# Claude Sonnet 5 vs Mistral Large 3

> Claude Sonnet 5 is the stronger model overall, scoring 54.5 to 38.6 on the Noometry Index. Mistral Large 3 costs 11× less per token, which makes it the better buy when Claude Sonnet 5's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/claude-sonnet-5-vs-mistral-large-3
- Last updated: 2026-10-10
- Shared benchmarks: 21

## Summary

- They share 21 benchmarks with published results for both. Claude Sonnet 5 scores higher in 9 categories and Mistral Large 3 in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Sonnet 5 leads 48.2 to 14.6.
- The biggest single-benchmark swing is NYT Connections (extended): 75.1% for Claude Sonnet 5 and 7.5% for Mistral Large 3.
- Mistral Large 3 is cheaper at $0.25 / $0.75 per million input/output tokens, against $2 / $10 for Claude Sonnet 5.
- Claude Sonnet 5 accepts more context: 1M tokens versus 262K.
- Mistral Large 3 has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Sonnet 5 | Mistral Large 3 |
|---|---|---|
| Provider | Anthropic | Mistral AI |
| Noometry Index | 54.5 | 38.6 |
| Rank | 26 | 172 |
| Context | 1M | 262K |
| Input $/M | $2 | $0.25 |
| Output $/M | $10 | $0.75 |
| Weights | Proprietary | Open |

## Coding

- Claude Sonnet 5: 55.5 (#20)
- Mistral Large 3: 34.1 (#230)

| Benchmark | Claude Sonnet 5 | Mistral Large 3 |
|---|---|---|
| LMArena WebDev | 1540 | 1230 |
| LMArena Coding | 1483 | 1447 |
| DeepSWE | 53.8% | — |
| FrontierCode | 42.7% | — |
| CursorBench | 34.1% | — |
| SciCode | 53.6% | — |
| GSO | 37.3% | — |
| WeirdML | 68.8% | — |
| ALE-Bench | 1,463 | — |

## Agentic & Tool Use

- Claude Sonnet 5: 42.7 (#16)
- Mistral Large 3: —

| Benchmark | Claude Sonnet 5 | Mistral Large 3 |
|---|---|---|
| APEX-Agents | 54.5% | — |
| GBAEval | 65.3% | — |
| LMArena Search | 1194 | — |
| Vending-Bench 2 | 6,378 | — |

## Reasoning

- Claude Sonnet 5: 48.2 (#37)
- Mistral Large 3: 14.6 (#314)

| Benchmark | Claude Sonnet 5 | Mistral Large 3 |
|---|---|---|
| NYT Connections (extended) | 75.1% | 7.5% |
| LMArena Hard Prompts | 1461 | 1429 |
| SimpleBench | 60.6% | — |
| Kagi LLM Benchmark | — | 50.9% |
| CritPt | 16.9% | — |
| Chess Puzzles | 35% | — |
| Thematic Generalization | — | 23% |
| Mystery Game Puzzles | 35% | — |
| DTBench | 92.5% | — |
| LMCA | 50% | — |
| Surface Evolver Bench | 60% | — |
| Bench to the Future 3 | 0.14 | — |
| Epoch Capabilities Index | 156.34 | — |
| ForecastBench | 61.1 | — |

## Math

- Claude Sonnet 5: 66.1 (#21)
- Mistral Large 3: 36.0 (#131)

| Benchmark | Claude Sonnet 5 | Mistral Large 3 |
|---|---|---|
| LMArena Math | 1467 | 1415 |
| FrontierMath (Tiers 1-3) | 65.6% | — |
| FrontierMath Tier 4 | 29.3% | — |
| OTIS Mock AIME 2024-2025 | 94.7% | — |
| ProofBench | 77% | — |

## Knowledge

- Claude Sonnet 5: 55.7 (#42)
- Mistral Large 3: 35.5 (#173)

| Benchmark | Claude Sonnet 5 | Mistral Large 3 |
|---|---|---|
| LMArena Expert | 1491 | 1421 |
| GPQA Diamond | 90.5% | — |
| SimpleQA Verified | 33.7% | — |
| Vectara Hallucination Rate | — | 14.5% |

## Multimodal

- Claude Sonnet 5: 42.4 (#26)
- Mistral Large 3: 37.6 (#65)

| Benchmark | Claude Sonnet 5 | Mistral Large 3 |
|---|---|---|
| LMArena Vision | 1275 | 1222 |
| Blueprint-Bench 2 | 24.9% | — |
| LMArena Document | 1466 | — |

## Multilingual

- Claude Sonnet 5: 54.0 (#55)
- Mistral Large 3: 52.6 (#79)

| Benchmark | Claude Sonnet 5 | Mistral Large 3 |
|---|---|---|
| LMArena Non-English | 1431 | 1412 |
| LMArena Chinese | 1475 | 1448 |
| LMArena French | 1457 | 1456 |
| LMArena German | 1448 | 1438 |
| LMArena Japanese | 1422 | 1399 |
| LMArena Korean | 1411 | 1384 |
| LMArena Russian | 1452 | 1412 |
| LMArena Spanish | 1436 | 1437 |

## Instruction Following

- Claude Sonnet 5: 76.6 (#39)
- Mistral Large 3: 74.1 (#104)

| Benchmark | Claude Sonnet 5 | Mistral Large 3 |
|---|---|---|
| LMArena Instruction Following | 1453 | 1402 |

## Long Context

- Claude Sonnet 5: 44.8 (#53)
- Mistral Large 3: 43.1 (#102)

| Benchmark | Claude Sonnet 5 | Mistral Large 3 |
|---|---|---|
| LMArena Longer Query | 1464 | 1413 |

## Writing & Preference

- Claude Sonnet 5: 69.4 (#24)
- Mistral Large 3: 60.2 (#100)

| Benchmark | Claude Sonnet 5 | Mistral Large 3 |
|---|---|---|
| LMArena Text | 1443 | 1427 |
| LMArena Creative Writing | 1416 | 1385 |
| EQ-Bench Creative Writing | 1794 | 1412 |
| LMArena Multi-Turn | 1454 | 1429 |
| EQ-Bench 4 | 1236 | — |

## FAQ

### Is Claude Sonnet 5 better than Mistral Large 3?

Claude Sonnet 5 is the stronger model overall, scoring 54.5 to 38.6 on the Noometry Index. Mistral Large 3 costs 11× less per token, which makes it the better buy when Claude Sonnet 5's lead doesn't matter for your workload.

### Which is cheaper, Claude Sonnet 5 or Mistral Large 3?

Mistral Large 3 is cheaper. It lists at $0.25 per million input tokens and $0.75 per million output tokens; Claude Sonnet 5 lists at $2 and $10.

### Is Claude Sonnet 5 or Mistral Large 3 better for coding?

Claude Sonnet 5 scores higher on coding benchmarks: 55.5 versus 34.1 in the Noometry coding category.

### Which has the bigger context window?

Claude Sonnet 5 does, with 1M tokens against 262K.

### How many benchmarks do Claude Sonnet 5 and Mistral Large 3 share?

21 benchmarks have published results for both models. Claude Sonnet 5 has 51 scored results on Noometry and Mistral Large 3 has 24.