# Mistral Medium vs Qwen2.5 7B Instruct

> Mistral Medium is the stronger model overall, scoring 36.3 to 29.0 on the Noometry Index. Qwen2.5 7B Instruct costs 9.8× less per token, which makes it the better buy when Mistral Medium's lead doesn't matter for your workload.

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

## Summary

- They share 4 benchmarks with published results for both. Mistral Medium scores higher in 6 categories and Qwen2.5 7B Instruct in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where Mistral Medium leads 28.1 to 12.6.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 32.2% for Mistral Medium and 2.5% for Qwen2.5 7B Instruct.
- Qwen2.5 7B Instruct is cheaper at $0.17 / $0.70 per million input/output tokens, against $1.50 / $7.50 for Mistral Medium.
- Mistral Medium accepts more context: 262K tokens versus 131K.

## Snapshot

| | Mistral Medium | Qwen2.5 7B Instruct |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 36.3 | 29.0 |
| Rank | 218 | 320 |
| Context | 262K | 131K |
| Input $/M | $1.50 | $0.17 |
| Output $/M | $7.50 | $0.70 |
| Weights | Open | Open |

## Coding

- Mistral Medium: 34.2 (#243)
- Qwen2.5 7B Instruct: 36.5 (#208)

| Benchmark | Mistral Medium | Qwen2.5 7B Instruct |
|---|---|---|
| FrontierCode | 8% | — |
| SciCode | 40.2% | — |
| WeirdML | 43.7% | — |
| BigCodeBench Instruct | — | 37.6% |
| LMArena Coding | 1434 | — |
| BigCodeBench Complete | — | 46.1% |
| ALE-Bench | 763.98 | — |

## Agentic & Tool Use

- Mistral Medium: 28.3 (#90)
- Qwen2.5 7B Instruct: 23.8 (#124)

| Benchmark | Mistral Medium | Qwen2.5 7B Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | 37.7% | — |
| BALROG | — | 7.8% |

## Reasoning

- Mistral Medium: 24.0 (#167)
- Qwen2.5 7B Instruct: 14.8 (#322)

| Benchmark | Mistral Medium | Qwen2.5 7B Instruct |
|---|---|---|
| DTBench | 75.5% | 47.7% |
| LMCA | 26.1% | 6.4% |
| Kagi LLM Benchmark | 50% | — |
| CritPt | 0% | — |
| Chess Puzzles | — | 0% |
| LMArena Hard Prompts | 1426 | — |
| Surface Evolver Bench | 26.9% | — |
| Epoch Capabilities Index | — | 118.51 |

## Math

- Mistral Medium: 28.1 (#245)
- Qwen2.5 7B Instruct: 12.6 (#306)

| Benchmark | Mistral Medium | Qwen2.5 7B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 32.2% | 2.5% |
| ProofBench | 9% | — |
| Omni-MATH | — | 29.4% |
| LMArena Math | 1408 | — |
| MATH Level 5 | 81.6% | — |
| FrontierMath (Feb 2025 set) | 0.3% | — |

## Knowledge

- Mistral Medium: 25.0 (#265)
- Qwen2.5 7B Instruct: 17.0 (#286)

| Benchmark | Mistral Medium | Qwen2.5 7B Instruct |
|---|---|---|
| GPQA Diamond | 59.5% | 35.5% |
| Humanity's Last Exam | 4.5% | — |
| MMLU-Pro | — | 53.9% |
| Vectara Hallucination Rate | 22.7% | — |
| GPQA (HELM) | — | 34.1% |
| LMArena Expert | 1408 | — |
| MMLU | — | 72.9% |

## Multimodal

- Mistral Medium: 35.3 (#88)
- Qwen2.5 7B Instruct: —

| Benchmark | Mistral Medium | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Vision | 1172 | — |

## Multilingual

- Mistral Medium: 52.1 (#91)
- Qwen2.5 7B Instruct: —

| Benchmark | Mistral Medium | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Non-English | 1408 | — |
| LMArena Chinese | 1447 | — |
| LMArena French | 1459 | — |
| LMArena German | 1432 | — |
| LMArena Japanese | 1378 | — |
| LMArena Korean | 1380 | — |
| LMArena Russian | 1411 | — |
| LMArena Spanish | 1433 | — |

## Instruction Following

- Mistral Medium: 73.7 (#116)
- Qwen2.5 7B Instruct: 63.2 (#231)

| Benchmark | Mistral Medium | Qwen2.5 7B Instruct |
|---|---|---|
| IFEval | — | 74.1% |
| LMArena Instruction Following | 1398 | — |

## Long Context

- Mistral Medium: 42.9 (#114)
- Qwen2.5 7B Instruct: —

| Benchmark | Mistral Medium | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Longer Query | 1406 | — |

## Writing & Preference

- Mistral Medium: 60.0 (#103)
- Qwen2.5 7B Instruct: 48.8 (#195)

| Benchmark | Mistral Medium | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Text | 1424 | — |
| LMArena Creative Writing | 1391 | — |
| Short-Story Creative Writing | 77.3% | — |
| WildBench | — | 73.1% |
| LMArena Multi-Turn | 1418 | — |

## FAQ

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

Mistral Medium is the stronger model overall, scoring 36.3 to 29.0 on the Noometry Index. Qwen2.5 7B Instruct costs 9.8× less per token, which makes it the better buy when Mistral Medium's lead doesn't matter for your workload.

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

Qwen2.5 7B Instruct is cheaper. It lists at $0.17 per million input tokens and $0.70 per million output tokens; Mistral Medium lists at $1.50 and $7.50.

### Is Mistral Medium or Qwen2.5 7B Instruct better for coding?

Qwen2.5 7B Instruct scores higher on coding benchmarks: 36.5 versus 34.2 in the Noometry coding category.

### Which has the bigger context window?

Mistral Medium does, with 262K tokens against 131K.

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

4 benchmarks have published results for both models. Mistral Medium has 36 scored results on Noometry and Qwen2.5 7B Instruct has 15.