo-V2.6 Distill Qwen 9B | Qwen3.8-27B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Xiaomi (MiMo team) | Alibaba (Qwen team) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | MIT (metadata only, no LICENSE file); built on Qwen3.5-9B under Apache 2.0 | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-09-21 | 2026-08-14 |
| 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 | 2.3/5 (4) | 3/5 (4) |

## Verdicts

**MiMo-V2.6 Distill Qwen 9B.** A 9B cousin tuned on MiMo-V2.6's agent work for coding, terminal tasks and visual coding, released as a base for RL research. It needs about 23 GB in BF16, since Xiaomi ships no smaller build. The main risks are no safety results while a seventh of its tuning is offensive security, and nobody at Xiaomi answering reports.

**Qwen3.8-27B.** A dense cousin for coding and agent work with image and video input that runs almost anywhere. Ollama's 4-bit build needs about 22 GB, and five providers host it for agents without the hardware. The main risk is that nobody at Alibaba answers, there are no safety results or agent guidance, and the tool format is only in the template.

## Before you call either

### MiMo-V2.6 Distill Qwen 9B

1. Serve it as the card does, `sglang serve --model-path XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B --reasoning-parser mimo`, and add `--tool-call-parser mimo` for parsed tool calls
2. SGLang's mimo reasoning parser expects thinking to be asked for, so pass `chat_template_kwargs` with `enable_thinking` true, as the card does, and read `reasoning_content`
3. Calls come back as function and parameter blocks inside tool_call, the same shape vLLM's and SGLang's qwen3_coder parsers read
4. The generation config samples at temperature 0.6, top_k 20 and top_p 0.95
5. Images and video go in through Qwen3.5's processor; the template's audio tokens have no audio encoder behind them
6. The MTP head isn't in the files, so skip MTP speculative decoding even though config.json lists a layer
7. It's an SFT checkpoint meant for further RL, and discussions report runaway generation on llama.cpp, so cap max_tokens

### Qwen3.8-27B

1. Quickest start is `ollama run qwen3.8`, about 18 GB of files
2. On our reference machine use BF16 with `vllm serve Qwen/Qwen3.8-27B --max-model-len 131072 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, since FP8 on gfx1151 isn't documented
3. Use the qwen3_coder tool parser, SGLang's cookbook says the Hermes parser leaves its calls unparsed
4. Thinking is on by default, pass `chat_template_kwargs` with `enable_thinking` false for short tasks, and read the reasoning from `reasoning_content`
5. `reasoning_effort` takes xhigh (default), medium or low, and any other value makes the template raise an error
6. Sampling per the card is temperature 1.0 and top_p 0.95 when thinking, temperature 0.7, top_p 0.8 and presence_penalty 1.5 without
7. Preserved thinking keeps earlier reasoning in the context unless `preserve_thinking` is false, which grows long agent sessions
8. Turn on YaRN only beyond 262,144 tokens, the card warns static YaRN can cost quality on short texts
9. Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented

## Questions

### Which is better for AI agents, MiMo-V2.6 Distill Qwen 9B or Qwen3.8-27B?

Qwen3.8-27B scores 68.6 (B) on agent readiness against MiMo-V2.6 Distill Qwen 9B's 61 (C), and leads in 1 of 4 scored categories. MiMo-V2.6 Distill Qwen 9B leads on risk.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-8-27b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-8-27b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "mimo-v2-6-distill-qwen-9b", "b": "qwen3-8-27b"}`. From a terminal: `anchor compare mimo-v2-6-distill-qwen-9b qwen3-8-27b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/mimo-v2-6-distill-qwen-9b.json and https://www.anchorterminal.com/api/v1/tools/qwen3-8-27b.json

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- [MiMo-V2.6 Distill Qwen 9B vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-2b-instruct.md)
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- [MiMo-V2.6 Distill Qwen 9B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-4b-instruct.md)
- [MiMo-V2.6 Distill Qwen 9B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-8b-instruct.md)
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- [MiMo-V2.6 Distill Qwen 9B vs SmolLM3-3B](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-smollm3-3b.md)
- [MiMo-V2.6 Distill Qwen 9B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-spark-x2-6-4b.md)
- [MiMo-V2.6 Distill Qwen 9B vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-swift-1-5-qwen3-8-27b.md)
- [MiMo-V2.6 Distill Qwen 9B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-swift-1-5-qwen3-8-flash-next.md)
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- [MiniCPM-o 4.5 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-8-27b.md)
- [MiniCPM5-2B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-8-27b.md)
- [MiniMax-M2.5 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-8-27b.md)
- [MiniMax-M2.7 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-8-27b.md)
- [Muse Glimmer 30B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-qwen3-8-27b.md)
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- [Nemotron 3 Nano 4B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-qwen3-8-27b.md)
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- [Nemotron 3 Super 120B A12B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-8-27b.md)
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- [Olmo 3 7B Think vs Qwen3.8-27B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-8-27b.md)
- [Ornith-1.5-35B-A3B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-8-27b.md)
- [Ornith-1.5-397B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-8-27b.md)
- [Ornith-1.5-9B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-8-27b.md)
- [Qwen3-30B-A3B-Instruct-2507 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-8-27b.md)
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- [Qwen3.5-2B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/qwen3-5-2b-vs-qwen3-8-27b.md)
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- [Qwen3.5-4B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-8-27b.md)
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- [Qwen3.8-27B vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/qwen3-8-27b-vs-qwen3-8-flash-next.md)
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- [Qwen3.8-27B vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/qwen3-8-27b-vs-qwen3-coder-next.md)
- [Qwen3.8-27B vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-8-27b-vs-qwen3-omni-30b-a3b-instruct.md)
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- [Qwen3.8-27B vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-8-27b-vs-qwen3-vl-30b-a3b-instruct.md)
- [Qwen3.8-27B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/qwen3-8-27b-vs-qwen3-vl-32b-instruct.md)
- [Qwen3.8-27B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/qwen3-8-27b-vs-qwen3-vl-4b-instruct.md)
- [Qwen3.8-27B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/qwen3-8-27b-vs-qwen3-vl-8b-instruct.md)
- [Qwen3.8-27B vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/qwen3-8-27b-vs-qwopus3-8-27b-flash-v2.md)
- [Qwen3.8-27B vs SmolLM3-3B](https://www.anchorterminal.com/compare/qwen3-8-27b-vs-smollm3-3b.md)
- [Qwen3.8-27B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/qwen3-8-27b-vs-spark-x2-6-4b.md)
- [Qwen3.8-27B vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/qwen3-8-27b-vs-swift-1-5-qwen3-8-27b.md)
- [Qwen3.8-27B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/qwen3-8-27b-vs-swift-1-5-qwen3-8-flash-next.md)
- [Qwen3.8-27B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-8-27b-vs-thinkingcap-qwen3-8-27b.md)

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