# Mistral Small 3.2 vs Qwen2.5 7B Instruct

> Mistral Small 3.2 is the stronger model overall, scoring 31.2 to 29.0 on the Noometry Index.

- Canonical page: https://noometry.com/compare/mistral-small-3-2-vs-qwen2-5-7b-instruct
- Last updated: 2026-10-12
- Shared benchmarks: 4

## Summary

- They share 4 benchmarks with published results for both. Mistral Small 3.2 scores higher in 3 categories and Qwen2.5 7B Instruct in 1 category; 4 gaps are clear of the uncertainty.
- The widest gap is in math, where Mistral Small 3.2 leads 26.3 to 12.6.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 30.3% for Mistral Small 3.2 and 2.5% for Qwen2.5 7B Instruct.
- Mistral Small 3.2 is cheaper at $0.0938 / $0.25 per million input/output tokens, against $0.17 / $0.70 for Qwen2.5 7B Instruct.
- Mistral Small 3.2 accepts more context: 256K tokens versus 131K.

## Snapshot

| | Mistral Small 3.2 | Qwen2.5 7B Instruct |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 31.2 | 29.0 |
| Rank | 280 | 320 |
| Context | 256K | 131K |
| Input $/M | $0.0938 | $0.17 |
| Output $/M | $0.25 | $0.70 |
| Weights | Open | Open |

## Coding

- Mistral Small 3.2: —
- Qwen2.5 7B Instruct: 36.5 (#208)

| Benchmark | Mistral Small 3.2 | Qwen2.5 7B Instruct |
|---|---|---|
| BigCodeBench Instruct | — | 37.6% |
| BigCodeBench Complete | — | 46.1% |

## Agentic & Tool Use

- Mistral Small 3.2: —
- Qwen2.5 7B Instruct: 23.8 (#124)

| Benchmark | Mistral Small 3.2 | Qwen2.5 7B Instruct |
|---|---|---|
| BALROG | — | 7.8% |

## Reasoning

- Mistral Small 3.2: 18.1 (#287)
- Qwen2.5 7B Instruct: 14.8 (#322)

| Benchmark | Mistral Small 3.2 | Qwen2.5 7B Instruct |
|---|---|---|
| Chess Puzzles | 1% | 0% |
| Epoch Capabilities Index | 131.74 | 118.51 |
| Kagi LLM Benchmark | 40.4% | — |
| DTBench | — | 47.7% |
| LMCA | — | 6.4% |

## Math

- Mistral Small 3.2: 26.3 (#260)
- Qwen2.5 7B Instruct: 12.6 (#306)

| Benchmark | Mistral Small 3.2 | Qwen2.5 7B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 30.3% | 2.5% |
| Omni-MATH | — | 29.4% |

## Knowledge

- Mistral Small 3.2: 26.7 (#256)
- Qwen2.5 7B Instruct: 17.0 (#286)

| Benchmark | Mistral Small 3.2 | Qwen2.5 7B Instruct |
|---|---|---|
| GPQA Diamond | 49.1% | 35.5% |
| MMLU-Pro | — | 53.9% |
| GPQA (HELM) | — | 34.1% |
| MMLU | — | 72.9% |

## Instruction Following

- Mistral Small 3.2: —
- Qwen2.5 7B Instruct: 63.2 (#231)

| Benchmark | Mistral Small 3.2 | Qwen2.5 7B Instruct |
|---|---|---|
| IFEval | — | 74.1% |

## Writing & Preference

- Mistral Small 3.2: 45.0 (#224)
- Qwen2.5 7B Instruct: 48.8 (#195)

| Benchmark | Mistral Small 3.2 | Qwen2.5 7B Instruct |
|---|---|---|
| EQ-Bench Creative Writing | 1255 | — |
| WildBench | — | 73.1% |

## FAQ

### Is Mistral Small 3.2 better than Qwen2.5 7B Instruct?

Mistral Small 3.2 is the stronger model overall, scoring 31.2 to 29.0 on the Noometry Index.

### Which is cheaper, Mistral Small 3.2 or Qwen2.5 7B Instruct?

Mistral Small 3.2 is cheaper. It lists at $0.0938 per million input tokens and $0.25 per million output tokens; Qwen2.5 7B Instruct lists at $0.17 and $0.70.

### Which has the bigger context window?

Mistral Small 3.2 does, with 256K tokens against 131K.

### How many benchmarks do Mistral Small 3.2 and Qwen2.5 7B Instruct share?

4 benchmarks have published results for both models. Mistral Small 3.2 has 6 scored results on Noometry and Qwen2.5 7B Instruct has 15.