# Claude Opus 4.7 vs GPT-4.1 mini

> Claude Opus 4.7 is the stronger model overall, scoring 58.4 to 33.5 on the Noometry Index. GPT-4.1 mini costs 14× 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-mini
- Last updated: 2026-10-10
- Shared benchmarks: 35

## Summary

- They share 35 benchmarks with published results for both. Claude Opus 4.7 scores higher in 10 categories and GPT-4.1 mini 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 23.1.
- The biggest single-benchmark swing is ARC-AGI-1: 93.5% for Claude Opus 4.7 and 3.5% for GPT-4.1 mini.
- GPT-4.1 mini is cheaper at $0.40 / $1.60 per million input/output tokens, against $5 / $25 for Claude Opus 4.7.
- GPT-4.1 mini accepts more context: 1.05M tokens versus 1M.

## Snapshot

| | Claude Opus 4.7 | GPT-4.1 mini |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 58.4 | 33.5 |
| Rank | 17 | 232 |
| Context | 1M | 1.05M |
| Input $/M | $5 | $0.40 |
| Output $/M | $25 | $1.60 |
| Weights | Proprietary | Proprietary |

## Coding

- Claude Opus 4.7: 59.9 (#10)
- GPT-4.1 mini: 30.4 (#286)

| Benchmark | Claude Opus 4.7 | GPT-4.1 mini |
|---|---|---|
| SciCode | 54.5% | 40.4% |
| WeirdML | 76.4% | 37.6% |
| LMArena Coding | 1519 | 1367 |
| SWE-bench Verified | 83.5% | — |
| FrontierCode | 38.5% | — |
| SWE-bench Verified (bash only) | — | 23.9% |
| Aider Polyglot | — | 32.4% |
| LMArena WebDev | 1557 | — |
| GSO | 44.1% | — |
| BigCodeBench Instruct | — | 48.9% |
| MirrorCode | 31.1% | — |
| CadEval | — | 16% |
| ALE-Bench | 1,323 | — |

## Agentic & Tool Use

- Claude Opus 4.7: 47.9 (#8)
- GPT-4.1 mini: 33.0 (#52)

| Benchmark | Claude Opus 4.7 | GPT-4.1 mini |
|---|---|---|
| Terminal-Bench | 80.2% | — |
| APEX-Agents | 49.2% | — |
| Berkeley Function Calling Leaderboard | — | 50.5% |
| 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 mini: 10.9 (#335)

| Benchmark | Claude Opus 4.7 | GPT-4.1 mini |
|---|---|---|
| ARC-AGI-2 | 75.8% | 0% |
| Kagi LLM Benchmark | 80.7% | 48.6% |
| ARC-AGI-1 | 93.5% | 3.5% |
| CritPt | 12% | 0% |
| Chess Puzzles | 30% | 7% |
| LMArena Hard Prompts | 1507 | 1349 |
| Mystery Game Puzzles | 28% | 7% |
| DTBench | 94.7% | 68.8% |
| LMCA | 52.2% | 21.1% |
| Epoch Capabilities Index | 156.39 | 135.01 |
| SimpleBench | 61.7% | — |
| NYT Connections (extended) | 39% | — |
| Thematic Generalization | 72.8% | — |
| EBR-Bench | 19% | — |
| ForecastBench | 60.3 | — |

## Math

- Claude Opus 4.7: 66.5 (#20)
- GPT-4.1 mini: 23.1 (#264)

| Benchmark | Claude Opus 4.7 | GPT-4.1 mini |
|---|---|---|
| FrontierMath (Tiers 1-3) | 70.2% | 6.7% |
| OTIS Mock AIME 2024-2025 | 97.8% | 44.7% |
| LMArena Math | 1499 | 1343 |
| FrontierMath (Feb 2025 set) | 43.8% | 4.5% |
| FrontierMath Tier 4 | 31.7% | — |
| MathArena Final-Answer Competitions | 73.6% | — |
| ProofBench | 54% | — |
| Omni-MATH | — | 49.1% |
| MATH Level 5 | — | 87.3% |
| FrontierMath Tier 4 (v1) | 22.9% | — |

## Knowledge

- Claude Opus 4.7: 62.6 (#20)
- GPT-4.1 mini: 34.7 (#183)

| Benchmark | Claude Opus 4.7 | GPT-4.1 mini |
|---|---|---|
| GPQA Diamond | 90.2% | 65.8% |
| SimpleQA Verified | 51.7% | 12.7% |
| LMArena Expert | 1521 | 1338 |
| Humanity's Last Exam | 36.2% | — |
| MMLU-Pro | — | 78.3% |
| Vectara Hallucination Rate | 12% | — |
| GPQA (HELM) | — | 61.4% |

## Multimodal

- Claude Opus 4.7: 41.5 (#29)
- GPT-4.1 mini: 35.2 (#77)

| Benchmark | Claude Opus 4.7 | GPT-4.1 mini |
|---|---|---|
| LMArena Vision | 1317 | 1181 |
| Blueprint-Bench 2 | 24.5% | — |
| Furniture Assembly | 33.3% | — |
| LMArena Document | 1495 | — |

## Multilingual

- Claude Opus 4.7: 57.5 (#9)
- GPT-4.1 mini: 45.9 (#161)

| Benchmark | Claude Opus 4.7 | GPT-4.1 mini |
|---|---|---|
| LMArena Non-English | 1481 | 1318 |
| LMArena Chinese | 1530 | 1329 |
| LMArena French | 1505 | 1357 |
| LMArena German | 1494 | 1349 |
| LMArena Japanese | 1472 | 1291 |
| LMArena Korean | 1466 | 1298 |
| LMArena Russian | 1494 | 1324 |
| LMArena Spanish | 1497 | 1319 |

## Instruction Following

- Claude Opus 4.7: 78.6 (#9)
- GPT-4.1 mini: 73.9 (#113)

| Benchmark | Claude Opus 4.7 | GPT-4.1 mini |
|---|---|---|
| LMArena Instruction Following | 1498 | 1332 |
| IFEval | — | 90.4% |

## Long Context

- Claude Opus 4.7: 46.1 (#24)
- GPT-4.1 mini: 31.8 (#270)

| Benchmark | Claude Opus 4.7 | GPT-4.1 mini |
|---|---|---|
| LMArena Longer Query | 1505 | 1344 |
| Fiction.LiveBench | — | 44.4% |

## Writing & Preference

- Claude Opus 4.7: 75.3 (#8)
- GPT-4.1 mini: 48.8 (#193)

| Benchmark | Claude Opus 4.7 | GPT-4.1 mini |
|---|---|---|
| LMArena Text | 1491 | 1341 |
| LMArena Creative Writing | 1486 | 1300 |
| EQ-Bench Creative Writing | 1914 | 1147 |
| LMArena Multi-Turn | 1506 | 1354 |
| WildBench | — | 83.8% |
| EQ-Bench 4 | 1311 | — |

## FAQ

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

Claude Opus 4.7 is the stronger model overall, scoring 58.4 to 33.5 on the Noometry Index. GPT-4.1 mini costs 14× 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 mini?

GPT-4.1 mini is cheaper. It lists at $0.40 per million input tokens and $1.60 per million output tokens; Claude Opus 4.7 lists at $5 and $25.

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

Claude Opus 4.7 scores higher on coding benchmarks: 59.9 versus 30.4 in the Noometry coding category.

### Which has the bigger context window?

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

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

35 benchmarks have published results for both models. Claude Opus 4.7 has 66 scored results on Noometry and GPT-4.1 mini has 47.