# DeepSeek-V3.1-Terminus vs Mistral Small 3.2

> DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 31.2 on the Noometry Index. Mistral Small 3.2 costs 3.4× less per token, which makes it the better buy when DeepSeek-V3.1-Terminus's lead doesn't matter for your workload.

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

## Summary

- They share 1 benchmark with published results for both. DeepSeek-V3.1-Terminus scores higher in 3 categories and Mistral Small 3.2 in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.1-Terminus leads 61.0 to 45.0.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 57.4% for DeepSeek-V3.1-Terminus and 40.4% for Mistral Small 3.2.
- Mistral Small 3.2 is cheaper at $0.0938 / $0.25 per million input/output tokens, against $0.27 / $1 for DeepSeek-V3.1-Terminus.
- Mistral Small 3.2 accepts more context: 256K tokens versus 164K.

## Snapshot

| | DeepSeek-V3.1-Terminus | Mistral Small 3.2 |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 43.1 | 31.2 |
| Rank | 97 | 280 |
| Context | 164K | 256K |
| Input $/M | $0.27 | $0.0938 |
| Output $/M | $1 | $0.25 |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.1-Terminus: 42.0 (#113)
- Mistral Small 3.2: —

| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small 3.2 |
|---|---|---|
| SciCode | 40.6% | — |
| LMArena Coding | 1426 | — |
| ALE-Bench | 745.17 | — |

## Reasoning

- DeepSeek-V3.1-Terminus: 26.4 (#133)
- Mistral Small 3.2: 18.1 (#287)

| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small 3.2 |
|---|---|---|
| Kagi LLM Benchmark | 57.4% | 40.4% |
| CritPt | 1.7% | — |
| Chess Puzzles | — | 1% |
| LMArena Hard Prompts | 1426 | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
| Epoch Capabilities Index | — | 131.74 |

## Math

- DeepSeek-V3.1-Terminus: 38.5 (#137)
- Mistral Small 3.2: 26.3 (#260)

| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small 3.2 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 30.3% |
| LMArena Math | 1402 | — |

## Knowledge

- DeepSeek-V3.1-Terminus: —
- Mistral Small 3.2: 26.7 (#256)

| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small 3.2 |
|---|---|---|
| GPQA Diamond | — | 49.1% |

## Multilingual

- DeepSeek-V3.1-Terminus: 52.1 (#92)
- Mistral Small 3.2: —

| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small 3.2 |
|---|---|---|
| LMArena Non-English | 1407 | — |
| LMArena Russian | 1436 | — |

## Instruction Following

- DeepSeek-V3.1-Terminus: 74.0 (#106)
- Mistral Small 3.2: —

| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small 3.2 |
|---|---|---|
| LMArena Instruction Following | 1404 | — |

## Long Context

- DeepSeek-V3.1-Terminus: 43.4 (#97)
- Mistral Small 3.2: —

| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small 3.2 |
|---|---|---|
| LMArena Longer Query | 1421 | — |

## Writing & Preference

- DeepSeek-V3.1-Terminus: 61.0 (#92)
- Mistral Small 3.2: 45.0 (#224)

| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small 3.2 |
|---|---|---|
| LMArena Text | 1419 | — |
| LMArena Creative Writing | 1403 | — |
| EQ-Bench Creative Writing | — | 1255 |
| LMArena Multi-Turn | 1411 | — |

## FAQ

### Is DeepSeek-V3.1-Terminus better than Mistral Small 3.2?

DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 31.2 on the Noometry Index. Mistral Small 3.2 costs 3.4× less per token, which makes it the better buy when DeepSeek-V3.1-Terminus's lead doesn't matter for your workload.

### Which is cheaper, DeepSeek-V3.1-Terminus or Mistral Small 3.2?

Mistral Small 3.2 is cheaper. It lists at $0.0938 per million input tokens and $0.25 per million output tokens; DeepSeek-V3.1-Terminus lists at $0.27 and $1.

### Which has the bigger context window?

Mistral Small 3.2 does, with 256K tokens against 164K.

### How many benchmarks do DeepSeek-V3.1-Terminus and Mistral Small 3.2 share?

1 benchmark has published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Mistral Small 3.2 has 6.