# DeepSeek-V3 vs Mistral Large

> DeepSeek-V3 is the stronger model overall, scoring 39.2 to 31.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-vs-mistral-large
- Last updated: 2026-10-10
- Shared benchmarks: 49

## Summary

- They share 49 benchmarks with published results for both. DeepSeek-V3 scores higher in 7 categories and Mistral Large in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3 leads 57.6 to 40.9.
- The biggest single-benchmark swing is LiveBench Math: 73.5% for DeepSeek-V3 and 42.5% for Mistral Large.
- DeepSeek-V3 is cheaper at $0.24 / $0.90 per million input/output tokens, against $2 / $6 for Mistral Large.
- DeepSeek-V3 accepts more context: 164K tokens versus 131K.

## Snapshot

| | DeepSeek-V3 | Mistral Large |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 39.2 | 31.6 |
| Rank | 157 | 258 |
| Context | 164K | 131K |
| Input $/M | $0.24 | $2 |
| Output $/M | $0.90 | $6 |
| Weights | Open | Open |

## Coding

- DeepSeek-V3: 41.9 (#99)
- Mistral Large: 33.8 (#240)

| Benchmark | DeepSeek-V3 | Mistral Large |
|---|---|---|
| SciCode | 35.8% | 36.2% |
| BigCodeBench Instruct | 50% | 30% |
| LiveBench Coding | 70.9% | 47.1% |
| LMArena Coding | 1368 | 1277 |
| BigCodeBench Complete | 62.2% | 38.3% |
| HumanEval+ | 86.6% | 62.2% |
| MBPP+ | 73% | 59.5% |
| Aider Polyglot | 55.1% | — |
| WeirdML | 36.1% | — |
| ALE-Bench | — | 264.7 |

## Agentic & Tool Use

- DeepSeek-V3: —
- Mistral Large: 28.4 (#83)

| Benchmark | DeepSeek-V3 | Mistral Large |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 38.4% |
| METR Time Horizons | 49.6% | — |

## Reasoning

- DeepSeek-V3: 20.0 (#226)
- Mistral Large: 15.4 (#305)

| Benchmark | DeepSeek-V3 | Mistral Large |
|---|---|---|
| SimpleBench | 27.2% | 22.5% |
| CritPt | 0% | 0% |
| LiveBench Reasoning | 65.8% | 43.5% |
| LMArena Hard Prompts | 1365 | 1257 |
| DTBench | 64.8% | 65.1% |
| LiveBench Data Analysis | 60.9% | 50.1% |
| LMCA | 15.5% | 16.7% |
| Epoch Capabilities Index | 135.95 | 128.52 |
| ForecastBench | 59.1 | 57.1 |
| LiveBench | 66.9% | 48.4% |
| Kagi LLM Benchmark | 52.3% | — |
| BIG-Bench Hard | 87.5% | — |
| HellaSwag | 88.9% | — |
| PIQA | 84.7% | — |
| WinoGrande | 85.2% | — |

## Math

- DeepSeek-V3: 30.4 (#208)
- Mistral Large: 17.1 (#285)

| Benchmark | DeepSeek-V3 | Mistral Large |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 37.8% | 8.5% |
| Omni-MATH | 40.3% | 28.1% |
| LiveBench Math | 73.5% | 42.5% |
| LMArena Math | 1373 | 1262 |
| MATH Level 5 | 75.5% | 50.3% |
| FrontierMath (Feb 2025 set) | 1.7% | 0.3% |

## Knowledge

- DeepSeek-V3: 37.5 (#147)
- Mistral Large: 30.0 (#224)

| Benchmark | DeepSeek-V3 | Mistral Large |
|---|---|---|
| GPQA Diamond | 67.6% | 51.3% |
| MMLU-Pro | 72.3% | 59.9% |
| Confabulations | 26.1% | 21.4% |
| Vectara Hallucination Rate | 6.1% | 4.5% |
| GPQA (HELM) | 53.8% | 43.5% |
| LMArena Expert | 1352 | 1232 |
| MMLU | 87.2% | 80% |
| ARC (AI2) Challenge | 95.3% | — |
| TriviaQA | 82.9% | — |

## Multilingual

- DeepSeek-V3: 48.8 (#138)
- Mistral Large: 40.1 (#214)

| Benchmark | DeepSeek-V3 | Mistral Large |
|---|---|---|
| LMArena Non-English | 1358 | 1237 |
| LMArena Chinese | 1390 | 1240 |
| LMArena French | 1386 | 1324 |
| LMArena German | 1374 | 1254 |
| LMArena Japanese | 1333 | 1187 |
| LMArena Korean | 1321 | 1202 |
| LMArena Russian | 1372 | 1257 |
| LMArena Spanish | 1358 | 1268 |

## Instruction Following

- DeepSeek-V3: 73.0 (#125)
- Mistral Large: 68.1 (#186)

| Benchmark | DeepSeek-V3 | Mistral Large |
|---|---|---|
| LiveBench Instruction Following | 81.5% | 67.9% |
| IFEval | 83.2% | 87.7% |
| LMArena Instruction Following | 1345 | 1249 |

## Long Context

- DeepSeek-V3: 34.0 (#248)
- Mistral Large: 38.3 (#194)

| Benchmark | DeepSeek-V3 | Mistral Large |
|---|---|---|
| LMArena Longer Query | 1353 | 1262 |
| Fiction.LiveBench | 50% | — |

## Writing & Preference

- DeepSeek-V3: 57.6 (#124)
- Mistral Large: 40.9 (#237)

| Benchmark | DeepSeek-V3 | Mistral Large |
|---|---|---|
| LMArena Text | 1375 | 1266 |
| LMArena Creative Writing | 1364 | 1243 |
| Short-Story Creative Writing | 77% | 69% |
| EQ-Bench Creative Writing | 1472 | 985 |
| WildBench | 83% | 80.1% |
| LMArena Multi-Turn | 1389 | 1260 |
| LiveBench Language | 49.1% | 39.4% |

## FAQ

### Is DeepSeek-V3 better than Mistral Large?

DeepSeek-V3 is the stronger model overall, scoring 39.2 to 31.6 on the Noometry Index.

### Which is cheaper, DeepSeek-V3 or Mistral Large?

DeepSeek-V3 is cheaper. It lists at $0.24 per million input tokens and $0.90 per million output tokens; Mistral Large lists at $2 and $6.

### Is DeepSeek-V3 or Mistral Large better for coding?

DeepSeek-V3 scores higher on coding benchmarks: 41.9 versus 33.8 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek-V3 does, with 164K tokens against 131K.

### How many benchmarks do DeepSeek-V3 and Mistral Large share?

49 benchmarks have published results for both models. DeepSeek-V3 has 60 scored results on Noometry and Mistral Large has 51.