# Mistral Large 4 vs Qwen3.6-27B

> Qwen3.6-27B scores 67.2 (B) to Mistral Large 4's 54.6 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-6-27b
- Markdown: https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-6-27b.md (~6,750 tokens)
- Slim: https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-6-27b.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-6-27b.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: 2026-10-30

Qwen3.6-27B scores 67.2 (B) on agent readiness against Mistral Large 4's 54.6 (C), and leads in 2 of 5 scored categories. Mistral Large 4 leads on risk, agent interface and documentation and upkeep. Both do open-weight models you run yourself.

- Mistral Large 4: grade C, 54.6/100, rank #92 of 117 open-weight models. Markdown https://www.anchorterminal.com/tools/mistral-large-4.md · JSON https://www.anchorterminal.com/api/v1/tools/mistral-large-4.json
- Qwen3.6-27B: grade B, 67.2/100, rank #11 of 117 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-6-27b.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-6-27b.json
- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md
- All 3588 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### Mistral Large 4 (C)

Good for: Operators with an 8-GPU Blackwell or H200 node who want a frontier-sized open model for coding agents and defensive security, with a hosted twin on Mistral's API.

Ahead on:
- Risk, 75 against 55
- Agent interface, 95 against 70
- Documentation and upkeep, 64 against 36

Watch for: The smallest 4-bit build needs about 732 GB, so nothing fits a single workstation or a 128 GB machine

### Qwen3.6-27B (B)

Good for: Agents that want an open coding and tool-calling model with vision on one 24 to 32 GB GPU or Mac, with plain licence terms.

Ahead on:
- Capability, 66 against 32
- Reach, 90 against 50

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


## Score by category

| Category | Weight | Mistral Large 4 | Qwen3.6-27B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35% (35 this run) | 32 | 66 | Qwen3.6-27B +34 |
| Reach | 25% (25 this run) | 50 | 90 | Qwen3.6-27B +40 |
| Risk | 20% (20 this run) | 75 | 55 | Mistral Large 4 +20 |
| Agent interface | 10% (10 this run) | 95 | 70 | Mistral Large 4 +25 |
| Documentation and upkeep | 10% (10 this run) | 64 | 36 | Mistral Large 4 +28 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **54.6 · C** | **67.2 · B** | |

## Facts side by side

| Fact | Mistral Large 4 | Qwen3.6-27B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Mistral AI | Alibaba (Qwen team) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Mistral Ecosystem Open-Weight License (modified MIT) | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-10-29 | 2026-04-22 |
| 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 | none | 3/5 (4) |

## Verdicts

**Mistral Large 4.** A frontier-sized open cousin for coding agents and defensive security, with strict JSON Schema output, parallel tool calls and three reasoning efforts. It needs a multi-GPU server, about 732 GB for the smallest 4-bit build, and vLLM and SGLang run it only from special images. The main risk is a licence that bars Model-as-a-Service businesses without a separate deal.

**Qwen3.6-27B.** A capable dense cousin for agentic coding and tool calls with images and video in, running in every major runtime. Ollama's 4-bit build needs about 22 GB, and three providers host it. The main risk is silence, with no safety results, no agent guidance, no answers in its repository and Qwen3.8-27B now ahead of it.

## Before you call either

### Mistral Large 4

1. Serve the NVFP4 build on Blackwell with `vllm/vllm-openai:mistral-large-4 --model mistralai/Mistral-Large-4-1T-A52B-NVFP4 --tensor-parallel-size 8 --kv-cache-dtype fp8_ds_mla --tool-call-parser mistral --reasoning-parser mistral --enable-auto-tool-choice`; released vLLM doesn't load it
2. On H200 use the FP8 build with tensor parallelism of 16 or 8 by 2 pipelines, per vLLM's recipe
3. Pass `reasoning_effort` low, medium or high (default high); any other value makes the template raise an error, and there is no off switch
4. Read the reasoning from `message.reasoning`; `max_completion_tokens` counts reasoning tokens too
5. Use temperature 1.0 and top_p 0.95 at every effort, per the card
6. Ask for JSON with `response_format` type json_schema and strict true; the template passes the schema to the model
7. The template rejects a tool message straight after a user message and a conversation that doesn't start with a user or system message
8. Add `--speculative-config '{"method": "dspark", "num_speculative_tokens": 3}'` to use the embedded draft head
9. If you'll offer it to others as a hosted model, read the licence first; Model-as-a-Service use needs Mistral's commercial licence

### Qwen3.6-27B

1. Quickest start is `ollama run qwen3.6:27b`, about 18 GB of files with the vision projector
2. Alibaba's FP8 build with the card's parsers is `vllm serve Qwen/Qwen3.6-27B-FP8 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, vllm 0.19.0 or later
3. Use the qwen3_coder tool parser, the template writes calls as function and parameter blocks inside tool_call
4. Thinking is on by default, pass `"chat_template_kwargs": {"enable_thinking": false}` for short tasks, and `/think` and `/nothink` aren't supported
5. `"preserve_thinking": true` in chat_template_kwargs keeps earlier reasoning in context, which helps long agent sessions but grows the prompt
6. Sampling per the card is temperature 1.0, top_p 0.95, top_k 20 when thinking, and temperature 0.7, top_p 0.8, presence_penalty 1.5 without
7. Keep at least 128K of context if you rely on thinking, and turn on YaRN only beyond 262,144 tokens
8. Validate any JSON it returns or use the runtime's guided decoding, since structured output isn't documented
9. Qwen3.8-27B (listed as qwen3-8-27b) is the newer model at this size on the same runtimes

