Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Mistral Small 4 (Reasoning)
~64
1/8 categoriesQwen3.6 Plus
69
Winner · 2/8 categoriesMistral Small 4 (Reasoning)· Qwen3.6 Plus
Pick Qwen3.6 Plus if you want the stronger benchmark profile. Mistral Small 4 (Reasoning) only becomes the better choice if knowledge is the priority.
Qwen3.6 Plus is clearly ahead on the aggregate, 69 to 64. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.6 Plus's sharpest advantage is in multimodal & grounded, where it averages 78.8 against 60. The single biggest benchmark swing on the page is GPQA, 71.2% to 90.4%. Mistral Small 4 (Reasoning) does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Qwen3.6 Plus gives you the larger context window at 1M, compared with 256K for Mistral Small 4 (Reasoning).
BenchLM keeps the benchmark table and the operator tradeoffs on the same page so a better score does not hide a materially slower, pricier, or smaller-context model.
Runtime metrics show N/A when BenchLM does not have a sourced snapshot for that exact model. The scoring rules and freshness policy are documented on the methodology page.
| Benchmark | Mistral Small 4 (Reasoning) | Qwen3.6 Plus |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 61.6% |
| Claw-Eval | — | 58.7% |
| QwenClawBench | — | 57.2% |
| QwenWebBench | — | 1502 |
| TAU3-Bench | — | 70.7% |
| VITA-Bench | — | 44.3% |
| DeepPlanning | — | 41.5% |
| Toolathlon | — | 39.8% |
| MCP Atlas | — | 48.2% |
| MCP-Tasks | — | 74.1% |
| WideResearch | — | 74.3% |
| OSWorld-Verified | — | 62.5% |
| CodingQwen3.6 Plus wins | ||
| LiveCodeBench | 63.6% | — |
| SWE-bench Verified | — | 78.8% |
| SWE-bench Pro | — | 56.6% |
| SWE Multilingual | — | 73.8% |
| LiveCodeBench v6 | — | 87.1% |
| NL2Repo | — | 37.9% |
| Multimodal & GroundedQwen3.6 Plus wins | ||
| MMMU-Pro | 60% | 78.8% |
| MMMU | — | 86.0% |
| RealWorldQA | — | 85.4% |
| OmniDocBench 1.5 | — | 91.2% |
| Video-MME (with subtitle) | — | 87.8% |
| Video-MME (w/o subtitle) | — | 84.2% |
| MathVision | — | 88.0% |
| We-Math | — | 89.0% |
| DynaMath | — | 88.0% |
| MStar | — | 83.3% |
| SimpleVQA | — | 67.3% |
| ChatCVQA | — | 81.5% |
| MMLongBench-Doc | — | 62.0% |
| CC-OCR | — | 83.4% |
| AI2D_TEST | — | 94.4% |
| CountBench | — | 97.6% |
| RefCOCO (avg) | — | 93.5% |
| ODINW13 | — | 51.8% |
| ERQA | — | 65.7% |
| VideoMMMU | — | 84.0% |
| MLVU (M-Avg) | — | 86.7% |
| ScreenSpot Pro | — | 68.2% |
| Reasoning | ||
| AI-Needle | — | 68.3% |
| LongBench v2 | — | 62% |
| KnowledgeMistral Small 4 (Reasoning) wins | ||
| GPQA | 71.2% | 90.4% |
| MMLU-Pro | 78% | 88.5% |
| SuperGPQA | — | 71.6% |
| MMLU-Redux | — | 94.5% |
| C-Eval | — | 93.3% |
| HLE | — | 28.8% |
| Instruction Following | ||
| IFEval | — | 94.3% |
| IFBench | — | 74.2% |
| Multilingual | ||
| MMLU-ProX | — | 84.7% |
| NOVA-63 | — | 57.9% |
| INCLUDE | — | 85.1% |
| PolyMath | — | 77.4% |
| VWT2k-lite | — | 84.3% |
| MAXIFE | — | 88.2% |
| Mathematics | ||
| AIME 2025 | 83.8% | — |
| AIME26 | — | 95.3% |
| HMMT Feb 2025 | — | 96.7% |
| HMMT Nov 2025 | — | 94.6% |
| HMMT Feb 2026 | — | 87.8% |
| MMAnswerBench | — | 83.8% |
Qwen3.6 Plus is ahead overall, 69 to 64. The biggest single separator in this matchup is GPQA, where the scores are 71.2% and 90.4%.
Mistral Small 4 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 75.6 versus 66. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Qwen3.6 Plus has the edge for coding in this comparison, averaging 64.9 versus 63.6. Mistral Small 4 (Reasoning) stays close enough that the answer can still flip depending on your workload.
Qwen3.6 Plus has the edge for multimodal and grounded tasks in this comparison, averaging 78.8 versus 60. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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