Model comparison
Mixtral 8x7B vs Qwen3 32B
Qwen3 32B is the stronger model overall, scoring 39.2 to 27.1 on the Noometry Index. Mixtral 8x7B costs 1.8× less per token, which makes it the better buy when Qwen3 32B's lead doesn't matter for your workload.
Last verified . 16 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 16 benchmarks with published results for both. Mixtral 8x7B scores higher in 0 categories and Qwen3 32B in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3 32B leads 40.0 to 11.0.
- The biggest single-benchmark swing is GPQA Diamond: 30.6% for Mixtral 8x7B and 65.7% for Qwen3 32B.
- Mixtral 8x7B is cheaper at $0.70 / $0.70 per million input/output tokens, against $0.70 / $2.80 for Qwen3 32B.
- Qwen3 32B accepts more context: 131K tokens versus 32K.
Side by side
| Mixtral 8x7B | Qwen3 32B | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 27.1 | 39.2 |
| Released | 2023-12-11 | 2025-04 |
| Weights | Open | Open |
| Context window | 32K | 131K |
| Max output | 32K | 16K |
| Input $ / M tokens | $0.70 | $0.70 |
| Output $ / M tokens | $0.70 | $2.80 |
| Results tracked | 38 | 26 |
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Category by category
Coding Qwen3 32B leads
Mixtral 8x7B: 32.8 (#269), Qwen3 32B: 37.7 (#190)
| Benchmark | Mixtral 8x7B | Qwen3 32B |
|---|---|---|
| LMArena Coding | 1126 | 1358 |
| Aider Polyglot | — | 40% |
| SciCode | — | 35.4% |
| HumanEval+ | 39.6% | — |
| MBPP+ | 49.7% | — |
Agentic & Tool Use Not comparable
Mixtral 8x7B: —, Qwen3 32B: 32.6 (#62)
| Benchmark | Mixtral 8x7B | Qwen3 32B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 48.7% |
Reasoning Qwen3 32B leads
Mixtral 8x7B: 18.2 (#285), Qwen3 32B: 20.2 (#241)
| Benchmark | Mixtral 8x7B | Qwen3 32B |
|---|---|---|
| LMArena Hard Prompts | 1115 | 1334 |
| DTBench | 49.6% | 67.5% |
| Epoch Capabilities Index | 118.47 | 138.51 |
| Kagi LLM Benchmark | — | 54.9% |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 5% |
| LMCA | — | 17.3% |
| Adversarial NLI | 55.2% | — |
| ForecastBench | 56.3 | — |
| HellaSwag | 86.7% | — |
| PIQA | 83.6% | — |
| WinoGrande | 77.2% | — |
Math Qwen3 32B leads
Mixtral 8x7B: 18.8 (#289), Qwen3 32B: 39.7 (#99)
| Benchmark | Mixtral 8x7B | Qwen3 32B |
|---|---|---|
| LMArena Math | 1147 | 1399 |
| OTIS Mock AIME 2024-2025 | — | 66.9% |
| Omni-MATH | 10.5% | — |
| MATH Level 5 | 10% | — |
| GSM8K | 74.4% | — |
Knowledge Qwen3 32B leads
Mixtral 8x7B: 11.0 (#301), Qwen3 32B: 40.0 (#125)
| Benchmark | Mixtral 8x7B | Qwen3 32B |
|---|---|---|
| GPQA Diamond | 30.6% | 65.7% |
| LMArena Expert | 1088 | 1362 |
| MMLU-Pro | 33.5% | — |
| Vectara Hallucination Rate | — | 5.9% |
| GPQA (HELM) | 29.6% | — |
| ARC (AI2) Challenge | 87.3% | — |
| MMLU | 70.6% | — |
| OpenBookQA | 85.8% | — |
| TriviaQA | 82.2% | — |
Multilingual Qwen3 32B leads
Mixtral 8x7B: 29.6 (#266), Qwen3 32B: 45.6 (#167)
| Benchmark | Mixtral 8x7B | Qwen3 32B |
|---|---|---|
| LMArena Non-English | 1077 | 1317 |
| LMArena Chinese | 1055 | 1357 |
| LMArena German | 1114 | 1341 |
| LMArena Russian | 1090 | 1311 |
| LMArena French | 1166 | — |
| LMArena Japanese | 931 | — |
| LMArena Korean | 968 | — |
| LMArena Spanish | 1111 | — |
Instruction Following Qwen3 32B leads
Mixtral 8x7B: 51.0 (#297), Qwen3 32B: 68.9 (#179)
| Benchmark | Mixtral 8x7B | Qwen3 32B |
|---|---|---|
| LMArena Instruction Following | 1109 | 1305 |
| IFEval | 57.5% | — |
Long Context Qwen3 32B leads
Mixtral 8x7B: 33.4 (#260), Qwen3 32B: 43.8 (#87)
| Benchmark | Mixtral 8x7B | Qwen3 32B |
|---|---|---|
| LMArena Longer Query | 1103 | 1327 |
| Fiction.LiveBench | — | 74.2% |
Writing & Preference Qwen3 32B leads
Mixtral 8x7B: 34.2 (#270), Qwen3 32B: 52.9 (#163)
| Benchmark | Mixtral 8x7B | Qwen3 32B |
|---|---|---|
| LMArena Text | 1132 | 1340 |
| LMArena Creative Writing | 1109 | 1297 |
| LMArena Multi-Turn | 1115 | 1331 |
| WildBench | 67.3% | — |
Frequently asked questions
Is Mixtral 8x7B better than Qwen3 32B?
Qwen3 32B is the stronger model overall, scoring 39.2 to 27.1 on the Noometry Index. Mixtral 8x7B costs 1.8× less per token, which makes it the better buy when Qwen3 32B's lead doesn't matter for your workload.
Which is cheaper, Mixtral 8x7B or Qwen3 32B?
Mixtral 8x7B is cheaper. It lists at $0.70 per million input tokens and $0.70 per million output tokens; Qwen3 32B lists at $0.70 and $2.80.
Is Mixtral 8x7B or Qwen3 32B better for coding?
Qwen3 32B scores higher on coding benchmarks: 37.7 versus 32.8 in the Noometry coding category.
Which has the bigger context window?
Qwen3 32B does, with 131K tokens against 32K.
How many benchmarks do Mixtral 8x7B and Qwen3 32B share?
16 benchmarks have published results for both models. Mixtral 8x7B has 38 scored results on Noometry and Qwen3 32B has 26.