# Claude Opus 4.7 vs GPT-4.1

> Claude Opus 4.7 is the stronger model overall, scoring 58.4 to 35.7 on the Noometry Index. GPT-4.1 costs 2.9× 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-gpt-4-1
- Last updated: 2026-10-10
- Shared benchmarks: 39

## Summary

- They share 39 benchmarks with published results for both. Claude Opus 4.7 scores higher in 10 categories and GPT-4.1 in 0 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Opus 4.7 leads 66.5 to 21.4.
- The biggest single-benchmark swing is ARC-AGI-1: 93.5% for Claude Opus 4.7 and 5.5% for GPT-4.1.
- GPT-4.1 is cheaper at $2 / $8 per million input/output tokens, against $5 / $25 for Claude Opus 4.7.
- GPT-4.1 accepts more context: 1.05M tokens versus 1M.

## Snapshot

| | Claude Opus 4.7 | GPT-4.1 |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 58.4 | 35.7 |
| Rank | 17 | 215 |
| Context | 1M | 1.05M |
| Input $/M | $5 | $2 |
| Output $/M | $25 | $8 |
| Weights | Proprietary | Proprietary |

## Coding

- Claude Opus 4.7: 59.9 (#10)
- GPT-4.1: 34.2 (#228)

| Benchmark | Claude Opus 4.7 | GPT-4.1 |
|---|---|---|
| SWE-bench Verified | 83.5% | 48.5% |
| WeirdML | 76.4% | 39% |
| LMArena Coding | 1519 | 1391 |
| ALE-Bench | 1,323 | 558.1 |
| FrontierCode | 38.5% | — |
| SWE-bench Verified (bash only) | — | 39.6% |
| Aider Polyglot | — | 52.4% |
| LMArena WebDev | 1557 | — |
| SciCode | 54.5% | — |
| GSO | 44.1% | — |
| MirrorCode | 31.1% | — |
| CadEval | — | 42% |

## Agentic & Tool Use

- Claude Opus 4.7: 47.9 (#8)
- GPT-4.1: 34.4 (#40)

| Benchmark | Claude Opus 4.7 | GPT-4.1 |
|---|---|---|
| Terminal-Bench | 80.2% | — |
| APEX-Agents | 49.2% | — |
| Berkeley Function Calling Leaderboard | — | 54% |
| 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)
- GPT-4.1: 11.7 (#334)

| Benchmark | Claude Opus 4.7 | GPT-4.1 |
|---|---|---|
| ARC-AGI-2 | 75.8% | 0.4% |
| SimpleBench | 61.7% | 27% |
| Kagi LLM Benchmark | 80.7% | 52.3% |
| ARC-AGI-1 | 93.5% | 5.5% |
| Chess Puzzles | 30% | 6% |
| LMArena Hard Prompts | 1507 | 1384 |
| DTBench | 94.7% | 68.3% |
| LMCA | 52.2% | 25.6% |
| Epoch Capabilities Index | 156.39 | 136.79 |
| ForecastBench | 60.3 | 61.5 |
| NYT Connections (extended) | 39% | — |
| CritPt | 12% | — |
| EnigmaEval | — | 2.2% |
| Thematic Generalization | 72.8% | — |
| EBR-Bench | 19% | — |
| Mystery Game Puzzles | 28% | — |

## Math

- Claude Opus 4.7: 66.5 (#20)
- GPT-4.1: 21.4 (#269)

| Benchmark | Claude Opus 4.7 | GPT-4.1 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 70.2% | 6% |
| OTIS Mock AIME 2024-2025 | 97.8% | 38.3% |
| LMArena Math | 1499 | 1369 |
| FrontierMath (Feb 2025 set) | 43.8% | 5.5% |
| FrontierMath Tier 4 (v1) | 22.9% | 0% |
| FrontierMath Tier 4 | 31.7% | — |
| MathArena Final-Answer Competitions | 73.6% | — |
| ProofBench | 54% | — |
| Omni-MATH | — | 47.1% |
| MATH Level 5 | — | 83% |

