Model comparison
Mistral vs Qwen3.6 27B
Qwen3.6 27B is the stronger model overall, scoring 42.2 to 29.9 on the Noometry Index.
Last verified . 0 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- The widest gap is in knowledge, where Qwen3.6 27B leads 52.4 to 16.6.
- Qwen3.6 27B has downloadable open weights; the other is API-only.
Side by side
| Mistral | Qwen3.6 27B | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 29.9 | 42.2 |
| Released | — | 2026-04-22 |
| Weights | Proprietary | Open |
| Context window | — | 262K |
| Max output | — | 66K |
| Input $ / M tokens | — | $0.60 |
| Output $ / M tokens | — | $3.60 |
| Results tracked | 22 | 11 |
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Category by category
Coding Qwen3.6 27B leads
Mistral: 33.8 (#250), Qwen3.6 27B: 39.1 (#163)
| Benchmark | Mistral | Qwen3.6 27B |
|---|---|---|
| SciCode | — | 37.3% |
| LMArena Coding | 1162 | — |
Reasoning Qwen3.6 27B leads
Mistral: 22.2 (#200), Qwen3.6 27B: 25.0 (#153)
| Benchmark | Mistral | Qwen3.6 27B |
|---|---|---|
| CritPt | — | 0.9% |
| Chess Puzzles | — | 22% |
| LMArena Hard Prompts | 1149 | — |
| Mystery Game Puzzles | — | 7% |
| DTBench | — | 78.1% |
| LMCA | — | 34.5% |
| Epoch Capabilities Index | — | 146.5 |
Math Qwen3.6 27B leads
Mistral: 22.3 (#278), Qwen3.6 27B: 48.5 (#62)
| Benchmark | Mistral | Qwen3.6 27B |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 35.1% |
| OTIS Mock AIME 2024-2025 | — | 91.1% |
| Omni-MATH | 7.2% | — |
| LMArena Math | 1180 | — |
Knowledge Qwen3.6 27B leads
Mistral: 16.6 (#288), Qwen3.6 27B: 52.4 (#63)
| Benchmark | Mistral | Qwen3.6 27B |
|---|---|---|
| GPQA Diamond | — | 85.9% |
| MMLU-Pro | 27.7% | — |
| GPQA (HELM) | 30.3% | — |
| LMArena Expert | 1125 | — |
Multilingual Not comparable
Mistral: 32.8 (#254), Qwen3.6 27B: —
| Benchmark | Mistral | Qwen3.6 27B |
|---|---|---|
| LMArena Non-English | 1129 | — |
| LMArena Chinese | 1109 | — |
| LMArena French | 1180 | — |
| LMArena German | 1155 | — |
| LMArena Japanese | 1013 | — |
| LMArena Korean | 1032 | — |
| LMArena Russian | 1168 | — |
| LMArena Spanish | 1143 | — |
Instruction Following Not comparable
Mistral: 52.6 (#288), Qwen3.6 27B: —
| Benchmark | Mistral | Qwen3.6 27B |
|---|---|---|
| IFEval | 56.8% | — |
| LMArena Instruction Following | 1152 | — |
Long Context Not comparable
Mistral: 35.0 (#245), Qwen3.6 27B: —
| Benchmark | Mistral | Qwen3.6 27B |
|---|---|---|
| LMArena Longer Query | 1153 | — |
Writing & Preference Qwen3.6 27B leads
Mistral: 37.0 (#260), Qwen3.6 27B: 50.3 (#181)
| Benchmark | Mistral | Qwen3.6 27B |
|---|---|---|
| LMArena Text | 1165 | — |
| LMArena Creative Writing | 1158 | — |
| WildBench | 66% | — |
| EQ-Bench 4 | — | 1026 |
| LMArena Multi-Turn | 1147 | — |
Frequently asked questions
Is Mistral better than Qwen3.6 27B?
Qwen3.6 27B is the stronger model overall, scoring 42.2 to 29.9 on the Noometry Index.
Is Mistral or Qwen3.6 27B better for coding?
Qwen3.6 27B scores higher on coding benchmarks: 39.1 versus 33.8 in the Noometry coding category.
How many benchmarks do Mistral and Qwen3.6 27B share?
0 benchmarks have published results for both models. Mistral has 22 scored results on Noometry and Qwen3.6 27B has 11.