Model comparison
Claude Opus 4.1 vs GPT-5.6 Sol
GPT-5.6 Sol is the stronger model overall, scoring 65.0 to 41.0 on the Noometry Index.
Last verified . 34 shared benchmarks.
Summary
- They share 34 benchmarks with published results for both. Claude Opus 4.1 scores higher in 0 categories and GPT-5.6 Sol in 10 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Sol leads 85.6 to 22.3.
- The biggest single-benchmark swing is FrontierMath Tier 4: 2.4% for Claude Opus 4.1 and 82.9% for GPT-5.6 Sol.
- GPT-5.6 Sol is cheaper at $4 / $20 per million input/output tokens, against $15 / $75 for Claude Opus 4.1.
- GPT-5.6 Sol accepts more context: 1.05M tokens versus 200K.
Side by side
| Claude Opus 4.1 | GPT-5.6 Sol | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 41.0 | 65.0 |
| Released | 2025-08-05 | 2026-07-09 |
| Weights | Proprietary | Proprietary |
| Context window | 200K | 1.05M |
| Max output | 32K | 128K |
| Input $ / M tokens | $15 | $4 |
| Output $ / M tokens | $75 | $20 |
| Results tracked | 48 | 65 |
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Category by category
Coding GPT-5.6 Sol leads
Claude Opus 4.1: 44.4 (#73), GPT-5.6 Sol: 65.1 (#7)
| Benchmark | Claude Opus 4.1 | GPT-5.6 Sol |
|---|---|---|
| LMArena WebDev | 1390 | 1618 |
| WeirdML | 45.9% | 89.4% |
| LMArena Coding | 1479 | 1498 |
| ALE-Bench | 674.77 | 2,177 |
| SWE-bench Verified | 73.3% | — |
| DeepSWE | — | 72.7% |
| FrontierCode | — | 47.5% |
| CursorBench | — | 41.7% |
| FrontierSWE | — | 32.2% |
| SciCode | — | 57.1% |
| GSO | — | 76.5% |
| MirrorCode | — | 20% |
| AlgoTune | 1.34 | — |
Agentic & Tool Use GPT-5.6 Sol leads
Claude Opus 4.1: 35.0 (#41), GPT-5.6 Sol: 50.3 (#7)
| Benchmark | Claude Opus 4.1 | GPT-5.6 Sol |
|---|---|---|
| LMArena Search | 1148 | 1257 |
| Terminal-Bench | 38% | — |
| APEX-Agents | — | 51.4% |
| OSWorld 2.0 | — | 27.3% |
| GDPval | 43.6% | — |
| τ²-bench Banking | — | 46.9% |
| Cybench | 42% | — |
| DeepResearch Bench | 48.3% | — |
| PostTrainBench | — | 36.2% |
| BALROG | — | 60% |
| GBAEval | — | 52.6% |
| GDP.pdf | — | 30.7% |
| METR Time Horizons | 66.8% | — |
| Vending-Bench 2 | — | 9,619 |
Reasoning GPT-5.6 Sol leads
Claude Opus 4.1: 32.2 (#76), GPT-5.6 Sol: 74.8 (#8)
| Benchmark | Claude Opus 4.1 | GPT-5.6 Sol |
|---|---|---|
| SimpleBench | 60% | 71.7% |
| Chess Puzzles | 7% | 64% |
| EnigmaEval | 7.2% | 37.1% |
| EBR-Bench | 7.9% | 44.8% |
| LMArena Hard Prompts | 1443 | 1484 |
| Mystery Game Puzzles | 21% | 58% |
| DTBench | 80% | 96% |
| LMCA | 37.1% | 59.2% |
| Epoch Capabilities Index | 144.12 | 161.66 |
| ARC-AGI-2 | — | 92.5% |
| Kagi LLM Benchmark | — | 67% |
| NYT Connections (extended) | — | 93.8% |
| ARC-AGI-1 | — | 97.5% |
| CritPt | — | 32.3% |
| Surface Evolver Bench | — | 93.1% |
| Bench to the Future 3 | — | 0.14 |
| ForecastBench | 62 | — |
Math GPT-5.6 Sol leads
Claude Opus 4.1: 22.3 (#277), GPT-5.6 Sol: 85.6 (#9)
| Benchmark | Claude Opus 4.1 | GPT-5.6 Sol |
