# Claude Opus 5 vs Mistral Large 3

> Claude Opus 5 is the stronger model overall, scoring 67.8 to 39.1 on the Noometry Index. Mistral Large 3 costs 27× less per token, which makes it the better buy when Claude Opus 5's lead doesn't matter for your workload.

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

## Summary

- They share 21 benchmarks with published results for both. Claude Opus 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 Opus 5 leads 77.2 to 15.2.
- The biggest single-benchmark swing is NYT Connections (extended): 94.3% for Claude Opus 5 and 7.5% for Mistral Large 3.
- Mistral Large 3 is cheaper at $0.25 / $0.75 per million input/output tokens, against $5 / $25 for Claude Opus 5.
- Claude Opus 5 accepts more context: 1M tokens versus 262K.
- Mistral Large 3 has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Opus 5 | Mistral Large 3 |
|---|---|---|
| Provider | Anthropic | Mistral AI |
| Noometry Index | 67.8 | 39.1 |
| Rank | 4 | 176 |
| Context | 1M | 262K |
| Input $/M | $5 | $0.25 |
| Output $/M | $25 | $0.75 |
| Weights | Proprietary | Open |

## Coding

- Claude Opus 5: 67.5 (#5)
- Mistral Large 3: 34.4 (#237)

| Benchmark | Claude Opus 5 | Mistral Large 3 |
|---|---|---|
| LMArena WebDev | 1691 | 1230 |
| LMArena Coding | 1534 | 1448 |
| DeepSWE | 73.6% | — |
| FrontierCode | 53.4% | — |
| CursorBench | 46.6% | — |
| FrontierSWE | 52% | — |
| SciCode | 56.4% | — |
| WeirdML | 91.8% | — |
| ALE-Bench | 2,165 | — |

## Agentic & Tool Use

- Claude Opus 5: 55.6 (#1)
- Mistral Large 3: —

| Benchmark | Claude Opus 5 | Mistral Large 3 |
|---|---|---|
| APEX-Agents | 65.8% | — |
| OSWorld 2.0 | 31.4% | — |
| τ²-bench Banking | 48.7% | — |
| PostTrainBench | 35% | — |
| BALROG | 63.4% | — |
| GBAEval | 79.6% | — |
| GDP.pdf | 24% | — |
| Vending-Bench 2 | 11,182 | — |

## Reasoning

- Claude Opus 5: 77.2 (#4)
- Mistral Large 3: 15.2 (#319)

| Benchmark | Claude Opus 5 | Mistral Large 3 |
|---|---|---|
| NYT Connections (extended) | 94.3% | 7.5% |
| LMArena Hard Prompts | 1526 | 1429 |
| ARC-AGI-2 | 90.4% | — |
| SimpleBench | 80.6% | — |
| Kagi LLM Benchmark | — | 50.9% |
| ARC-AGI-1 | 97.5% | — |
| CritPt | 29.1% | — |
| Chess Puzzles | 42% | — |
| Thematic Generalization | — | 23% |
| EBR-Bench | 45.7% | — |
| Mystery Game Puzzles | 59% | — |
| DTBench | 97.9% | — |
| LMCA | 64.5% | — |
| Bench to the Future 3 | 0.12 | — |
| Epoch Capabilities Index | 162.78 | — |

## Math

- Claude Opus 5: 86.2 (#8)
- Mistral Large 3: 38.7 (#129)

| Benchmark | Claude Opus 5 | Mistral Large 3 |
|---|---|---|
| LMArena Math | 1531 | 1414 |
| FrontierMath (Tiers 1-3) | 85.6% | — |
| FrontierMath Tier 4 | 73.2% | — |
| OTIS Mock AIME 2024-2025 | 98.9% | — |
| ProofBench | 99% | — |

## Knowledge

- Claude Opus 5: 66.8 (#9)
- Mistral Large 3: 36.0 (#177)

| Benchmark | Claude Opus 5 | Mistral Large 3 |
|---|---|---|
| LMArena Expert | 1557 | 1421 |
| GPQA Diamond | 93.9% | — |
| SimpleQA Verified | 59.9% | — |
| Vectara Hallucination Rate | — | 14.5% |

## Multimodal

- Claude Opus 5: 50.8 (#8)
- Mistral Large 3: 38.2 (#66)

| Benchmark | Claude Opus 5 | Mistral Large 3 |
|---|---|---|
| LMArena Vision | 1319 | 1221 |
| Blueprint-Bench 2 | 30.4% | — |
| Furniture Assembly | 60.8% | — |
| LMArena Document | 1516 | — |

## Multilingual

- Claude Opus 5: 58.8 (#4)
- Mistral Large 3: 52.5 (#84)

| Benchmark | Claude Opus 5 | Mistral Large 3 |
|---|---|---|
| LMArena Non-English | 1501 | 1413 |
| LMArena Chinese | 1574 | 1447 |
| LMArena French | 1519 | 1455 |
| LMArena German | 1524 | 1437 |
| LMArena Japanese | 1516 | 1394 |
| LMArena Korean | 1521 | 1384 |
| LMArena Russian | 1507 | 1411 |
| LMArena Spanish | 1519 | 1440 |

## Instruction Following

- Claude Opus 5: 79.2 (#7)
- Mistral Large 3: 74.0 (#108)

| Benchmark | Claude Opus 5 | Mistral Large 3 |
|---|---|---|
| LMArena Instruction Following | 1517 | 1403 |

## Long Context

- Claude Opus 5: 46.5 (#21)
- Mistral Large 3: 43.1 (#105)

| Benchmark | Claude Opus 5 | Mistral Large 3 |
|---|---|---|
| LMArena Longer Query | 1515 | 1413 |

## Writing & Preference

- Claude Opus 5: 79.2 (#1)
- Mistral Large 3: 60.0 (#101)

| Benchmark | Claude Opus 5 | Mistral Large 3 |
|---|---|---|
| LMArena Text | 1507 | 1428 |
| LMArena Creative Writing | 1491 | 1386 |
| EQ-Bench Creative Writing | 2133 | 1412 |
| LMArena Multi-Turn | 1499 | 1429 |
| EQ-Bench 4 | 1385 | — |

## FAQ

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

Claude Opus 5 is the stronger model overall, scoring 67.8 to 39.1 on the Noometry Index. Mistral Large 3 costs 27× less per token, which makes it the better buy when Claude Opus 5's lead doesn't matter for your workload.

### Which is cheaper, Claude Opus 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 Opus 5 lists at $5 and $25.

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

Claude Opus 5 scores higher on coding benchmarks: 67.5 versus 34.4 in the Noometry coding category.

### Which has the bigger context window?

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

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

21 benchmarks have published results for both models. Claude Opus 5 has 57 scored results on Noometry and Mistral Large 3 has 24.