# DeepSeek V4 Pro vs Mistral Nemo

> DeepSeek V4 Pro is the stronger model overall, scoring 54.2 to 25.9 on the Noometry Index. Mistral Nemo costs 3.6× 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-nemo
- Last updated: 2026-10-10
- Shared benchmarks: 4

## Summary

- They share 4 benchmarks with published results for both. DeepSeek V4 Pro scores higher in 5 categories and Mistral Nemo in 0 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where DeepSeek V4 Pro leads 59.5 to 12.3.
- The biggest single-benchmark swing is GPQA Diamond: 91.7% for DeepSeek V4 Pro and 29.9% for Mistral Nemo.
- Mistral Nemo is cheaper at $0.15 / $0.15 per million input/output tokens, against $0.43 / $0.87 for DeepSeek V4 Pro.
- DeepSeek V4 Pro accepts more context: 1M tokens versus 128K.

## Snapshot

| | DeepSeek V4 Pro | Mistral Nemo |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 54.2 | 25.9 |
| Rank | 28 | 332 |
| Context | 1M | 128K |
| Input $/M | $0.43 | $0.15 |
| Output $/M | $0.87 | $0.15 |
| Weights | Open | Open |

## Coding

- DeepSeek V4 Pro: 52.2 (#31)
- Mistral Nemo: —

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

## Agentic & Tool Use

- DeepSeek V4 Pro: 32.7 (#54)
- Mistral Nemo: 23.3 (#118)

| Benchmark | DeepSeek V4 Pro | Mistral Nemo |
|---|---|---|
| APEX-Agents | 47.3% | — |
| Berkeley Function Calling Leaderboard | — | 27.6% |
| BALROG | — | 17.6% |
| Vending-Bench 2 | 3,285 | — |

## Reasoning

- DeepSeek V4 Pro: 56.4 (#22)
- Mistral Nemo: 19.9 (#230)

| Benchmark | DeepSeek V4 Pro | Mistral Nemo |
|---|---|---|
| DTBench | 93.9% | 48.6% |
| Epoch Capabilities Index | 155.39 | 118.63 |
| ARC-AGI-2 | 61.3% | — |
| Kagi LLM Benchmark | 53.5% | — |
| NYT Connections (extended) | 91.3% | — |
| ARC-AGI-1 | 90.5% | — |
| CritPt | 18% | — |
| Chess Puzzles | 47% | — |
| LMArena Hard Prompts | 1461 | — |
| Mystery Game Puzzles | 43% | — |
| LMCA | 45.5% | — |
| Surface Evolver Bench | 40% | — |
| ForecastBench | 56.1 | — |
| PIQA | — | 83.5% |

## Math

- DeepSeek V4 Pro: 64.6 (#24)
- Mistral Nemo: 23.5 (#263)

| Benchmark | DeepSeek V4 Pro | Mistral Nemo |
|---|---|---|
| FrontierMath (Tiers 1-3) | 64.6% | — |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 76.6% | — |
| OTIS Mock AIME 2024-2025 | 98.6% | — |
| ProofBench | 50% | — |
| LMArena Math | 1455 | — |
| MATH Level 5 | — | 10.8% |
| GSM8K | — | 84.2% |

## Knowledge

- DeepSeek V4 Pro: 59.5 (#28)
- Mistral Nemo: 12.3 (#293)

| Benchmark | DeepSeek V4 Pro | Mistral Nemo |
|---|---|---|
| GPQA Diamond | 91.7% | 29.9% |
| SimpleQA Verified | 52.9% | — |
| Vectara Hallucination Rate | 8.6% | — |
| LMArena Expert | 1463 | — |
| BoolQ | — | 82.5% |

## Multilingual

- DeepSeek V4 Pro: 54.5 (#44)
- Mistral Nemo: —

| Benchmark | DeepSeek V4 Pro | Mistral Nemo |
|---|---|---|
| LMArena Non-English | 1438 | — |
| LMArena Chinese | 1486 | — |
| LMArena French | 1473 | — |
| LMArena German | 1458 | — |
| LMArena Japanese | 1448 | — |
| LMArena Korean | 1452 | — |
| LMArena Russian | 1452 | — |
| LMArena Spanish | 1457 | — |

## Instruction Following

- DeepSeek V4 Pro: 76.3 (#44)
- Mistral Nemo: —

| Benchmark | DeepSeek V4 Pro | Mistral Nemo |
|---|---|---|
| LMArena Instruction Following | 1448 | — |

## Long Context

- DeepSeek V4 Pro: 45.0 (#49)
- Mistral Nemo: —

| Benchmark | DeepSeek V4 Pro | Mistral Nemo |
|---|---|---|
| CL-bench Life | 13.5% | — |
| LMArena Longer Query | 1459 | — |

## Writing & Preference

- DeepSeek V4 Pro: 65.6 (#45)
- Mistral Nemo: 28.6 (#291)

| Benchmark | DeepSeek V4 Pro | Mistral Nemo |
|---|---|---|
| EQ-Bench Creative Writing | 1553 | 881 |
| LMArena Text | 1451 | — |
| LMArena Creative Writing | 1446 | — |
| EQ-Bench 4 | 1166 | — |
| LMArena Multi-Turn | 1467 | — |

## FAQ

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

DeepSeek V4 Pro is the stronger model overall, scoring 54.2 to 25.9 on the Noometry Index. Mistral Nemo costs 3.6× 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 Nemo?

Mistral Nemo is cheaper. It lists at $0.15 per million input tokens and $0.15 per million output tokens; DeepSeek V4 Pro lists at $0.43 and $0.87.

### Which has the bigger context window?

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

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

4 benchmarks have published results for both models. DeepSeek V4 Pro has 48 scored results on Noometry and Mistral Nemo has 10.