Model comparison
Mixtral 8x7B vs Qwen2.5 32B Instruct
Qwen2.5 32B Instruct is the stronger model overall, scoring 30.1 to 27.1 on the Noometry Index. Mixtral 8x7B costs 1.8× less per token, which makes it the better buy when Qwen2.5 32B Instruct's lead doesn't matter for your workload.
Last verified . 3 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both. Mixtral 8x7B scores higher in 1 category and Qwen2.5 32B Instruct in 3 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen2.5 32B Instruct leads 24.9 to 11.0.
- The biggest single-benchmark swing is MATH Level 5: 10% for Mixtral 8x7B and 56.1% for Qwen2.5 32B Instruct.
- Mixtral 8x7B is cheaper at $0.70 / $0.70 per million input/output tokens, against $0.70 / $2.80 for Qwen2.5 32B Instruct.
- Qwen2.5 32B Instruct accepts more context: 131K tokens versus 32K.
Side by side
| Mixtral 8x7B | Qwen2.5 32B Instruct | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 27.1 | 30.1 |
| Released | 2023-12-11 | 2024-09 |
| Weights | Open | Open |
| Context window | 32K | 131K |
| Max output | 32K | 8K |
| Input $ / M tokens | $0.70 | $0.70 |
| Output $ / M tokens | $0.70 | $2.80 |
| Results tracked | 38 | 7 |
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Category by category
Coding Qwen2.5 32B Instruct leads
Mixtral 8x7B: 32.8 (#269), Qwen2.5 32B Instruct: 38.7 (#169)
| Benchmark | Mixtral 8x7B | Qwen2.5 32B Instruct |
|---|---|---|
| BigCodeBench Instruct | — | 45% |
| LMArena Coding | 1126 | — |
| BigCodeBench Complete | — | 52.3% |
| HumanEval+ | 39.6% | — |
| MBPP+ | 49.7% | — |
Reasoning Qwen2.5 32B Instruct leads
Mixtral 8x7B: 18.2 (#285), Qwen2.5 32B Instruct: 19.2 (#266)
| Benchmark | Mixtral 8x7B | Qwen2.5 32B Instruct |
|---|---|---|
| Epoch Capabilities Index | 118.47 | 128.52 |
| Chess Puzzles | — | 0% |
| LMArena Hard Prompts | 1115 | — |
| DTBench | 49.6% | — |
| Adversarial NLI | 55.2% | — |
| ForecastBench | 56.3 | — |
| HellaSwag | 86.7% | — |
| PIQA | 83.6% | — |
| WinoGrande | 77.2% | — |
Math Mixtral 8x7B leads
Mixtral 8x7B: 18.8 (#289), Qwen2.5 32B Instruct: 16.2 (#296)
| Benchmark | Mixtral 8x7B | Qwen2.5 32B Instruct |
|---|---|---|
| MATH Level 5 | 10% | 56.1% |
| OTIS Mock AIME 2024-2025 | — | 7.4% |
| Omni-MATH | 10.5% | — |
| LMArena Math | 1147 | — |
| GSM8K | 74.4% | — |
Knowledge Qwen2.5 32B Instruct leads
Mixtral 8x7B: 11.0 (#301), Qwen2.5 32B Instruct: 24.9 (#266)
| Benchmark | Mixtral 8x7B | Qwen2.5 32B Instruct |
|---|---|---|
| GPQA Diamond | 30.6% | 46.1% |
| MMLU-Pro | 33.5% | — |
| GPQA (HELM) | 29.6% | — |
| LMArena Expert | 1088 | — |
| ARC (AI2) Challenge | 87.3% | — |
| MMLU | 70.6% | — |
| OpenBookQA | 85.8% | — |
| TriviaQA | 82.2% | — |
Multilingual Not comparable
Mixtral 8x7B: 29.6 (#266), Qwen2.5 32B Instruct: —
| Benchmark | Mixtral 8x7B | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Non-English | 1077 | — |
| LMArena Chinese | 1055 | — |
| LMArena French | 1166 | — |
| LMArena German | 1114 | — |
| LMArena Japanese | 931 | — |
| LMArena Korean | 968 | — |
| LMArena Russian | 1090 | — |
| LMArena Spanish | 1111 | — |
Instruction Following Not comparable
Mixtral 8x7B: 51.0 (#297), Qwen2.5 32B Instruct: —
| Benchmark | Mixtral 8x7B | Qwen2.5 32B Instruct |
|---|---|---|
| IFEval | 57.5% | — |
| LMArena Instruction Following | 1109 | — |
Long Context Not comparable
Mixtral 8x7B: 33.4 (#260), Qwen2.5 32B Instruct: —
| Benchmark | Mixtral 8x7B | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Longer Query | 1103 | — |
Writing & Preference Not comparable
Mixtral 8x7B: 34.2 (#270), Qwen2.5 32B Instruct: —
| Benchmark | Mixtral 8x7B | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Text | 1132 | — |
| LMArena Creative Writing | 1109 | — |
| WildBench | 67.3% | — |
| LMArena Multi-Turn | 1115 | — |
Frequently asked questions
Is Mixtral 8x7B better than Qwen2.5 32B Instruct?
Qwen2.5 32B Instruct is the stronger model overall, scoring 30.1 to 27.1 on the Noometry Index. Mixtral 8x7B costs 1.8× less per token, which makes it the better buy when Qwen2.5 32B Instruct's lead doesn't matter for your workload.
Which is cheaper, Mixtral 8x7B or Qwen2.5 32B Instruct?
Mixtral 8x7B is cheaper. It lists at $0.70 per million input tokens and $0.70 per million output tokens; Qwen2.5 32B Instruct lists at $0.70 and $2.80.
Is Mixtral 8x7B or Qwen2.5 32B Instruct better for coding?
Qwen2.5 32B Instruct scores higher on coding benchmarks: 38.7 versus 32.8 in the Noometry coding category.
Which has the bigger context window?
Qwen2.5 32B Instruct does, with 131K tokens against 32K.
How many benchmarks do Mixtral 8x7B and Qwen2.5 32B Instruct share?
3 benchmarks have published results for both models. Mixtral 8x7B has 38 scored results on Noometry and Qwen2.5 32B Instruct has 7.