# Claude Opus 4.6 vs GPT-6.1 Sol

> GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 58.2 on the Noometry Index.

- Canonical page: https://noometry.com/compare/claude-opus-4-6-vs-gpt-6-1-sol
- Last updated: 2026-10-12
- Shared benchmarks: 30

## Summary

- They share 30 benchmarks with published results for both. Claude Opus 4.6 scores higher in 5 categories and GPT-6.1 Sol in 5 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6.1 Sol leads 93.7 to 63.0.
- The biggest single-benchmark swing is FrontierMath Tier 4: 26.8% for Claude Opus 4.6 and 100% for GPT-6.1 Sol.
- GPT-6.1 Sol is cheaper at $2 / $10 per million input/output tokens, against $5 / $25 for Claude Opus 4.6.
- GPT-6.1 Sol accepts more context: 1.05M tokens versus 1M.

## Snapshot

| | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 58.2 | 65.6 |
| Rank | 20 | 6 |
| Context | 1M | 1.05M |
| Input $/M | $5 | $2 |
| Output $/M | $25 | $10 |
| Weights | Proprietary | Proprietary |

## Coding

- Claude Opus 4.6: 57.2 (#20)
- GPT-6.1 Sol: 63.2 (#8)

| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| FrontierCode | 26.6% | 50.2% |
| LMArena WebDev | 1547 | 1755 |
| LMArena Coding | 1536 | 1487 |
| SWE-bench Verified | 78.7% | — |
| DeepSWE | — | 75.2% |
| SWE-bench Verified (bash only) | 75.6% | — |
| SWE-bench Multilingual | 72% | — |
| SciCode | — | 55.8% |
| GSO | 41.2% | — |
| WeirdML | 78% | — |
| ALE-Bench | 996.5 | — |
| AlgoTune | 1.47 | — |

## Agentic & Tool Use

- Claude Opus 4.6: 51.1 (#4)
- GPT-6.1 Sol: 39.6 (#26)

| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| APEX-Agents | 46.3% | 60% |
| Terminal-Bench | 79.8% | — |
| Remote Labor Index | 4.2% | — |
| τ²-bench Banking | 27.3% | — |
| Cybench | 93% | — |
| DeepResearch Bench | 55.3% | — |
| GBAEval | 44.1% | — |
| GDP.pdf | — | 32% |
| LMArena Search | 1253 | — |
| METR Time Horizons | 78.9% | — |
| Vending-Bench 2 | 8,018 | — |

## Reasoning

- Claude Opus 4.6: 57.8 (#23)
- GPT-6.1 Sol: 81.9 (#2)

| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| ARC-AGI-2 | 69.2% | 94.2% |
| NYT Connections (extended) | 92.1% | 95.5% |
| ARC-AGI-1 | 94% | 98.5% |
| Chess Puzzles | 17% | 61% |
| EBR-Bench | 12.7% | 54.3% |
| LMArena Hard Prompts | 1527 | 1466 |
| Mystery Game Puzzles | 25% | 80% |
| Epoch Capabilities Index | 155.24 | 166.09 |
| SimpleBench | 67.6% | — |
| Kagi LLM Benchmark | 83.6% | — |
| CritPt | — | 31.7% |
| EnigmaEval | 7.6% | — |
| Thematic Generalization | 80.6% | — |
| DTBench | 91.2% | — |
| LMCA | 55.8% | — |
| ForecastBench | 60 | — |

## Math

- Claude Opus 4.6: 63.0 (#31)
- GPT-6.1 Sol: 93.7 (#1)

| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| FrontierMath (Tiers 1-3) | 66% | 93.7% |
| FrontierMath Tier 4 | 26.8% | 100% |
| OTIS Mock AIME 2024-2025 | 94.4% | 100% |
| ProofBench | 50% | 99% |
| LMArena Math | 1519 | 1464 |
| MathArena Final-Answer Competitions | 78.5% | — |
| FrontierMath (Feb 2025 set) | 40.7% | — |
| FrontierMath Tier 4 (v1) | 22.9% | — |

## Knowledge

- Claude Opus 4.6: 61.9 (#26)
- GPT-6.1 Sol: 71.8 (#4)

| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| GPQA Diamond | 90.5% | 95.4% |
| SimpleQA Verified | 47% | 73.9% |
| LMArena Expert | 1546 | 1502 |
| Humanity's Last Exam | 34.4% | — |
| Vectara Hallucination Rate | 12.2% | — |

## Multimodal

- Claude Opus 4.6: 37.3 (#74)
- GPT-6.1 Sol: 52.7 (#5)

| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| LMArena Vision | 1316 | 1288 |
| Furniture Assembly | 28.3% | 80% |
| LMArena Document | 1507 | — |

## Multilingual

- Claude Opus 4.6: 57.9 (#6)
- GPT-6.1 Sol: 54.3 (#46)

| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| LMArena Non-English | 1489 | 1438 |
| LMArena Chinese | 1551 | 1477 |
| LMArena Russian | 1497 | 1455 |
| LMArena French | 1513 | — |
| LMArena German | 1502 | — |
| LMArena Japanese | 1484 | — |
| LMArena Korean | 1464 | — |
| LMArena Spanish | 1510 | — |

## Instruction Following

- Claude Opus 4.6: 79.5 (#4)
- GPT-6.1 Sol: 77.0 (#29)

| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| LMArena Instruction Following | 1523 | 1468 |

## Long Context

- Claude Opus 4.6: 48.1 (#13)
- GPT-6.1 Sol: 44.9 (#54)

| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| LMArena Longer Query | 1520 | 1465 |
| CL-bench | 20.7% | — |
| CL-bench Life | 17% | — |

## Writing & Preference

- Claude Opus 4.6: 73.5 (#10)
- GPT-6.1 Sol: 63.6 (#63)

| Benchmark | Claude Opus 4.6 | GPT-6.1 Sol |
|---|---|---|
| LMArena Text | 1503 | 1447 |
| LMArena Creative Writing | 1505 | 1432 |
| LMArena Multi-Turn | 1513 | 1449 |
| EQ-Bench Creative Writing | 1809 | — |
| EQ-Bench 4 | 1223 | — |

## FAQ

### Is Claude Opus 4.6 better than GPT-6.1 Sol?

GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 58.2 on the Noometry Index.

### Which is cheaper, Claude Opus 4.6 or GPT-6.1 Sol?

GPT-6.1 Sol is cheaper. It lists at $2 per million input tokens and $10 per million output tokens; Claude Opus 4.6 lists at $5 and $25.

### Is Claude Opus 4.6 or GPT-6.1 Sol better for coding?

GPT-6.1 Sol scores higher on coding benchmarks: 63.2 versus 57.2 in the Noometry coding category.

### Which has the bigger context window?

GPT-6.1 Sol does, with 1.05M tokens against 1M.

### How many benchmarks do Claude Opus 4.6 and GPT-6.1 Sol share?

30 benchmarks have published results for both models. Claude Opus 4.6 has 68 scored results on Noometry and GPT-6.1 Sol has 34.