# DeepSeek-V3.2-Speciale vs Mistral Small 3.1

> DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 31.7 on the Noometry Index. Mistral Small 3.1 costs 2.1× less per token, which makes it the better buy when DeepSeek-V3.2-Speciale's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/deepseek-v3-2-speciale-vs-mistral-small-3-1
- Last updated: 2026-10-12
- Shared benchmarks: 1

## Summary

- They share 1 benchmark with published results for both. DeepSeek-V3.2-Speciale scores higher in 3 categories and Mistral Small 3.1 in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.9 to 19.7.
- Mistral Small 3.1 is cheaper at $0.35 / $0.56 per million input/output tokens, against $0.58 / $1.68 for DeepSeek-V3.2-Speciale.

## Snapshot

| | DeepSeek-V3.2-Speciale | Mistral Small 3.1 |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 39.7 | 31.7 |
| Rank | 162 | 269 |
| Context | 128K | 128K |
| Input $/M | $0.58 | $0.35 |
| Output $/M | $1.68 | $0.56 |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.2-Speciale: 40.4 (#140)
- Mistral Small 3.1: 38.3 (#179)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Small 3.1 |
|---|---|---|
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1309 |

## Reasoning

- DeepSeek-V3.2-Speciale: 32.9 (#73)
- Mistral Small 3.1: 19.7 (#254)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Small 3.1 |
|---|---|---|
| SimpleBench | 52.6% | — |
| Chess Puzzles | — | 1% |
| LMArena Hard Prompts | — | 1278 |
| Epoch Capabilities Index | — | 127.48 |

## Math

- DeepSeek-V3.2-Speciale: —
- Mistral Small 3.1: 14.7 (#301)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Small 3.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 3.9% |
| Omni-MATH | — | 24.8% |
| LMArena Math | — | 1262 |

## Knowledge

- DeepSeek-V3.2-Speciale: —
- Mistral Small 3.1: 22.6 (#271)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Small 3.1 |
|---|---|---|
| GPQA Diamond | — | 41.9% |
| MMLU-Pro | — | 61% |
| GPQA (HELM) | — | 39.2% |
| LMArena Expert | — | 1257 |

## Multimodal

- DeepSeek-V3.2-Speciale: —
- Mistral Small 3.1: 33.2 (#99)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Small 3.1 |
|---|---|---|
| LMArena Vision | — | 1136 |

## Multilingual

- DeepSeek-V3.2-Speciale: —
- Mistral Small 3.1: 41.2 (#209)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Small 3.1 |
|---|---|---|
| LMArena Non-English | — | 1255 |
| LMArena Chinese | — | 1253 |
| LMArena French | — | 1273 |
| LMArena German | — | 1266 |
| LMArena Japanese | — | 1208 |
| LMArena Korean | — | 1206 |
| LMArena Russian | — | 1263 |
| LMArena Spanish | — | 1283 |

## Instruction Following

- DeepSeek-V3.2-Speciale: —
- Mistral Small 3.1: 63.6 (#230)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Small 3.1 |
|---|---|---|
| IFEval | — | 75% |
| LMArena Instruction Following | — | 1264 |

## Long Context

- DeepSeek-V3.2-Speciale: —
- Mistral Small 3.1: 39.5 (#178)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Small 3.1 |
|---|---|---|
| LMArena Longer Query | — | 1299 |

## Writing & Preference

- DeepSeek-V3.2-Speciale: 46.0 (#222)
- Mistral Small 3.1: 37.0 (#259)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Small 3.1 |
|---|---|---|
| EQ-Bench Creative Writing | 1276 | 761 |
| LMArena Text | — | 1277 |
| LMArena Creative Writing | — | 1253 |
| WildBench | — | 78.8% |
| LMArena Multi-Turn | — | 1270 |

## FAQ

### Is DeepSeek-V3.2-Speciale better than Mistral Small 3.1?

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 31.7 on the Noometry Index. Mistral Small 3.1 costs 2.1× less per token, which makes it the better buy when DeepSeek-V3.2-Speciale's lead doesn't matter for your workload.

### Which is cheaper, DeepSeek-V3.2-Speciale or Mistral Small 3.1?

Mistral Small 3.1 is cheaper. It lists at $0.35 per million input tokens and $0.56 per million output tokens; DeepSeek-V3.2-Speciale lists at $0.58 and $1.68.

### Is DeepSeek-V3.2-Speciale or Mistral Small 3.1 better for coding?

DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 40.4 versus 38.3 in the Noometry coding category.

### Which has the bigger context window?

Both accept 128K tokens.

### How many benchmarks do DeepSeek-V3.2-Speciale and Mistral Small 3.1 share?

1 benchmark has published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Mistral Small 3.1 has 28.