Model comparison
Mistral Small 3.2 vs Qwen3.6 27B
Qwen3.6 27B is the stronger model overall, scoring 42.2 to 31.2 on the Noometry Index. Mistral Small 3.2 costs 10× less per token, which makes it the better buy when Qwen3.6 27B's lead doesn't matter for your workload.
Last verified . 4 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 4 benchmarks with published results for both. Mistral Small 3.2 scores higher in 0 categories and Qwen3.6 27B in 4 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.6 27B leads 52.4 to 26.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 30.3% for Mistral Small 3.2 and 91.1% for Qwen3.6 27B.
- Mistral Small 3.2 is cheaper at $0.0938 / $0.25 per million input/output tokens, against $0.60 / $3.60 for Qwen3.6 27B.
- Qwen3.6 27B accepts more context: 262K tokens versus 256K.
Side by side
| Mistral Small 3.2 | Qwen3.6 27B | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 31.2 | 42.2 |
| Released | 2025-06-20 | 2026-04-22 |
| Weights | Open | Open |
| Context window | 256K | 262K |
| Max output | 16K | 66K |
| Input $ / M tokens | $0.0938 | $0.60 |
| Output $ / M tokens | $0.25 | $3.60 |
| Results tracked | 6 | 11 |
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Category by category
Coding Not comparable
Mistral Small 3.2: —, Qwen3.6 27B: 39.1 (#163)
| Benchmark | Mistral Small 3.2 | Qwen3.6 27B |
|---|---|---|
| SciCode | — | 37.3% |
Reasoning Qwen3.6 27B leads
Mistral Small 3.2: 18.1 (#287), Qwen3.6 27B: 25.0 (#153)
| Benchmark | Mistral Small 3.2 | Qwen3.6 27B |
|---|---|---|
| Chess Puzzles | 1% | 22% |
| Epoch Capabilities Index | 131.74 | 146.5 |
| Kagi LLM Benchmark | 40.4% | — |
| CritPt | — | 0.9% |
| Mystery Game Puzzles | — | 7% |
| DTBench | — | 78.1% |
| LMCA | — | 34.5% |
Math Qwen3.6 27B leads
Mistral Small 3.2: 26.3 (#260), Qwen3.6 27B: 48.5 (#62)
| Benchmark | Mistral Small 3.2 | Qwen3.6 27B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 30.3% | 91.1% |
| FrontierMath (Tiers 1-3) | — | 35.1% |
Knowledge Qwen3.6 27B leads
Mistral Small 3.2: 26.7 (#256), Qwen3.6 27B: 52.4 (#63)
| Benchmark | Mistral Small 3.2 | Qwen3.6 27B |
|---|---|---|
| GPQA Diamond | 49.1% | 85.9% |
Writing & Preference Qwen3.6 27B leads
Mistral Small 3.2: 45.0 (#224), Qwen3.6 27B: 50.3 (#181)
| Benchmark | Mistral Small 3.2 | Qwen3.6 27B |
|---|---|---|
| EQ-Bench Creative Writing | 1255 | — |
| EQ-Bench 4 | — | 1026 |
Frequently asked questions
Is Mistral Small 3.2 better than Qwen3.6 27B?
Qwen3.6 27B is the stronger model overall, scoring 42.2 to 31.2 on the Noometry Index. Mistral Small 3.2 costs 10× less per token, which makes it the better buy when Qwen3.6 27B's lead doesn't matter for your workload.
Which is cheaper, Mistral Small 3.2 or Qwen3.6 27B?
Mistral Small 3.2 is cheaper. It lists at $0.0938 per million input tokens and $0.25 per million output tokens; Qwen3.6 27B lists at $0.60 and $3.60.
Which has the bigger context window?
Qwen3.6 27B does, with 262K tokens against 256K.
How many benchmarks do Mistral Small 3.2 and Qwen3.6 27B share?
4 benchmarks have published results for both models. Mistral Small 3.2 has 6 scored results on Noometry and Qwen3.6 27B has 11.