# DeepSeek V4 Pro vs Mistral Large

> DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 31.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v4-pro-vs-mistral-large
- Last updated: 2026-10-11
- Shared benchmarks: 28

## Summary

- They share 28 benchmarks with published results for both. DeepSeek V4 Pro scores higher in 9 categories and Mistral Large in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where DeepSeek V4 Pro leads 64.8 to 18.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 98.6% for DeepSeek V4 Pro and 8.5% for Mistral Large.
- DeepSeek V4 Pro is cheaper at $0.66 / $1.98 per million input/output tokens, against $2 / $6 for Mistral Large.
- DeepSeek V4 Pro accepts more context: 1M tokens versus 131K.

## Snapshot

| | DeepSeek V4 Pro | Mistral Large |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 54.3 | 31.9 |
| Rank | 31 | 263 |
| Context | 1M | 131K |
| Input $/M | $0.66 | $2 |
| Output $/M | $1.98 | $6 |
| Weights | Open | Open |

## Coding

- DeepSeek V4 Pro: 52.4 (#34)
- Mistral Large: 34.3 (#240)

| Benchmark | DeepSeek V4 Pro | Mistral Large |
|---|---|---|
| SciCode | 51% | 36.2% |
| LMArena Coding | 1470 | 1277 |
| ALE-Bench | 1,403 | 264.7 |
| SWE-bench Verified | 77.6% | — |
| FrontierCode | 28.6% | — |
| LMArena WebDev | 1582 | — |
| WeirdML | 66.2% | — |
| BigCodeBench Instruct | — | 30% |
| LiveBench Coding | — | 47.1% |
| BigCodeBench Complete | — | 38.3% |
| HumanEval+ | — | 62.2% |
| MBPP+ | — | 59.5% |

## Agentic & Tool Use

- DeepSeek V4 Pro: 32.8 (#58)
- Mistral Large: 28.6 (#89)

| Benchmark | DeepSeek V4 Pro | Mistral Large |
|---|---|---|
| APEX-Agents | 47.3% | — |
| Berkeley Function Calling Leaderboard | — | 38.4% |
| Vending-Bench 2 | 3,285 | — |

## Reasoning

- DeepSeek V4 Pro: 56.5 (#24)
- Mistral Large: 15.8 (#310)

| Benchmark | DeepSeek V4 Pro | Mistral Large |
|---|---|---|
| CritPt | 18% | 0% |
| LMArena Hard Prompts | 1461 | 1257 |
| DTBench | 93.9% | 65.1% |
| LMCA | 45.5% | 16.7% |
| Epoch Capabilities Index | 155.31 | 128.52 |
| ForecastBench | 56.1 | 57.1 |
| ARC-AGI-2 | 61.3% | — |
| SimpleBench | — | 22.5% |
| Kagi LLM Benchmark | 53.5% | — |
| NYT Connections (extended) | 91.3% | — |
| ARC-AGI-1 | 90.5% | — |
| Chess Puzzles | 47% | — |
| LiveBench Reasoning | — | 43.5% |
| Mystery Game Puzzles | 43% | — |
| LiveBench Data Analysis | — | 50.1% |
| Surface Evolver Bench | 40% | — |
| LiveBench | — | 48.4% |

## Math

- DeepSeek V4 Pro: 64.8 (#30)
- Mistral Large: 18.2 (#291)

| Benchmark | DeepSeek V4 Pro | Mistral Large |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 98.6% | 8.5% |
| 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 | — | 28.1% |
| LiveBench Math | — | 42.5% |
| MATH Level 5 | — | 50.3% |
| FrontierMath (Feb 2025 set) | — | 0.3% |

## Knowledge

- DeepSeek V4 Pro: 59.5 (#31)
- Mistral Large: 30.1 (#230)

| Benchmark | DeepSeek V4 Pro | Mistral Large |
|---|---|---|
| GPQA Diamond | 91.7% | 51.3% |
| Vectara Hallucination Rate | 8.6% | 4.5% |
| LMArena Expert | 1464 | 1232 |
| SimpleQA Verified | 52.9% | — |
| MMLU-Pro | — | 59.9% |
| Confabulations | — | 21.4% |
| GPQA (HELM) | — | 43.5% |
| MMLU | — | 80% |

## Multilingual

- DeepSeek V4 Pro: 54.4 (#45)
- Mistral Large: 40.0 (#219)

| Benchmark | DeepSeek V4 Pro | Mistral Large |
|---|---|---|
| LMArena Non-English | 1439 | 1237 |
| LMArena Chinese | 1486 | 1240 |
| LMArena French | 1472 | 1325 |
| LMArena German | 1458 | 1254 |
| LMArena Japanese | 1445 | 1188 |
| LMArena Korean | 1447 | 1202 |
| LMArena Russian | 1453 | 1257 |
| LMArena Spanish | 1458 | 1268 |

## Instruction Following

- DeepSeek V4 Pro: 76.1 (#47)
- Mistral Large: 67.9 (#191)

| Benchmark | DeepSeek V4 Pro | Mistral Large |
|---|---|---|
| LMArena Instruction Following | 1448 | 1249 |
| LiveBench Instruction Following | — | 67.9% |
| IFEval | — | 87.7% |

## Long Context

- DeepSeek V4 Pro: 45.0 (#51)
- Mistral Large: 38.3 (#199)

| Benchmark | DeepSeek V4 Pro | Mistral Large |
|---|---|---|
| LMArena Longer Query | 1458 | 1261 |
| CL-bench Life | 13.5% | — |

## Writing & Preference

- DeepSeek V4 Pro: 65.5 (#46)
- Mistral Large: 40.7 (#242)

| Benchmark | DeepSeek V4 Pro | Mistral Large |
|---|---|---|
| LMArena Text | 1451 | 1266 |
| LMArena Creative Writing | 1446 | 1243 |
| EQ-Bench Creative Writing | 1553 | 985 |
| LMArena Multi-Turn | 1467 | 1260 |
| Short-Story Creative Writing | — | 69% |
| WildBench | — | 80.1% |
| EQ-Bench 4 | 1166 | — |
| LiveBench Language | — | 39.4% |

## FAQ

### Is DeepSeek V4 Pro better than Mistral Large?

DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 31.9 on the Noometry Index.

### Which is cheaper, DeepSeek V4 Pro or Mistral Large?

DeepSeek V4 Pro is cheaper. It lists at $0.66 per million input tokens and $1.98 per million output tokens; Mistral Large lists at $2 and $6.

### Is DeepSeek V4 Pro or Mistral Large better for coding?

DeepSeek V4 Pro scores higher on coding benchmarks: 52.4 versus 34.3 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek V4 Pro does, with 1M tokens against 131K.

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

28 benchmarks have published results for both models. DeepSeek V4 Pro has 48 scored results on Noometry and Mistral Large has 51.