Model comparison
Codestral vs Qwen3.6 35B-A3B
Qwen3.6 35B-A3B is the stronger model overall, scoring 37.6 to 30.6 on the Noometry Index.
Last verified . 0 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- The widest gap is in coding, where Qwen3.6 35B-A3B leads 37.2 to 27.3.
- Codestral is cheaper at $0.30 / $0.90 per million input/output tokens, against $0.25 / $1.49 for Qwen3.6 35B-A3B.
- Qwen3.6 35B-A3B accepts more context: 262K tokens versus 256K.
- Qwen3.6 35B-A3B has downloadable open weights; the other is API-only.
Side by side
| Codestral | Qwen3.6 35B-A3B | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 30.6 | 37.6 |
| Released | 2024-05-29 | 2026-04-01 |
| Weights | Proprietary | Open |
| Context window | 256K | 262K |
| Max output | 8K | 66K |
| Input $ / M tokens | $0.30 | $0.25 |
| Output $ / M tokens | $0.90 | $1.49 |
| Results tracked | 7 | 14 |
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Category by category
Coding Qwen3.6 35B-A3B leads
Codestral: 27.3 (#321), Qwen3.6 35B-A3B: 37.2 (#196)
| Benchmark | Codestral | Qwen3.6 35B-A3B |
|---|---|---|
| Aider Polyglot | 11.1% | — |
| SciCode | — | 35.8% |
| WeirdML | — | 34.5% |
| BigCodeBench Instruct | 41.8% | — |
| BigCodeBench Complete | 52.5% | — |
| ALE-Bench | 137.78 | — |
| HumanEval+ | 73.8% | — |
| MBPP+ | 61.9% | — |
Agentic & Tool Use Not comparable
Codestral: —, Qwen3.6 35B-A3B: 22.1 (#134)
| Benchmark | Codestral | Qwen3.6 35B-A3B |
|---|---|---|
| Terminal-Bench | — | 23% |
Reasoning Qwen3.6 35B-A3B leads
Codestral: 19.8 (#251), Qwen3.6 35B-A3B: 28.0 (#109)
| Benchmark | Codestral | Qwen3.6 35B-A3B |
|---|---|---|
| Kagi LLM Benchmark | 32.5% | — |
| NYT Connections (extended) | — | 41.6% |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 26% |
| Mystery Game Puzzles | — | 22% |
| DTBench | — | 73.9% |
| LMCA | — | 29.7% |
| Surface Evolver Bench | — | 44.4% |
| Epoch Capabilities Index | — | 143.93 |
Math Not comparable
Codestral: —, Qwen3.6 35B-A3B: 38.9 (#121)
| Benchmark | Codestral | Qwen3.6 35B-A3B |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 20.4% |
| OTIS Mock AIME 2024-2025 | — | 86.7% |
Knowledge Not comparable
Codestral: —, Qwen3.6 35B-A3B: 51.3 (#68)
| Benchmark | Codestral | Qwen3.6 35B-A3B |
|---|---|---|
| GPQA Diamond | — | 84.8% |
Frequently asked questions
Is Codestral better than Qwen3.6 35B-A3B?
Qwen3.6 35B-A3B is the stronger model overall, scoring 37.6 to 30.6 on the Noometry Index.
Which is cheaper, Codestral or Qwen3.6 35B-A3B?
Codestral is cheaper. It lists at $0.30 per million input tokens and $0.90 per million output tokens; Qwen3.6 35B-A3B lists at $0.25 and $1.49.
Is Codestral or Qwen3.6 35B-A3B better for coding?
Qwen3.6 35B-A3B scores higher on coding benchmarks: 37.2 versus 27.3 in the Noometry coding category.
Which has the bigger context window?
Qwen3.6 35B-A3B does, with 262K tokens against 256K.
How many benchmarks do Codestral and Qwen3.6 35B-A3B share?
0 benchmarks have published results for both models. Codestral has 7 scored results on Noometry and Qwen3.6 35B-A3B has 14.