Model comparison
Mixtral 8x22B vs Qwen2.5 32B Instruct
Qwen2.5 32B Instruct is the stronger model overall, scoring 30.1 to 27.1 on the Noometry Index.
Last verified . 5 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 5 benchmarks with published results for both. Mixtral 8x22B scores higher in 2 categories and Qwen2.5 32B Instruct in 2 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in coding, where Qwen2.5 32B Instruct leads 38.7 to 24.2.
- The biggest single-benchmark swing is MATH Level 5: 24.2% for Mixtral 8x22B and 56.1% for Qwen2.5 32B Instruct.
- Qwen2.5 32B Instruct is cheaper at $0.70 / $2.80 per million input/output tokens, against $2 / $6 for Mixtral 8x22B.
- Qwen2.5 32B Instruct accepts more context: 131K tokens versus 64K.
Side by side
| Mixtral 8x22B | Qwen2.5 32B Instruct | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 27.1 | 30.1 |
| Released | 2024-04-17 | 2024-09 |
| Weights | Open | Open |
| Context window | 64K | 131K |
| Max output | 64K | 8K |
| Input $ / M tokens | $2 | $0.70 |
| Output $ / M tokens | $6 | $2.80 |
| Results tracked | 34 | 7 |
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Category by category
Coding Qwen2.5 32B Instruct leads
Mixtral 8x22B: 24.2 (#329), Qwen2.5 32B Instruct: 38.7 (#169)
| Benchmark | Mixtral 8x22B | Qwen2.5 32B Instruct |
|---|---|---|
| BigCodeBench Instruct | 40.6% | 45% |
| BigCodeBench Complete | 50.2% | 52.3% |
| WeirdML | 3.2% | — |
| LMArena Coding | 1166 | — |
| HumanEval+ | 72% | — |
| MBPP+ | 64.3% | — |
Agentic & Tool Use Not comparable
Mixtral 8x22B: 23.1 (#127), Qwen2.5 32B Instruct: —
| Benchmark | Mixtral 8x22B | Qwen2.5 32B Instruct |
|---|---|---|
| Cybench | 7.5% | — |
Reasoning Too close to call
Mixtral 8x22B: 19.9 (#248), Qwen2.5 32B Instruct: 19.2 (#266)
| Benchmark | Mixtral 8x22B | Qwen2.5 32B Instruct |
|---|---|---|
| Epoch Capabilities Index | 122.03 | 128.52 |
| Chess Puzzles | — | 0% |
| LMArena Hard Prompts | 1150 | — |
| DTBench | 55.1% | — |
| ForecastBench | 56.3 | — |
Math Mixtral 8x22B leads
Mixtral 8x22B: 22.9 (#275), Qwen2.5 32B Instruct: 16.2 (#296)
| Benchmark | Mixtral 8x22B | Qwen2.5 32B Instruct |
|---|---|---|
| MATH Level 5 | 24.2% | 56.1% |
| OTIS Mock AIME 2024-2025 | — | 7.4% |
| Omni-MATH | 16.3% | — |
| LMArena Math | 1184 | — |
Knowledge Qwen2.5 32B Instruct leads
Mixtral 8x22B: 15.1 (#293), Qwen2.5 32B Instruct: 24.9 (#266)
| Benchmark | Mixtral 8x22B | Qwen2.5 32B Instruct |
|---|---|---|
| GPQA Diamond | 34.1% | 46.1% |
| MMLU-Pro | 46% | — |
| GPQA (HELM) | 33.4% | — |
| LMArena Expert | 1113 | — |
| MMLU | 77.8% | — |
Multilingual Not comparable
Mixtral 8x22B: 32.8 (#255), Qwen2.5 32B Instruct: —
| Benchmark | Mixtral 8x22B | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Non-English | 1128 | — |
| LMArena Chinese | 1116 | — |
| LMArena French | 1166 | — |
| LMArena German | 1141 | — |
| LMArena Japanese | 1037 | — |
| LMArena Korean | 1057 | — |
| LMArena Russian | 1158 | — |
| LMArena Spanish | 1151 | — |
Instruction Following Not comparable
Mixtral 8x22B: 57.7 (#266), Qwen2.5 32B Instruct: —
| Benchmark | Mixtral 8x22B | Qwen2.5 32B Instruct |
|---|---|---|
| IFEval | 72.4% | — |
| LMArena Instruction Following | 1147 | — |
Long Context Not comparable
Mixtral 8x22B: 34.7 (#247), Qwen2.5 32B Instruct: —
| Benchmark | Mixtral 8x22B | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Longer Query | 1144 | — |
Writing & Preference Not comparable
Mixtral 8x22B: 36.9 (#262), Qwen2.5 32B Instruct: —
| Benchmark | Mixtral 8x22B | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Text | 1162 | — |
| LMArena Creative Writing | 1141 | — |
| WildBench | 71.1% | — |
| LMArena Multi-Turn | 1130 | — |
Frequently asked questions
Is Mixtral 8x22B 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.
Which is cheaper, Mixtral 8x22B or Qwen2.5 32B Instruct?
Qwen2.5 32B Instruct is cheaper. It lists at $0.70 per million input tokens and $2.80 per million output tokens; Mixtral 8x22B lists at $2 and $6.
Is Mixtral 8x22B or Qwen2.5 32B Instruct better for coding?
Qwen2.5 32B Instruct scores higher on coding benchmarks: 38.7 versus 24.2 in the Noometry coding category.
Which has the bigger context window?
Qwen2.5 32B Instruct does, with 131K tokens against 64K.
How many benchmarks do Mixtral 8x22B and Qwen2.5 32B Instruct share?
5 benchmarks have published results for both models. Mixtral 8x22B has 34 scored results on Noometry and Qwen2.5 32B Instruct has 7.