## Knowledge

- Claude Opus 4.7: 62.6 (#20)
- GPT-4.1: 37.0 (#152)

| Benchmark | Claude Opus 4.7 | GPT-4.1 |
|---|---|---|
| GPQA Diamond | 90.2% | 66.9% |
| Humanity's Last Exam | 36.2% | 5.4% |
| SimpleQA Verified | 51.7% | 31.1% |
| Vectara Hallucination Rate | 12% | 5.6% |
| LMArena Expert | 1521 | 1364 |
| MMLU-Pro | — | 81.1% |
| GPQA (HELM) | — | 65.9% |

## Multimodal

- Claude Opus 4.7: 41.5 (#29)
- GPT-4.1: 37.5 (#66)

| Benchmark | Claude Opus 4.7 | GPT-4.1 |
|---|---|---|
| LMArena Vision | 1317 | 1210 |
| GeoBench | — | 72% |
| Blueprint-Bench 2 | 24.5% | — |
| Furniture Assembly | 33.3% | — |
| LMArena Document | 1495 | — |

## Multilingual

- Claude Opus 4.7: 57.5 (#9)
- GPT-4.1: 49.6 (#128)

| Benchmark | Claude Opus 4.7 | GPT-4.1 |
|---|---|---|
| LMArena Non-English | 1481 | 1370 |
| LMArena Chinese | 1530 | 1382 |
| LMArena French | 1505 | 1383 |
| LMArena German | 1494 | 1380 |
| LMArena Japanese | 1472 | 1320 |
| LMArena Korean | 1466 | 1339 |
| LMArena Russian | 1494 | 1377 |
| LMArena Spanish | 1497 | 1375 |

## Instruction Following

- Claude Opus 4.7: 78.6 (#9)
- GPT-4.1: 71.5 (#148)

| Benchmark | Claude Opus 4.7 | GPT-4.1 |
|---|---|---|
| LMArena Instruction Following | 1498 | 1367 |
| IFEval | — | 83.8% |

## Long Context

- Claude Opus 4.7: 46.1 (#24)
- GPT-4.1: 40.0 (#158)

| Benchmark | Claude Opus 4.7 | GPT-4.1 |
|---|---|---|
| LMArena Longer Query | 1505 | 1385 |
| Fiction.LiveBench | — | 63.9% |

## Writing & Preference

- Claude Opus 4.7: 75.3 (#8)
- GPT-4.1: 57.8 (#120)

| Benchmark | Claude Opus 4.7 | GPT-4.1 |
|---|---|---|
| LMArena Text | 1491 | 1383 |
| LMArena Creative Writing | 1486 | 1363 |
| EQ-Bench Creative Writing | 1914 | 1420 |
| LMArena Multi-Turn | 1506 | 1398 |
| WildBench | — | 85.4% |
| EQ-Bench 4 | 1311 | — |

## FAQ

### Is Claude Opus 4.7 better than GPT-4.1?

Claude Opus 4.7 is the stronger model overall, scoring 58.4 to 35.7 on the Noometry Index. GPT-4.1 costs 2.9× 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 GPT-4.1?

GPT-4.1 is cheaper. It lists at $2 per million input tokens and $8 per million output tokens; Claude Opus 4.7 lists at $5 and $25.

### Is Claude Opus 4.7 or GPT-4.1 better for coding?

Claude Opus 4.7 scores higher on coding benchmarks: 59.9 versus 34.2 in the Noometry coding category.

### Which has the bigger context window?

GPT-4.1 does, with 1.05M tokens against 1M.

### How many benchmarks do Claude Opus 4.7 and GPT-4.1 share?

39 benchmarks have published results for both models. Claude Opus 4.7 has 66 scored results on Noometry and GPT-4.1 has 52.