# DeepSeek-V3 vs Mistral Small 3

> DeepSeek-V3 is the stronger model overall, scoring 39.5 to 31.2 on the Noometry Index. Mistral Small 3 costs 7.0× less per token, which makes it the better buy when DeepSeek-V3's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/deepseek-v3-vs-mistral-small-3
- Last updated: 2026-10-12
- Shared benchmarks: 23

## Summary

- They share 23 benchmarks with published results for both. DeepSeek-V3 scores higher in 7 categories and Mistral Small 3 in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3 leads 57.4 to 32.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 37.8% for DeepSeek-V3 and 6.7% for Mistral Small 3.
- Mistral Small 3 is cheaper at $0.05 / $0.08 per million input/output tokens, against $0.24 / $0.90 for DeepSeek-V3.
- DeepSeek-V3 accepts more context: 164K tokens versus 33K.

## Snapshot

| | DeepSeek-V3 | Mistral Small 3 |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 39.5 | 31.2 |
| Rank | 166 | 278 |
| Context | 164K | 33K |
| Input $/M | $0.24 | $0.05 |
| Output $/M | $0.90 | $0.08 |
| Weights | Open | Open |

## Coding

- DeepSeek-V3: 42.3 (#106)
- Mistral Small 3: 36.5 (#207)

| Benchmark | DeepSeek-V3 | Mistral Small 3 |
|---|---|---|
| BigCodeBench Instruct | 50% | 45.3% |
| LMArena Coding | 1368 | 1246 |
| BigCodeBench Complete | 62.2% | 50.4% |
| Aider Polyglot | 55.1% | — |
| SciCode | 35.8% | — |
| WeirdML | 36.1% | — |
| LiveBench Coding | 70.9% | — |
| HumanEval+ | 86.6% | — |
| MBPP+ | 73% | — |

## Agentic & Tool Use

- DeepSeek-V3: —
- Mistral Small 3: —

| Benchmark | DeepSeek-V3 | Mistral Small 3 |
|---|---|---|
| METR Time Horizons | 49.6% | — |

## Reasoning

- DeepSeek-V3: 20.5 (#236)
- Mistral Small 3: 18.9 (#273)

| Benchmark | DeepSeek-V3 | Mistral Small 3 |
|---|---|---|
| LMArena Hard Prompts | 1365 | 1233 |
| Epoch Capabilities Index | 135.94 | 127.07 |
| SimpleBench | 27.2% | — |
| Kagi LLM Benchmark | 52.3% | — |
| CritPt | 0% | — |
| Chess Puzzles | — | 0% |
| LiveBench Reasoning | 65.8% | — |
| DTBench | 64.8% | — |
| LiveBench Data Analysis | 60.9% | — |
| LMCA | 15.5% | — |
| BIG-Bench Hard | 87.5% | — |
| ForecastBench | 59.1 | — |
| HellaSwag | 88.9% | — |
| LiveBench | 66.9% | — |
| PIQA | 84.7% | — |
| WinoGrande | 85.2% | — |

## Math

- DeepSeek-V3: 32.1 (#219)
- Mistral Small 3: 16.3 (#295)

| Benchmark | DeepSeek-V3 | Mistral Small 3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 37.8% | 6.7% |
| LMArena Math | 1373 | 1240 |
| Omni-MATH | 40.3% | — |
| LiveBench Math | 73.5% | — |
| MATH Level 5 | 75.5% | — |
| FrontierMath (Feb 2025 set) | 1.7% | — |

## Knowledge

- DeepSeek-V3: 37.5 (#155)
- Mistral Small 3: 25.1 (#263)

| Benchmark | DeepSeek-V3 | Mistral Small 3 |
|---|---|---|
| GPQA Diamond | 67.6% | 47.3% |
| Confabulations | 26.1% | 25.2% |
| LMArena Expert | 1351 | 1202 |
| MMLU-Pro | 72.3% | — |
| Vectara Hallucination Rate | 6.1% | — |
| GPQA (HELM) | 53.8% | — |
| ARC (AI2) Challenge | 95.3% | — |
| MMLU | 87.2% | — |
| TriviaQA | 82.9% | — |

## Multilingual

- DeepSeek-V3: 48.5 (#143)
- Mistral Small 3: 37.3 (#236)

| Benchmark | DeepSeek-V3 | Mistral Small 3 |
|---|---|---|
| LMArena Non-English | 1358 | 1198 |
| LMArena Chinese | 1391 | 1204 |
| LMArena French | 1385 | 1203 |
| LMArena German | 1374 | 1211 |
| LMArena Japanese | 1333 | 1111 |
| LMArena Korean | 1319 | 1188 |
| LMArena Russian | 1373 | 1216 |
| LMArena Spanish | 1358 | — |

## Instruction Following

- DeepSeek-V3: 72.8 (#130)
- Mistral Small 3: 63.7 (#229)

| Benchmark | DeepSeek-V3 | Mistral Small 3 |
|---|---|---|
| LMArena Instruction Following | 1345 | 1214 |
| LiveBench Instruction Following | 81.5% | — |
| IFEval | 83.2% | — |

## Long Context

- DeepSeek-V3: 34.0 (#253)
- Mistral Small 3: 37.8 (#211)

| Benchmark | DeepSeek-V3 | Mistral Small 3 |
|---|---|---|
| LMArena Longer Query | 1352 | 1246 |
| Fiction.LiveBench | 50% | — |

## Writing & Preference

- DeepSeek-V3: 57.4 (#130)
- Mistral Small 3: 32.2 (#280)

| Benchmark | DeepSeek-V3 | Mistral Small 3 |
|---|---|---|
| LMArena Text | 1375 | 1234 |
| LMArena Creative Writing | 1364 | 1195 |
| EQ-Bench Creative Writing | 1472 | 707 |
| LMArena Multi-Turn | 1389 | 1217 |
| Short-Story Creative Writing | 77% | — |
| WildBench | 83% | — |
| LiveBench Language | 49.1% | — |

## FAQ

### Is DeepSeek-V3 better than Mistral Small 3?

DeepSeek-V3 is the stronger model overall, scoring 39.5 to 31.2 on the Noometry Index. Mistral Small 3 costs 7.0× less per token, which makes it the better buy when DeepSeek-V3's lead doesn't matter for your workload.

### Which is cheaper, DeepSeek-V3 or Mistral Small 3?

Mistral Small 3 is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; DeepSeek-V3 lists at $0.24 and $0.90.

### Is DeepSeek-V3 or Mistral Small 3 better for coding?

DeepSeek-V3 scores higher on coding benchmarks: 42.3 versus 36.5 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek-V3 does, with 164K tokens against 33K.

### How many benchmarks do DeepSeek-V3 and Mistral Small 3 share?

23 benchmarks have published results for both models. DeepSeek-V3 has 60 scored results on Noometry and Mistral Small 3 has 24.