# DeepSeek V4 Pro vs Mistral Small 3.1

> DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 31.7 on the Noometry Index. Mistral Small 3.1 costs 2.5× less per token, which makes it the better buy when DeepSeek V4 Pro's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/deepseek-v4-pro-vs-mistral-small-3-1
- Last updated: 2026-10-12
- Shared benchmarks: 22

## Summary

- They share 22 benchmarks with published results for both. DeepSeek V4 Pro scores higher in 8 categories and Mistral Small 3.1 in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where DeepSeek V4 Pro leads 64.8 to 14.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 98.6% for DeepSeek V4 Pro and 3.9% for Mistral Small 3.1.
- Mistral Small 3.1 is cheaper at $0.35 / $0.56 per million input/output tokens, against $0.66 / $1.98 for DeepSeek V4 Pro.
- DeepSeek V4 Pro accepts more context: 1M tokens versus 128K.

## Snapshot

| | DeepSeek V4 Pro | Mistral Small 3.1 |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 54.3 | 31.7 |
| Rank | 31 | 269 |
| Context | 1M | 128K |
| Input $/M | $0.66 | $0.35 |
| Output $/M | $1.98 | $0.56 |
| Weights | Open | Open |

## Coding

- DeepSeek V4 Pro: 52.4 (#34)
- Mistral Small 3.1: 38.3 (#179)

| Benchmark | DeepSeek V4 Pro | Mistral Small 3.1 |
|---|---|---|
| LMArena Coding | 1470 | 1309 |
| SWE-bench Verified | 77.6% | — |
| FrontierCode | 28.6% | — |
| LMArena WebDev | 1582 | — |
| SciCode | 51% | — |
| WeirdML | 66.2% | — |
| ALE-Bench | 1,403 | — |

## Agentic & Tool Use

- DeepSeek V4 Pro: 32.8 (#58)
- Mistral Small 3.1: —

| Benchmark | DeepSeek V4 Pro | Mistral Small 3.1 |
|---|---|---|
| APEX-Agents | 47.3% | — |
| Vending-Bench 2 | 3,285 | — |

## Reasoning

- DeepSeek V4 Pro: 56.5 (#24)
- Mistral Small 3.1: 19.7 (#254)

| Benchmark | DeepSeek V4 Pro | Mistral Small 3.1 |
|---|---|---|
| Chess Puzzles | 47% | 1% |
| LMArena Hard Prompts | 1461 | 1278 |
| Epoch Capabilities Index | 155.31 | 127.48 |
| ARC-AGI-2 | 61.3% | — |
| Kagi LLM Benchmark | 53.5% | — |
| NYT Connections (extended) | 91.3% | — |
| ARC-AGI-1 | 90.5% | — |
| CritPt | 18% | — |
| Mystery Game Puzzles | 43% | — |
| DTBench | 93.9% | — |
| LMCA | 45.5% | — |
| Surface Evolver Bench | 40% | — |
| ForecastBench | 56.1 | — |

## Math

- DeepSeek V4 Pro: 64.8 (#30)
- Mistral Small 3.1: 14.7 (#301)

| Benchmark | DeepSeek V4 Pro | Mistral Small 3.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 98.6% | 3.9% |
| LMArena Math | 1455 | 1262 |
| FrontierMath (Tiers 1-3) | 64.6% | — |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 76.6% | — |
| ProofBench | 50% | — |
| Omni-MATH | — | 24.8% |

## Knowledge

- DeepSeek V4 Pro: 59.5 (#31)
- Mistral Small 3.1: 22.6 (#271)

| Benchmark | DeepSeek V4 Pro | Mistral Small 3.1 |
|---|---|---|
| GPQA Diamond | 91.7% | 41.9% |
| LMArena Expert | 1464 | 1257 |
| SimpleQA Verified | 52.9% | — |
| MMLU-Pro | — | 61% |
| Vectara Hallucination Rate | 8.6% | — |
| GPQA (HELM) | — | 39.2% |

## Multimodal

- DeepSeek V4 Pro: —
- Mistral Small 3.1: 33.2 (#99)

| Benchmark | DeepSeek V4 Pro | Mistral Small 3.1 |
|---|---|---|
| LMArena Vision | — | 1136 |

## Multilingual

- DeepSeek V4 Pro: 54.4 (#45)
- Mistral Small 3.1: 41.2 (#209)

| Benchmark | DeepSeek V4 Pro | Mistral Small 3.1 |
|---|---|---|
| LMArena Non-English | 1439 | 1255 |
| LMArena Chinese | 1486 | 1253 |
| LMArena French | 1472 | 1273 |
| LMArena German | 1458 | 1266 |
| LMArena Japanese | 1445 | 1208 |
| LMArena Korean | 1447 | 1206 |
| LMArena Russian | 1453 | 1263 |
| LMArena Spanish | 1458 | 1283 |

## Instruction Following

- DeepSeek V4 Pro: 76.1 (#47)
- Mistral Small 3.1: 63.6 (#230)

| Benchmark | DeepSeek V4 Pro | Mistral Small 3.1 |
|---|---|---|
| LMArena Instruction Following | 1448 | 1264 |
| IFEval | — | 75% |

## Long Context

- DeepSeek V4 Pro: 45.0 (#51)
- Mistral Small 3.1: 39.5 (#178)

| Benchmark | DeepSeek V4 Pro | Mistral Small 3.1 |
|---|---|---|
| LMArena Longer Query | 1458 | 1299 |
| CL-bench Life | 13.5% | — |

## Writing & Preference

- DeepSeek V4 Pro: 65.5 (#46)
- Mistral Small 3.1: 37.0 (#259)

| Benchmark | DeepSeek V4 Pro | Mistral Small 3.1 |
|---|---|---|
| LMArena Text | 1451 | 1277 |
| LMArena Creative Writing | 1446 | 1253 |
| EQ-Bench Creative Writing | 1553 | 761 |
| LMArena Multi-Turn | 1467 | 1270 |
| WildBench | — | 78.8% |
| EQ-Bench 4 | 1166 | — |

## FAQ

### Is DeepSeek V4 Pro better than Mistral Small 3.1?

DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 31.7 on the Noometry Index. Mistral Small 3.1 costs 2.5× less per token, which makes it the better buy when DeepSeek V4 Pro's lead doesn't matter for your workload.

### Which is cheaper, DeepSeek V4 Pro 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 V4 Pro lists at $0.66 and $1.98.

### Is DeepSeek V4 Pro or Mistral Small 3.1 better for coding?

DeepSeek V4 Pro scores higher on coding benchmarks: 52.4 versus 38.3 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek V4 Pro does, with 1M tokens against 128K.

### How many benchmarks do DeepSeek V4 Pro and Mistral Small 3.1 share?

22 benchmarks have published results for both models. DeepSeek V4 Pro has 48 scored results on Noometry and Mistral Small 3.1 has 28.