# DeepSeek-V2.5 (Sep 2024) vs Mistral Small 3.2

> DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.6 to 31.2 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v2-5-vs-mistral-small-3-2
- Last updated: 2026-10-12
- Shared benchmarks: 0

## Summary

- The widest gap is in math, where DeepSeek-V2.5 (Sep 2024) leads 35.9 to 26.3.

## Snapshot

| | DeepSeek-V2.5 (Sep 2024) | Mistral Small 3.2 |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 37.6 | 31.2 |
| Rank | 200 | 280 |
| Context | — | 256K |
| Input $/M | — | $0.0938 |
| Output $/M | — | $0.25 |
| Weights | Open | Open |

## Coding

- DeepSeek-V2.5 (Sep 2024): 31.7 (#281)
- Mistral Small 3.2: —

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Mistral Small 3.2 |
|---|---|---|
| Aider Polyglot | 17.8% | — |
| BigCodeBench Instruct | 48.6% | — |
| LMArena Coding | 1309 | — |
| BigCodeBench Complete | 53.2% | — |
| HumanEval+ | 83.5% | — |
| MBPP+ | 74.1% | — |

## Reasoning

- DeepSeek-V2.5 (Sep 2024): 25.6 (#145)
- Mistral Small 3.2: 18.1 (#287)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Mistral Small 3.2 |
|---|---|---|
| Kagi LLM Benchmark | — | 40.4% |
| Chess Puzzles | — | 1% |
| LMArena Hard Prompts | 1289 | — |
| Epoch Capabilities Index | — | 131.74 |

## Math

- DeepSeek-V2.5 (Sep 2024): 35.9 (#177)
- Mistral Small 3.2: 26.3 (#260)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Mistral Small 3.2 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 30.3% |
| LMArena Math | 1288 | — |

## Knowledge

- DeepSeek-V2.5 (Sep 2024): 34.8 (#193)
- Mistral Small 3.2: 26.7 (#256)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Mistral Small 3.2 |
|---|---|---|
| GPQA Diamond | — | 49.1% |
| LMArena Expert | 1266 | — |

## Multilingual

- DeepSeek-V2.5 (Sep 2024): 42.5 (#193)
- Mistral Small 3.2: —

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Mistral Small 3.2 |
|---|---|---|
| LMArena Non-English | 1273 | — |
| LMArena Chinese | 1318 | — |
| LMArena French | 1289 | — |
| LMArena German | 1258 | — |
| LMArena Japanese | 1228 | — |
| LMArena Korean | 1209 | — |
| LMArena Russian | 1289 | — |
| LMArena Spanish | 1248 | — |

## Instruction Following

- DeepSeek-V2.5 (Sep 2024): 67.5 (#194)
- Mistral Small 3.2: —

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Mistral Small 3.2 |
|---|---|---|
| LMArena Instruction Following | 1280 | — |

## Long Context

- DeepSeek-V2.5 (Sep 2024): 39.5 (#174)
- Mistral Small 3.2: —

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Mistral Small 3.2 |
|---|---|---|
| LMArena Longer Query | 1301 | — |

## Writing & Preference

- DeepSeek-V2.5 (Sep 2024): 49.8 (#187)
- Mistral Small 3.2: 45.0 (#224)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Mistral Small 3.2 |
|---|---|---|
| LMArena Text | 1294 | — |
| LMArena Creative Writing | 1285 | — |
| EQ-Bench Creative Writing | — | 1255 |
| LMArena Multi-Turn | 1297 | — |

## FAQ

### Is DeepSeek-V2.5 (Sep 2024) better than Mistral Small 3.2?

DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.6 to 31.2 on the Noometry Index.

### How many benchmarks do DeepSeek-V2.5 (Sep 2024) and Mistral Small 3.2 share?

0 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and Mistral Small 3.2 has 6.