# Mistral Large vs Qwen2.5 7B Instruct

> Mistral Large is the stronger model overall, scoring 31.9 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 Large's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/mistral-large-vs-qwen2-5-7b-instruct
- Last updated: 2026-10-11
- Shared benchmarks: 13

## Summary

- They share 13 benchmarks with published results for both. Mistral Large scores higher in 5 categories and Qwen2.5 7B Instruct in 2 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Mistral Large leads 30.1 to 17.0.
- The biggest single-benchmark swing is DTBench: 65.1% for Mistral Large and 47.7% for Qwen2.5 7B Instruct.
- Qwen2.5 7B Instruct is cheaper at $0.17 / $0.70 per million input/output tokens, against $2 / $6 for Mistral Large.

## Snapshot

| | Mistral Large | Qwen2.5 7B Instruct |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 31.9 | 29.0 |
| Rank | 263 | 320 |
| Context | 131K | 131K |
| Input $/M | $2 | $0.17 |
| Output $/M | $6 | $0.70 |
| Weights | Open | Open |

## Coding

- Mistral Large: 34.3 (#240)
- Qwen2.5 7B Instruct: 36.5 (#208)

| Benchmark | Mistral Large | Qwen2.5 7B Instruct |
|---|---|---|
| BigCodeBench Instruct | 30% | 37.6% |
| BigCodeBench Complete | 38.3% | 46.1% |
| SciCode | 36.2% | — |
| LiveBench Coding | 47.1% | — |
| LMArena Coding | 1277 | — |
| ALE-Bench | 264.7 | — |
| HumanEval+ | 62.2% | — |
| MBPP+ | 59.5% | — |

## Agentic & Tool Use

- Mistral Large: 28.6 (#89)
- Qwen2.5 7B Instruct: 23.8 (#124)

| Benchmark | Mistral Large | Qwen2.5 7B Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | 38.4% | — |
| BALROG | — | 7.8% |

## Reasoning

- Mistral Large: 15.8 (#310)
- Qwen2.5 7B Instruct: 14.8 (#322)

| Benchmark | Mistral Large | Qwen2.5 7B Instruct |
|---|---|---|
| DTBench | 65.1% | 47.7% |
| LMCA | 16.7% | 6.4% |
| Epoch Capabilities Index | 128.52 | 118.51 |
| SimpleBench | 22.5% | — |
| CritPt | 0% | — |
| Chess Puzzles | — | 0% |
| LiveBench Reasoning | 43.5% | — |
| LMArena Hard Prompts | 1257 | — |
| LiveBench Data Analysis | 50.1% | — |
| ForecastBench | 57.1 | — |
| LiveBench | 48.4% | — |

## Math

- Mistral Large: 18.2 (#291)
- Qwen2.5 7B Instruct: 12.6 (#306)

| Benchmark | Mistral Large | Qwen2.5 7B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 8.5% | 2.5% |
| Omni-MATH | 28.1% | 29.4% |
| LiveBench Math | 42.5% | — |
| LMArena Math | 1262 | — |
| MATH Level 5 | 50.3% | — |
| FrontierMath (Feb 2025 set) | 0.3% | — |

## Knowledge

- Mistral Large: 30.1 (#230)
- Qwen2.5 7B Instruct: 17.0 (#286)

| Benchmark | Mistral Large | Qwen2.5 7B Instruct |
|---|---|---|
| GPQA Diamond | 51.3% | 35.5% |
| MMLU-Pro | 59.9% | 53.9% |
| GPQA (HELM) | 43.5% | 34.1% |
| MMLU | 80% | 72.9% |
| Confabulations | 21.4% | — |
| Vectara Hallucination Rate | 4.5% | — |
| LMArena Expert | 1232 | — |

## Multilingual

- Mistral Large: 40.0 (#219)
- Qwen2.5 7B Instruct: —

| Benchmark | Mistral Large | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Non-English | 1237 | — |
| LMArena Chinese | 1240 | — |
| LMArena French | 1325 | — |
| LMArena German | 1254 | — |
| LMArena Japanese | 1188 | — |
| LMArena Korean | 1202 | — |
| LMArena Russian | 1257 | — |
| LMArena Spanish | 1268 | — |

## Instruction Following

- Mistral Large: 67.9 (#191)
- Qwen2.5 7B Instruct: 63.2 (#231)

| Benchmark | Mistral Large | Qwen2.5 7B Instruct |
|---|---|---|
| IFEval | 87.7% | 74.1% |
| LiveBench Instruction Following | 67.9% | — |
| LMArena Instruction Following | 1249 | — |

## Long Context

- Mistral Large: 38.3 (#199)
- Qwen2.5 7B Instruct: —

| Benchmark | Mistral Large | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Longer Query | 1261 | — |

## Writing & Preference

- Mistral Large: 40.7 (#242)
- Qwen2.5 7B Instruct: 48.8 (#195)

| Benchmark | Mistral Large | Qwen2.5 7B Instruct |
|---|---|---|
| WildBench | 80.1% | 73.1% |
| LMArena Text | 1266 | — |
| LMArena Creative Writing | 1243 | — |
| Short-Story Creative Writing | 69% | — |
| EQ-Bench Creative Writing | 985 | — |
| LMArena Multi-Turn | 1260 | — |
| LiveBench Language | 39.4% | — |

## FAQ

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

Mistral Large is the stronger model overall, scoring 31.9 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 Large's lead doesn't matter for your workload.

### Which is cheaper, Mistral Large 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 Large lists at $2 and $6.

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

Qwen2.5 7B Instruct scores higher on coding benchmarks: 36.5 versus 34.3 in the Noometry coding category.

### Which has the bigger context window?

Both accept 131K tokens.

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

13 benchmarks have published results for both models. Mistral Large has 51 scored results on Noometry and Qwen2.5 7B Instruct has 15.