# DeepSeek-V3.2-Speciale vs Mistral

> DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 29.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-2-speciale-vs-mistral
- Last updated: 2026-10-11
- Shared benchmarks: 0

## Summary

- The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.9 to 22.2.
- DeepSeek-V3.2-Speciale has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-V3.2-Speciale | Mistral |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 39.7 | 29.9 |
| Rank | 162 | 303 |
| Context | 128K | — |
| Input $/M | $0.58 | — |
| Output $/M | $1.68 | — |
| Weights | Open | Proprietary |

## Coding

- DeepSeek-V3.2-Speciale: 40.4 (#140)
- Mistral: 33.8 (#250)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral |
|---|---|---|
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1162 |

## Reasoning

- DeepSeek-V3.2-Speciale: 32.9 (#73)
- Mistral: 22.2 (#200)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral |
|---|---|---|
| SimpleBench | 52.6% | — |
| LMArena Hard Prompts | — | 1149 |

## Math

- DeepSeek-V3.2-Speciale: —
- Mistral: 22.3 (#278)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral |
|---|---|---|
| Omni-MATH | — | 7.2% |
| LMArena Math | — | 1180 |

## Knowledge

- DeepSeek-V3.2-Speciale: —
- Mistral: 16.6 (#288)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral |
|---|---|---|
| MMLU-Pro | — | 27.7% |
| GPQA (HELM) | — | 30.3% |
| LMArena Expert | — | 1125 |

## Multilingual

- DeepSeek-V3.2-Speciale: —
- Mistral: 32.8 (#254)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral |
|---|---|---|
| LMArena Non-English | — | 1129 |
| LMArena Chinese | — | 1109 |
| LMArena French | — | 1180 |
| LMArena German | — | 1155 |
| LMArena Japanese | — | 1013 |
| LMArena Korean | — | 1032 |
| LMArena Russian | — | 1168 |
| LMArena Spanish | — | 1143 |

## Instruction Following

- DeepSeek-V3.2-Speciale: —
- Mistral: 52.6 (#288)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral |
|---|---|---|
| IFEval | — | 56.8% |
| LMArena Instruction Following | — | 1152 |

## Long Context

- DeepSeek-V3.2-Speciale: —
- Mistral: 35.0 (#245)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral |
|---|---|---|
| LMArena Longer Query | — | 1153 |

## Writing & Preference

- DeepSeek-V3.2-Speciale: 46.0 (#222)
- Mistral: 37.0 (#260)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral |
|---|---|---|
| LMArena Text | — | 1165 |
| LMArena Creative Writing | — | 1158 |
| EQ-Bench Creative Writing | 1276 | — |
| WildBench | — | 66% |
| LMArena Multi-Turn | — | 1147 |

## FAQ

### Is DeepSeek-V3.2-Speciale better than Mistral?

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 29.9 on the Noometry Index.

### Is DeepSeek-V3.2-Speciale or Mistral better for coding?

DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 40.4 versus 33.8 in the Noometry coding category.

### How many benchmarks do DeepSeek-V3.2-Speciale and Mistral share?

0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Mistral has 22.