|---|---|---|
| FrontierMath (Tiers 1-3) | 12.6% | 89.1% |
| FrontierMath Tier 4 | 2.4% | 82.9% |
| OTIS Mock AIME 2024-2025 | 68.9% | 100% |
| LMArena Math | 1431 | 1474 |
| ProofBench | — | 83% |
| FrontierMath (Feb 2025 set) | 7.2% | — |
| FrontierMath Erdős | — | 0% |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge GPT-5.6 Sol leads
Claude Opus 4.1: 42.0 (#101), GPT-5.6 Sol: 64.3 (#18)
| Benchmark | Claude Opus 4.1 | GPT-5.6 Sol |
|---|---|---|
| GPQA Diamond | 77.3% | 93.5% |
| Vectara Hallucination Rate | 11.8% | 12.4% |
| LMArena Expert | 1439 | 1516 |
| Humanity's Last Exam | 11.5% | — |
| SimpleQA Verified | — | 69.7% |
| Confabulations | 17.1% | — |
Multimodal GPT-5.6 Sol leads
Claude Opus 4.1: 26.8 (#119), GPT-5.6 Sol: 48.6 (#9)
| Benchmark | Claude Opus 4.1 | GPT-5.6 Sol |
|---|---|---|
| LMArena Vision | — | 1281 |
| VPCT | 35% | — |
| Blueprint-Bench 2 | — | 33.6% |
| Furniture Assembly | — | 56.7% |
| LMArena Document | — | 1483 |
Multilingual GPT-5.6 Sol leads
Claude Opus 4.1: 52.0 (#95), GPT-5.6 Sol: 55.3 (#32)
| Benchmark | Claude Opus 4.1 | GPT-5.6 Sol |
|---|---|---|
| LMArena Non-English | 1405 | 1452 |
| LMArena Chinese | 1427 | 1527 |
| LMArena French | 1431 | 1477 |
| LMArena German | 1413 | 1476 |
| LMArena Japanese | 1378 | 1471 |
| LMArena Korean | 1380 | 1442 |
| LMArena Russian | 1422 | 1468 |
| LMArena Spanish | 1448 | 1441 |
Instruction Following GPT-5.6 Sol leads
Claude Opus 4.1: 75.6 (#58), GPT-5.6 Sol: 77.7 (#16)
| Benchmark | Claude Opus 4.1 | GPT-5.6 Sol |
|---|---|---|
| LMArena Instruction Following | 1435 | 1482 |
Long Context Too close to call
Claude Opus 4.1: 44.5 (#63), GPT-5.6 Sol: 45.4 (#42)
| Benchmark | Claude Opus 4.1 | GPT-5.6 Sol |
|---|---|---|
| LMArena Longer Query | 1455 | 1480 |
Writing & Preference GPT-5.6 Sol leads
Claude Opus 4.1: 62.4 (#74), GPT-5.6 Sol: 73.3 (#12)
| Benchmark | Claude Opus 4.1 | GPT-5.6 Sol |
|---|---|---|
| LMArena Text | 1419 | 1457 |
| LMArena Creative Writing | 1412 | 1448 |
| LMArena Multi-Turn | 1444 | 1460 |
| Short-Story Creative Writing | 84.7% | — |
| EQ-Bench Creative Writing | — | 1972 |
| EQ-Bench 4 | — | 1250 |
Frequently asked questions
Is Claude Opus 4.1 better than GPT-5.6 Sol?
GPT-5.6 Sol is the stronger model overall, scoring 65.0 to 41.0 on the Noometry Index.
Which is cheaper, Claude Opus 4.1 or GPT-5.6 Sol?
GPT-5.6 Sol is cheaper. It lists at $4 per million input tokens and $20 per million output tokens; Claude Opus 4.1 lists at $15 and $75.
Is Claude Opus 4.1 or GPT-5.6 Sol better for coding?
GPT-5.6 Sol scores higher on coding benchmarks: 65.1 versus 44.4 in the Noometry coding category.
Which has the bigger context window?
GPT-5.6 Sol does, with 1.05M tokens against 200K.
How many benchmarks do Claude Opus 4.1 and GPT-5.6 Sol share?
34 benchmarks have published results for both models. Claude Opus 4.1 has 48 scored results on Noometry and GPT-5.6 Sol has 65.