# Claude Opus 4.7 vs Mistral Nemo

> Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 26.4 on the Noometry Index. Mistral Nemo costs 67× 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-nemo
- Last updated: 2026-10-10
- Shared benchmarks: 4

## Summary

- They share 4 benchmarks with published results for both. Claude Opus 4.7 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 Claude Opus 4.7 leads 62.6 to 12.3.
- The biggest single-benchmark swing is GPQA Diamond: 90.2% for Claude Opus 4.7 and 29.9% for Mistral Nemo.
- Mistral Nemo is cheaper at $0.15 / $0.15 per million input/output tokens, against $5 / $25 for Claude Opus 4.7.
- Claude Opus 4.7 accepts more context: 1M tokens versus 128K.
- Mistral Nemo has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Opus 4.7 | Mistral Nemo |
|---|---|---|
| Provider | Anthropic | Mistral AI |
| Noometry Index | 58.3 | 26.4 |
| Rank | 19 | 337 |
| Context | 1M | 128K |
| Input $/M | $5 | $0.15 |
| Output $/M | $25 | $0.15 |
| Weights | Proprietary | Open |

## Coding

- Claude Opus 4.7: 59.6 (#13)
- Mistral Nemo: —

| Benchmark | Claude Opus 4.7 | Mistral Nemo |
|---|---|---|
| SWE-bench Verified | 83.5% | — |
| FrontierCode | 38.5% | — |
| LMArena WebDev | 1558 | — |
| SciCode | 54.5% | — |
| GSO | 44.1% | — |
| WeirdML | 76.4% | — |
| LMArena Coding | 1518 | — |
| MirrorCode | 31.1% | — |
| ALE-Bench | 1,323 | — |

## Agentic & Tool Use

- Claude Opus 4.7: 47.9 (#10)
- Mistral Nemo: 23.5 (#125)

| Benchmark | Claude Opus 4.7 | Mistral Nemo |
|---|---|---|
| Terminal-Bench | 80.2% | — |
| APEX-Agents | 49.2% | — |
| Berkeley Function Calling Leaderboard | — | 27.6% |
| OSWorld 2.0 | 18.2% | — |
| τ²-bench Banking | 40.2% | — |
| PostTrainBench | 28.6% | — |
| BALROG | — | 17.6% |
| ExploitBench | 26.5% | — |
| GBAEval | 43.8% | — |
| GDP.pdf | 21% | — |
| LMArena Search | 1233 | — |
| Vending-Bench 2 | 10,937 | — |

## Reasoning

- Claude Opus 4.7: 53.8 (#29)
- Mistral Nemo: 20.7 (#232)

| Benchmark | Claude Opus 4.7 | Mistral Nemo |
|---|---|---|
| DTBench | 94.7% | 48.6% |
| Epoch Capabilities Index | 156.25 | 118.68 |
| ARC-AGI-2 | 75.8% | — |
| SimpleBench | 61.7% | — |
| Kagi LLM Benchmark | 80.7% | — |
| NYT Connections (extended) | 39% | — |
| ARC-AGI-1 | 93.5% | — |
| CritPt | 12% | — |
| Chess Puzzles | 30% | — |
| Thematic Generalization | 72.8% | — |
| EBR-Bench | 19% | — |
| LMArena Hard Prompts | 1506 | — |
| Mystery Game Puzzles | 28% | — |
| LMCA | 52.2% | — |
| ForecastBench | 60.3 | — |
| PIQA | — | 83.5% |

## Math

- Claude Opus 4.7: 66.7 (#26)
- Mistral Nemo: 25.5 (#268)

| Benchmark | Claude Opus 4.7 | Mistral Nemo |
|---|---|---|
| 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% | — |
| LMArena Math | 1499 | — |
| MATH Level 5 | — | 10.8% |
| FrontierMath (Feb 2025 set) | 43.8% | — |
| FrontierMath Tier 4 (v1) | 22.9% | — |
| GSM8K | — | 84.2% |

## Knowledge

- Claude Opus 4.7: 62.6 (#23)
- Mistral Nemo: 12.3 (#298)

| Benchmark | Claude Opus 4.7 | Mistral Nemo |
|---|---|---|
| GPQA Diamond | 90.2% | 29.9% |
| Humanity's Last Exam | 36.2% | — |
| SimpleQA Verified | 51.7% | — |
| Vectara Hallucination Rate | 12% | — |
| LMArena Expert | 1521 | — |
| BoolQ | — | 82.5% |

## Multimodal

- Claude Opus 4.7: 41.2 (#38)
- Mistral Nemo: —

| Benchmark | Claude Opus 4.7 | Mistral Nemo |
|---|---|---|
| LMArena Vision | 1316 | — |
| Blueprint-Bench 2 | 24.5% | — |
| Furniture Assembly | 33.3% | — |
| LMArena Document | 1495 | — |

## Multilingual

- Claude Opus 4.7: 57.3 (#10)
- Mistral Nemo: —

| Benchmark | Claude Opus 4.7 | Mistral Nemo |
|---|---|---|
| LMArena Non-English | 1480 | — |
| LMArena Chinese | 1531 | — |
| LMArena French | 1503 | — |
| LMArena German | 1495 | — |
| LMArena Japanese | 1472 | — |
| LMArena Korean | 1464 | — |
| LMArena Russian | 1494 | — |
| LMArena Spanish | 1495 | — |

## Instruction Following

- Claude Opus 4.7: 78.4 (#10)
- Mistral Nemo: —

| Benchmark | Claude Opus 4.7 | Mistral Nemo |
|---|---|---|
| LMArena Instruction Following | 1498 | — |

## Long Context

- Claude Opus 4.7: 46.2 (#25)
- Mistral Nemo: —

| Benchmark | Claude Opus 4.7 | Mistral Nemo |
|---|---|---|
| LMArena Longer Query | 1505 | — |

## Writing & Preference

- Claude Opus 4.7: 75.1 (#8)
- Mistral Nemo: 28.5 (#296)

| Benchmark | Claude Opus 4.7 | Mistral Nemo |
|---|---|---|
| EQ-Bench Creative Writing | 1914 | 881 |
| LMArena Text | 1490 | — |
| LMArena Creative Writing | 1486 | — |
| EQ-Bench 4 | 1311 | — |
| LMArena Multi-Turn | 1505 | — |

## FAQ

### Is Claude Opus 4.7 better than Mistral Nemo?

Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 26.4 on the Noometry Index. Mistral Nemo costs 67× 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 Nemo?

Mistral Nemo is cheaper. It lists at $0.15 per million input tokens and $0.15 per million output tokens; Claude Opus 4.7 lists at $5 and $25.

### Which has the bigger context window?

Claude Opus 4.7 does, with 1M tokens against 128K.

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

4 benchmarks have published results for both models. Claude Opus 4.7 has 66 scored results on Noometry and Mistral Nemo has 10.