## Questions

### Which is better for AI agents, Mistral Large 4 or Qwen3.6-27B?

Qwen3.6-27B scores 67.2 (B) on agent readiness against Mistral Large 4's 54.6 (C), and leads in 2 of 5 scored categories. Mistral Large 4 leads on risk, agent interface and documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-6-27b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-6-27b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "mistral-large-4", "b": "qwen3-6-27b"}`. From a terminal: `anchor compare mistral-large-4 qwen3-6-27b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/mistral-large-4.json and https://www.anchorterminal.com/api/v1/tools/qwen3-6-27b.json

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- [Mistral Large 4 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-6-35b-a3b.md)
- [Mistral Large 4 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-8-27b.md)
- [Mistral Large 4 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-8-flash-next.md)
- [Mistral Large 4 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-coder-30b-a3b-instruct.md)
- [Mistral Large 4 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-coder-next.md)
- [Mistral Large 4 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-omni-30b-a3b-instruct.md)
- [Mistral Large 4 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-vl-2b-instruct.md)
- [Mistral Large 4 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-vl-30b-a3b-instruct.md)
- [Mistral Large 4 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-vl-32b-instruct.md)
- [Mistral Large 4 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-vl-4b-instruct.md)
- [Mistral Large 4 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-vl-8b-instruct.md)
- [Mistral Large 4 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/mistral-large-4-vs-qwopus3-8-27b-flash-v2.md)
- [Mistral Large 4 vs Recursive Flint](https://www.anchorterminal.com/compare/mistral-large-4-vs-recursive-flint.md)
- [Mistral Large 4 vs SmolLM3-3B](https://www.anchorterminal.com/compare/mistral-large-4-vs-smollm3-3b.md)
- [Mistral Large 4 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/mistral-large-4-vs-spark-x2-6-4b.md)
- [Mistral Large 4 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/mistral-large-4-vs-swift-1-5-qwen3-8-27b.md)
- [Mistral Large 4 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/mistral-large-4-vs-swift-1-5-qwen3-8-flash-next.md)
- [Mistral Large 4 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/mistral-large-4-vs-thinkingcap-qwen3-8-27b.md)
- [Mistral Large 4 vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/mistral-large-4-vs-unlimited-ocr-2.md)
- [Muse Glimmer 30B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-qwen3-6-27b.md)
- [Nanbeige4.3-33B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-qwen3-6-27b.md)
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- [Nemotron 3 Nano 30B A3B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-6-27b.md)
- [Nemotron 3 Nano 4B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-qwen3-6-27b.md)
- [Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3.6-27B](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-6-27b.md)
- [Nemotron 3 Super 120B A12B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-6-27b.md)
- [Nemotron 3 Ultra 550B A55B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-6-27b.md)
- [occamy-1.0 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-6-27b.md)
- [Olmo 3 7B Think vs Qwen3.6-27B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-6-27b.md)
- [Ornith-1.5-35B-A3B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-6-27b.md)
- [Ornith-1.5-397B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-6-27b.md)
- [Ornith-1.5-9B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-6-27b.md)
- [Qwen3-30B-A3B-Instruct-2507 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-6-27b.md)
- [Qwen3-4B-Instruct-2507 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-6-27b.md)
- [Qwen3.5-0.8B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-qwen3-6-27b.md)
- [Qwen3.5-122B-A10B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-qwen3-6-27b.md)
- [Qwen3.5-2B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/qwen3-5-2b-vs-qwen3-6-27b.md)
- [Qwen3.5-397B-A17B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-qwen3-6-27b.md)
- [Qwen3.5-4B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/qwen3-5-4b-vs-qwen3-6-27b.md)
- [Qwen3.5-9B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/qwen3-5-9b-vs-qwen3-6-27b.md)
- [Qwen3.6-27B vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-6-35b-a3b.md)
- [Qwen3.6-27B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-8-27b.md)
- [Qwen3.6-27B vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-8-flash-next.md)
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- [Qwen3.6-27B vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-coder-next.md)
- [Qwen3.6-27B vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-omni-30b-a3b-instruct.md)
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- [Qwen3.6-27B vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-vl-30b-a3b-instruct.md)
- [Qwen3.6-27B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-vl-32b-instruct.md)
- [Qwen3.6-27B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-vl-4b-instruct.md)
- [Qwen3.6-27B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwen3-vl-8b-instruct.md)
- [Qwen3.6-27B vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-qwopus3-8-27b-flash-v2.md)
- [Qwen3.6-27B vs Recursive Flint](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-recursive-flint.md)
- [Qwen3.6-27B vs SmolLM3-3B](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-smollm3-3b.md)
- [Qwen3.6-27B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-spark-x2-6-4b.md)
- [Qwen3.6-27B vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-swift-1-5-qwen3-8-27b.md)
- [Qwen3.6-27B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-swift-1-5-qwen3-8-flash-next.md)
- [Qwen3.6-27B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-thinkingcap-qwen3-8-27b.md)
- [Qwen3.6-27B vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-unlimited-ocr-2.md)

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