# Claude Opus 4.7 vs Mistral Large 3

> Claude Opus 4.7 is the stronger model overall, scoring 58.4 to 38.6 on the Noometry Index. Mistral Large 3 costs 27× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/claude-opus-4-7-vs-mistral-large-3
- Last updated: 2026-10-10
- Shared benchmarks: 24

## Summary

- They share 24 benchmarks with published results for both. Claude Opus 4.7 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 4.7 leads 53.7 to 14.6.
- The biggest single-benchmark swing is Thematic Generalization: 72.8% for Claude Opus 4.7 and 23% 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 4.7.
- Claude Opus 4.7 accepts more context: 1M tokens versus 262K.
- Mistral Large 3 has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| Provider | Anthropic | Mistral AI |
| Noometry Index | 58.4 | 38.6 |
| Rank | 17 | 172 |
| Context | 1M | 262K |
| Input $/M | $5 | $0.25 |
| Output $/M | $25 | $0.75 |
| Weights | Proprietary | Open |

## Coding

- Claude Opus 4.7: 59.9 (#10)
- Mistral Large 3: 34.1 (#230)

| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| LMArena WebDev | 1557 | 1230 |
| LMArena Coding | 1519 | 1447 |
| SWE-bench Verified | 83.5% | — |
| FrontierCode | 38.5% | — |
| SciCode | 54.5% | — |
| GSO | 44.1% | — |
| WeirdML | 76.4% | — |
| MirrorCode | 31.1% | — |
| ALE-Bench | 1,323 | — |

## Agentic & Tool Use

- Claude Opus 4.7: 47.9 (#8)
- Mistral Large 3: —

| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| Terminal-Bench | 80.2% | — |
| APEX-Agents | 49.2% | — |
| OSWorld 2.0 | 18.2% | — |
| τ²-bench Banking | 40.2% | — |
| PostTrainBench | 28.6% | — |
| ExploitBench | 26.5% | — |
| GBAEval | 43.8% | — |
| GDP.pdf | 21% | — |
| LMArena Search | 1233 | — |
| Vending-Bench 2 | 10,937 | — |

## Reasoning

- Claude Opus 4.7: 53.7 (#24)
- Mistral Large 3: 14.6 (#314)

| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| Kagi LLM Benchmark | 80.7% | 50.9% |
| NYT Connections (extended) | 39% | 7.5% |
| Thematic Generalization | 72.8% | 23% |
| LMArena Hard Prompts | 1507 | 1429 |
| ARC-AGI-2 | 75.8% | — |
| SimpleBench | 61.7% | — |
| ARC-AGI-1 | 93.5% | — |
| CritPt | 12% | — |
| Chess Puzzles | 30% | — |
| EBR-Bench | 19% | — |
| Mystery Game Puzzles | 28% | — |
| DTBench | 94.7% | — |
| LMCA | 52.2% | — |
| Epoch Capabilities Index | 156.39 | — |
| ForecastBench | 60.3 | — |

## Math

- Claude Opus 4.7: 66.5 (#20)
- Mistral Large 3: 36.0 (#131)

| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| LMArena Math | 1499 | 1415 |
| FrontierMath (Tiers 1-3) | 70.2% | — |
| FrontierMath Tier 4 | 31.7% | — |
| MathArena Final-Answer Competitions | 73.6% | — |
| OTIS Mock AIME 2024-2025 | 97.8% | — |
| ProofBench | 54% | — |
| FrontierMath (Feb 2025 set) | 43.8% | — |
| FrontierMath Tier 4 (v1) | 22.9% | — |

## Knowledge

- Claude Opus 4.7: 62.6 (#20)
- Mistral Large 3: 35.5 (#173)

| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| Vectara Hallucination Rate | 12% | 14.5% |
| LMArena Expert | 1521 | 1421 |
| GPQA Diamond | 90.2% | — |
| Humanity's Last Exam | 36.2% | — |
| SimpleQA Verified | 51.7% | — |

## Multimodal

- Claude Opus 4.7: 41.5 (#29)
- Mistral Large 3: 37.6 (#65)

| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| LMArena Vision | 1317 | 1222 |
| Blueprint-Bench 2 | 24.5% | — |
| Furniture Assembly | 33.3% | — |
| LMArena Document | 1495 | — |

## Multilingual

- Claude Opus 4.7: 57.5 (#9)
- Mistral Large 3: 52.6 (#79)

| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| LMArena Non-English | 1481 | 1412 |
| LMArena Chinese | 1530 | 1448 |
| LMArena French | 1505 | 1456 |
| LMArena German | 1494 | 1438 |
| LMArena Japanese | 1472 | 1399 |
| LMArena Korean | 1466 | 1384 |
| LMArena Russian | 1494 | 1412 |
| LMArena Spanish | 1497 | 1437 |

## Instruction Following

- Claude Opus 4.7: 78.6 (#9)
- Mistral Large 3: 74.1 (#104)

| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| LMArena Instruction Following | 1498 | 1402 |

## Long Context

- Claude Opus 4.7: 46.1 (#24)
- Mistral Large 3: 43.1 (#102)

| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| LMArena Longer Query | 1505 | 1413 |

## Writing & Preference

- Claude Opus 4.7: 75.3 (#8)
- Mistral Large 3: 60.2 (#100)

| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| LMArena Text | 1491 | 1427 |
| LMArena Creative Writing | 1486 | 1385 |
| EQ-Bench Creative Writing | 1914 | 1412 |
| LMArena Multi-Turn | 1506 | 1429 |
| EQ-Bench 4 | 1311 | — |

## FAQ

### Is Claude Opus 4.7 better than Mistral Large 3?

Claude Opus 4.7 is the stronger model overall, scoring 58.4 to 38.6 on the Noometry Index. Mistral Large 3 costs 27× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.

### Which is cheaper, Claude Opus 4.7 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 4.7 lists at $5 and $25.

### Is Claude Opus 4.7 or Mistral Large 3 better for coding?

Claude Opus 4.7 scores higher on coding benchmarks: 59.9 versus 34.1 in the Noometry coding category.

### Which has the bigger context window?

Claude Opus 4.7 does, with 1M tokens against 262K.

### How many benchmarks do Claude Opus 4.7 and Mistral Large 3 share?

24 benchmarks have published results for both models. Claude Opus 4.7 has 66 scored results on Noometry and Mistral Large 3 has 24.