# DeepSeek-V3.2-Speciale vs Mistral Nemo

> DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 25.9 on the Noometry Index. Mistral Nemo costs 5.7× 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-nemo
- 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 Nemo in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.2-Speciale leads 46.1 to 28.6.
- Mistral Nemo is cheaper at $0.15 / $0.15 per million input/output tokens, against $0.58 / $1.68 for DeepSeek-V3.2-Speciale.

## Snapshot

| | DeepSeek-V3.2-Speciale | Mistral Nemo |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 39.1 | 25.9 |
| Rank | 159 | 332 |
| Context | 128K | 128K |
| Input $/M | $0.58 | $0.15 |
| Output $/M | $1.68 | $0.15 |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.2-Speciale: 39.9 (#136)
- Mistral Nemo: —

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Nemo |
|---|---|---|
| WeirdML | 46.7% | — |

## Agentic & Tool Use

- DeepSeek-V3.2-Speciale: —
- Mistral Nemo: 23.3 (#118)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Nemo |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 27.6% |
| BALROG | — | 17.6% |

## Reasoning

- DeepSeek-V3.2-Speciale: 32.1 (#65)
- Mistral Nemo: 19.9 (#230)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Nemo |
|---|---|---|
| SimpleBench | 52.6% | — |
| DTBench | — | 48.6% |
| Epoch Capabilities Index | — | 118.63 |
| PIQA | — | 83.5% |

## Math

- DeepSeek-V3.2-Speciale: —
- Mistral Nemo: 23.5 (#263)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Nemo |
|---|---|---|
| MATH Level 5 | — | 10.8% |
| GSM8K | — | 84.2% |

## Knowledge

- DeepSeek-V3.2-Speciale: —
- Mistral Nemo: 12.3 (#293)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Nemo |
|---|---|---|
| GPQA Diamond | — | 29.9% |
| BoolQ | — | 82.5% |

## Writing & Preference

- DeepSeek-V3.2-Speciale: 46.1 (#217)
- Mistral Nemo: 28.6 (#291)

| Benchmark | DeepSeek-V3.2-Speciale | Mistral Nemo |
|---|---|---|
| EQ-Bench Creative Writing | 1276 | 881 |

## FAQ

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

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 25.9 on the Noometry Index. Mistral Nemo costs 5.7× 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 Nemo?

Mistral Nemo is cheaper. It lists at $0.15 per million input tokens and $0.15 per million output tokens; DeepSeek-V3.2-Speciale lists at $0.58 and $1.68.

### Which has the bigger context window?

Both accept 128K tokens.

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

1 benchmark has published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Mistral Nemo has 10.