# DeepSeek-V3.2-Speciale vs Mistral Medium

> DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 36.0 on the Noometry Index.

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

## Summary

- They share 1 benchmark with published results for both. DeepSeek-V3.2-Speciale scores higher in 2 categories and Mistral Medium in 1 category; 3 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Mistral Medium leads 60.2 to 46.1.
- DeepSeek-V3.2-Speciale is cheaper at $0.58 / $1.68 per million input/output tokens, against $1.50 / $7.50 for Mistral Medium.
- Mistral Medium accepts more context: 262K tokens versus 128K.

## Snapshot

| | DeepSeek-V3.2-Speciale | Mistral Medium |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 39.1 | 36.0 |
| Rank | 159 | 211 |
| Context | 128K | 262K |
| Input $/M | $0.58 | $1.50 |
| Output $/M | $1.68 | $7.50 |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.2-Speciale: 39.9 (#136)
- Mistral Medium: 33.8 (#241)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Medium |
|---|---|---|
| WeirdML | 46.7% | 43.7% |
| FrontierCode | — | 8% |
| SciCode | — | 40.2% |
| LMArena Coding | — | 1434 |
| ALE-Bench | — | 763.98 |

## Agentic & Tool Use

- DeepSeek-V3.2-Speciale: —
- Mistral Medium: 28.1 (#84)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Medium |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 37.7% |

## Reasoning

- DeepSeek-V3.2-Speciale: 32.1 (#65)
- Mistral Medium: 23.3 (#165)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Medium |
|---|---|---|
| SimpleBench | 52.6% | — |
| Kagi LLM Benchmark | — | 50% |
| CritPt | — | 0% |
| LMArena Hard Prompts | — | 1426 |
| DTBench | — | 75.5% |
| LMCA | — | 26.1% |
| Surface Evolver Bench | — | 26.9% |

## Math

- DeepSeek-V3.2-Speciale: —
- Mistral Medium: 27.2 (#238)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Medium |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 32.2% |
| ProofBench | — | 9% |
| LMArena Math | — | 1409 |
| MATH Level 5 | — | 81.6% |
| FrontierMath (Feb 2025 set) | — | 0.3% |

## Knowledge

- DeepSeek-V3.2-Speciale: —
- Mistral Medium: 24.9 (#260)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Medium |
|---|---|---|
| GPQA Diamond | — | 59.5% |
| Humanity's Last Exam | — | 4.5% |
| Vectara Hallucination Rate | — | 22.7% |
| LMArena Expert | — | 1408 |

## Multimodal

- DeepSeek-V3.2-Speciale: —
- Mistral Medium: 34.6 (#82)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Medium |
|---|---|---|
| LMArena Vision | — | 1172 |

## Multilingual

- DeepSeek-V3.2-Speciale: —
- Mistral Medium: 52.3 (#86)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Medium |
|---|---|---|
| LMArena Non-English | — | 1408 |
| LMArena Chinese | — | 1448 |
| LMArena French | — | 1460 |
| LMArena German | — | 1433 |
| LMArena Japanese | — | 1378 |
| LMArena Korean | — | 1382 |
| LMArena Russian | — | 1411 |
| LMArena Spanish | — | 1433 |

## Instruction Following

- DeepSeek-V3.2-Speciale: —
- Mistral Medium: 73.9 (#111)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Medium |
|---|---|---|
| LMArena Instruction Following | — | 1398 |

## Long Context

- DeepSeek-V3.2-Speciale: —
- Mistral Medium: 42.9 (#108)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Medium |
|---|---|---|
| LMArena Longer Query | — | 1406 |

## Writing & Preference

- DeepSeek-V3.2-Speciale: 46.1 (#217)
- Mistral Medium: 60.2 (#97)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Medium |
|---|---|---|
| LMArena Text | — | 1424 |
| LMArena Creative Writing | — | 1391 |
| Short-Story Creative Writing | — | 77.3% |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 1418 |

## FAQ

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

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 36.0 on the Noometry Index.

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

DeepSeek-V3.2-Speciale is cheaper. It lists at $0.58 per million input tokens and $1.68 per million output tokens; Mistral Medium lists at $1.50 and $7.50.

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

DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 39.9 versus 33.8 in the Noometry coding category.

### Which has the bigger context window?

Mistral Medium does, with 262K tokens against 128K.

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

1 benchmark has published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Mistral Medium has 36.