Model comparison
Mistral Small vs Qwen3 235B-A22B
Qwen3 235B-A22B is the stronger model overall, scoring 43.5 to 33.4 on the Noometry Index. Mistral Small costs 4.7× less per token, which makes it the better buy when Qwen3 235B-A22B's lead doesn't matter for your workload.
Last verified . 27 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 27 benchmarks with published results for both. Mistral Small scores higher in 1 category and Qwen3 235B-A22B in 8 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3 235B-A22B leads 50.4 to 16.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 5.8% for Mistral Small and 86.7% for Qwen3 235B-A22B.
- Mistral Small is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.70 / $2.80 for Qwen3 235B-A22B.
- Mistral Small accepts more context: 262K tokens versus 131K.
Side by side
| Mistral Small | Qwen3 235B-A22B | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 33.4 | 43.5 |
| Released | 2024-02-26 | 2025-04 |
| Weights | Open | Open |
| Context window | 262K | 131K |
| Max output | 256K | 16K |
| Input $ / M tokens | $0.15 | $0.70 |
| Output $ / M tokens | $0.60 | $2.80 |
| Results tracked | 39 | 49 |
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Category by category
Coding Qwen3 235B-A22B leads
Mistral Small: 34.0 (#247), Qwen3 235B-A22B: 44.3 (#75)
| Benchmark | Mistral Small | Qwen3 235B-A22B |
|---|---|---|
| SciCode | 26.5% | 42.4% |
| LMArena Coding | 1362 | 1445 |
| Aider Polyglot | — | 59.6% |
| WeirdML | — | 41% |
| BigCodeBench Instruct | 36.1% | — |
| LiveBench Coding | 36.2% | — |
| BigCodeBench Complete | 46.6% | — |
| ALE-Bench | 497.62 | — |
Agentic & Tool Use Qwen3 235B-A22B leads
Mistral Small: 28.1 (#93), Qwen3 235B-A22B: 33.9 (#51)
| Benchmark | Mistral Small | Qwen3 235B-A22B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 37.1% | 52.1% |
| Vending-Bench 2 | — | -11.34 |
Reasoning Mistral Small leads
Mistral Small: 19.8 (#250), Qwen3 235B-A22B: 15.7 (#311)
| Benchmark | Mistral Small | Qwen3 235B-A22B |
|---|---|---|
| Kagi LLM Benchmark | 37.8% | 69.4% |
| CritPt | 0% | 0% |
| LMArena Hard Prompts | 1335 | 1433 |
| DTBench | 70.9% | 80.3% |
| LMCA | 20.6% | 29.3% |
| ARC-AGI-2 | — | 1.3% |
| SimpleBench | — | 31% |
| ARC-AGI-1 | — | 11% |
| Chess Puzzles | — | 12% |
| LiveBench Reasoning | 44.8% | — |
| Mystery Game Puzzles | — | 9% |
| LiveBench Data Analysis | 53.7% | — |
| Epoch Capabilities Index | — | 143.85 |
| ForecastBench | — | 59.7 |
| LiveBench | 44% | — |
Math Qwen3 235B-A22B leads
Mistral Small: 16.4 (#293), Qwen3 235B-A22B: 50.4 (#57)
| Benchmark | Mistral Small | Qwen3 235B-A22B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 5.8% | 86.7% |
| LMArena Math | 1341 | 1432 |
| MATH Level 5 | 46.8% | 68.9% |
| Omni-MATH | — | 71.8% |
| LiveBench Math | 39.9% | — |
| FrontierMath (Feb 2025 set) | — | 8.5% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge Qwen3 235B-A22B leads
Mistral Small: 31.0 (#222), Qwen3 235B-A22B: 49.6 (#73)
| Benchmark | Mistral Small | Qwen3 235B-A22B |
|---|---|---|
| GPQA Diamond | 47.5% | 80.1% |
| Vectara Hallucination Rate | 5.1% | 9.3% |
| LMArena Expert | 1291 | 1463 |
| SimpleQA Verified | — | 40.4% |
| MMLU-Pro | — | 84.4% |
| Confabulations | — | 15.6% |
| GPQA (HELM) | — | 72.7% |
| MMLU | 68.7% | — |
Multimodal Not comparable
Mistral Small: 33.5 (#96), Qwen3 235B-A22B: —
| Benchmark | Mistral Small | Qwen3 235B-A22B |
|---|---|---|
| LMArena Vision | 1142 | — |
Multilingual Qwen3 235B-A22B leads
Mistral Small: 45.5 (#169), Qwen3 235B-A22B: 52.3 (#89)
| Benchmark | Mistral Small | Qwen3 235B-A22B |
|---|---|---|
| LMArena Non-English | 1315 | 1409 |
| LMArena Chinese | 1340 | 1481 |
| LMArena French | 1337 | 1445 |
| LMArena German | 1340 | 1433 |
| LMArena Japanese | 1275 | 1399 |
| LMArena Korean | 1259 | 1391 |
| LMArena Russian | 1324 | 1411 |
| LMArena Spanish | 1346 | 1430 |
Instruction Following Qwen3 235B-A22B leads
Mistral Small: 66.4 (#209), Qwen3 235B-A22B: 72.6 (#136)
| Benchmark | Mistral Small | Qwen3 235B-A22B |
|---|---|---|
| LMArena Instruction Following | 1310 | 1408 |
| LiveBench Instruction Following | 63.7% | — |
| IFEval | — | 83.5% |
Long Context Qwen3 235B-A22B leads
Mistral Small: 40.4 (#156), Qwen3 235B-A22B: 46.1 (#26)
| Benchmark | Mistral Small | Qwen3 235B-A22B |
|---|---|---|
| LMArena Longer Query | 1327 | 1426 |
| Fiction.LiveBench | — | 75% |
Writing & Preference Qwen3 235B-A22B leads
Mistral Small: 52.5 (#171), Qwen3 235B-A22B: 59.6 (#108)
| Benchmark | Mistral Small | Qwen3 235B-A22B |
|---|---|---|
| LMArena Text | 1338 | 1419 |
| LMArena Creative Writing | 1305 | 1384 |
| LMArena Multi-Turn | 1344 | 1432 |
| Short-Story Creative Writing | — | 83% |
| EQ-Bench Creative Writing | — | 1366 |
| WildBench | — | 86.6% |
| LiveBench Language | 30.5% | — |
Frequently asked questions
Is Mistral Small better than Qwen3 235B-A22B?
Qwen3 235B-A22B is the stronger model overall, scoring 43.5 to 33.4 on the Noometry Index. Mistral Small costs 4.7× less per token, which makes it the better buy when Qwen3 235B-A22B's lead doesn't matter for your workload.
Which is cheaper, Mistral Small or Qwen3 235B-A22B?
Mistral Small is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Qwen3 235B-A22B lists at $0.70 and $2.80.
Is Mistral Small or Qwen3 235B-A22B better for coding?
Qwen3 235B-A22B scores higher on coding benchmarks: 44.3 versus 34.0 in the Noometry coding category.
Which has the bigger context window?
Mistral Small does, with 262K tokens against 131K.
How many benchmarks do Mistral Small and Qwen3 235B-A22B share?
27 benchmarks have published results for both models. Mistral Small has 39 scored results on Noometry and Qwen3 235B-A22B has 49.