Model comparison
Magistral Small vs Qwen3.6 27B
Qwen3.6 27B is the stronger model overall, scoring 42.2 to 30.2 on the Noometry Index. Magistral Small costs 1.8× less per token, which makes it the better buy when Qwen3.6 27B's lead doesn't matter for your workload.
Last verified . 7 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 7 benchmarks with published results for both. Magistral Small scores higher in 0 categories and Qwen3.6 27B in 4 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3.6 27B leads 48.5 to 26.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 30% for Magistral Small and 91.1% for Qwen3.6 27B.
- Magistral Small is cheaper at $0.50 / $1.50 per million input/output tokens, against $0.60 / $3.60 for Qwen3.6 27B.
- Qwen3.6 27B accepts more context: 262K tokens versus 128K.
Side by side
| Magistral Small | Qwen3.6 27B | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 30.2 | 42.2 |
| Released | 2025-06-10 | 2026-04-22 |
| Weights | Open | Open |
| Context window | 128K | 262K |
| Max output | 40K | 66K |
| Input $ / M tokens | $0.50 | $0.60 |
| Output $ / M tokens | $1.50 | $3.60 |
| Results tracked | 10 | 11 |
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Category by category
Coding Too close to call
Magistral Small: 38.4 (#176), Qwen3.6 27B: 39.1 (#163)
| Benchmark | Magistral Small | Qwen3.6 27B |
|---|---|---|
| SciCode | 35.2% | 37.3% |
Reasoning Qwen3.6 27B leads
Magistral Small: 6.8 (#350), Qwen3.6 27B: 25.0 (#153)
| Benchmark | Magistral Small | Qwen3.6 27B |
|---|---|---|
| CritPt | 0.3% | 0.9% |
| Chess Puzzles | 3% | 22% |
| DTBench | 61.3% | 78.1% |
| Epoch Capabilities Index | 133.19 | 146.5 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 6.3% | — |
| ARC-AGI-1 | 5% | — |
| Mystery Game Puzzles | — | 7% |
| LMCA | — | 34.5% |
Math Qwen3.6 27B leads
Magistral Small: 26.2 (#261), Qwen3.6 27B: 48.5 (#62)
| Benchmark | Magistral Small | Qwen3.6 27B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 30% | 91.1% |
| FrontierMath (Tiers 1-3) | — | 35.1% |
Knowledge Qwen3.6 27B leads
Magistral Small: 30.9 (#223), Qwen3.6 27B: 52.4 (#63)
| Benchmark | Magistral Small | Qwen3.6 27B |
|---|---|---|
| GPQA Diamond | 56.1% | 85.9% |
Writing & Preference Not comparable
Magistral Small: —, Qwen3.6 27B: 50.3 (#181)
| Benchmark | Magistral Small | Qwen3.6 27B |
|---|---|---|
| EQ-Bench 4 | — | 1026 |
Frequently asked questions
Is Magistral Small better than Qwen3.6 27B?
Qwen3.6 27B is the stronger model overall, scoring 42.2 to 30.2 on the Noometry Index. Magistral Small costs 1.8× less per token, which makes it the better buy when Qwen3.6 27B's lead doesn't matter for your workload.
Which is cheaper, Magistral Small or Qwen3.6 27B?
Magistral Small is cheaper. It lists at $0.50 per million input tokens and $1.50 per million output tokens; Qwen3.6 27B lists at $0.60 and $3.60.
Is Magistral Small or Qwen3.6 27B better for coding?
They score almost the same on coding (38.4 vs 39.1); test both on your own repository before choosing.
Which has the bigger context window?
Qwen3.6 27B does, with 262K tokens against 128K.
How many benchmarks do Magistral Small and Qwen3.6 27B share?
7 benchmarks have published results for both models. Magistral Small has 10 scored results on Noometry and Qwen3.6 27B has 11.