# Mixtral 8x7B vs Qwen2.5 32B Instruct

> Qwen2.5 32B Instruct is the stronger model overall, scoring 29.7 to 26.8 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.

- Canonical page: https://noometry.com/compare/mixtral-8x7b-vs-qwen2-5-32b-instruct
- Last updated: 2026-10-10
- Shared benchmarks: 3

## 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.

## Snapshot

| | Mixtral 8x7B | Qwen2.5 32B Instruct |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 26.8 | 29.7 |
| Rank | 328 | 291 |
| Context | 32K | 131K |
| Input $/M | $0.70 | $0.70 |
| Output $/M | $0.70 | $2.80 |
| Weights | Open | Open |

## Coding

- Mixtral 8x7B: 32.2 (#265)
- Qwen2.5 32B Instruct: 38.1 (#165)

| Benchmark | Mixtral 8x7B | Qwen2.5 32B Instruct |
|---|---|---|
| BigCodeBench Instruct | — | 45% |
| LMArena Coding | 1127 | — |
| BigCodeBench Complete | — | 52.3% |
| HumanEval+ | 39.6% | — |
| MBPP+ | 49.7% | — |

## Reasoning

- Mixtral 8x7B: 17.4 (#283)
- Qwen2.5 32B Instruct: 18.5 (#262)

| Benchmark | Mixtral 8x7B | Qwen2.5 32B Instruct |
|---|---|---|
| Epoch Capabilities Index | 118.38 | 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: 17.2 (#284)
- Qwen2.5 32B Instruct: 15.3 (#289)

| 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

- Mixtral 8x7B: 11.0 (#296)
- Qwen2.5 32B Instruct: 24.9 (#259)

| 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

- Mixtral 8x7B: 29.8 (#261)
- Qwen2.5 32B Instruct: —

| Benchmark | Mixtral 8x7B | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Non-English | 1077 | — |
| LMArena Chinese | 1055 | — |
| LMArena French | 1165 | — |
| LMArena German | 1114 | — |
| LMArena Japanese | 931 | — |
| LMArena Korean | 968 | — |
| LMArena Russian | 1090 | — |
| LMArena Spanish | 1110 | — |

## Instruction Following

- Mixtral 8x7B: 51.2 (#292)
- Qwen2.5 32B Instruct: —

| Benchmark | Mixtral 8x7B | Qwen2.5 32B Instruct |
|---|---|---|
| IFEval | 57.5% | — |
| LMArena Instruction Following | 1110 | — |

## Long Context

- Mixtral 8x7B: 33.4 (#255)
- Qwen2.5 32B Instruct: —

| Benchmark | Mixtral 8x7B | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Longer Query | 1103 | — |

## Writing & Preference

- Mixtral 8x7B: 34.4 (#265)
- 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 | — |

## FAQ

### Is Mixtral 8x7B better than Qwen2.5 32B Instruct?

Qwen2.5 32B Instruct is the stronger model overall, scoring 29.7 to 26.8 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: 38.1 versus 32.2 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.