Model comparison
Claude Opus 5.5 vs GPT-6 Sol
Claude Opus 5.5 is the stronger model overall, scoring 68.6 to 61.8 on the Noometry Index. GPT-6 Sol costs 2.0× less per token, which makes it the better buy when Claude Opus 5.5's lead doesn't matter for your workload.
Last verified . 40 shared benchmarks.
Summary
- They share 40 benchmarks with published results for both. Claude Opus 5.5 scores higher in 10 categories and GPT-6 Sol in 0 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in coding, where Claude Opus 5.5 leads 71.9 to 60.1.
- The biggest single-benchmark swing is Furniture Assembly: 83.3% for Claude Opus 5.5 and 58.3% for GPT-6 Sol.
- GPT-6 Sol is cheaper at $2 / $10 per million input/output tokens, against $4 / $20 for Claude Opus 5.5.
- GPT-6 Sol accepts more context: 1.05M tokens versus 1M.
Side by side
| Claude Opus 5.5 | GPT-6 Sol | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 68.6 | 61.8 |
| Released | 2026-09-22 | 2026-09-22 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 1.05M |
| Max output | 128K | 128K |
| Input $ / M tokens | $4 | $2 |
| Output $ / M tokens | $20 | $10 |
| Results tracked | 44 | 45 |
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Category by category
Coding Claude Opus 5.5 leads
Claude Opus 5.5: 71.9 (#3), GPT-6 Sol: 60.1 (#11)
| Benchmark | Claude Opus 5.5 | GPT-6 Sol |
|---|---|---|
| FrontierCode | 54.6% | 49.3% |
| LMArena WebDev | 1813 | 1688 |
| SciCode | 66.9% | 57.6% |
| LMArena Coding | 1547 | 1447 |
| ALE-Bench | 2,147 | 2,462 |
| DeepSWE | — | 68.8% |
| CursorBench | 57.8% | — |
| FrontierSWE | 62.3% | — |
| MirrorCode | 77.4% | — |
Agentic & Tool Use Claude Opus 5.5 leads
Claude Opus 5.5: 45.3 (#15), GPT-6 Sol: 37.2 (#36)
| Benchmark | Claude Opus 5.5 | GPT-6 Sol |
|---|---|---|
| APEX-Agents | 73.5% | 54.3% |
| GDP.pdf | 30.6% | 26.4% |
| Vending-Bench 2 | 9,235 | 14,428 |
Reasoning Claude Opus 5.5 leads
Claude Opus 5.5: 80.2 (#3), GPT-6 Sol: 74.0 (#9)
| Benchmark | Claude Opus 5.5 | GPT-6 Sol |
|---|---|---|
| ARC-AGI-2 | 93.3% | 89.6% |
| NYT Connections (extended) | 88.5% | 90.1% |
| ARC-AGI-1 | 98.5% | 95.5% |
| CritPt | 31.7% | 30.9% |
| EBR-Bench | 71.4% | 53.3% |
| LMArena Hard Prompts | 1535 | 1418 |
| Mystery Game Puzzles | 71% | 56% |
| DTBench | 98.9% | 97.3% |
| LMCA | 68.2% | 59.1% |
| Epoch Capabilities Index | 167.33 | 162.72 |
Math Claude Opus 5.5 leads
Claude Opus 5.5: 91.8 (#3), GPT-6 Sol: 87.2 (#7)
| Benchmark | Claude Opus 5.5 | GPT-6 Sol |
|---|---|---|
| FrontierMath (Tiers 1-3) | 91.2% | 89.8% |
| FrontierMath Tier 4 | 95% | 90% |
| OTIS Mock AIME 2024-2025 | 100% | 100% |
| ProofBench | 100% | 83% |
| LMArena Math | 1506 | 1402 |
| FrontierMath Erdős | 2.9% | — |
Knowledge Claude Opus 5.5 leads
Claude Opus 5.5: 66.4 (#10), GPT-6 Sol: 64.8 (#15)
| Benchmark | Claude Opus 5.5 | GPT-6 Sol |
|---|---|---|
| GPQA Diamond | 90.6% | 94.3% |
| SimpleQA Verified | 72.2% | 60.7% |
| LMArena Expert | 1547 | 1439 |
| Vectara Hallucination Rate | — | 6.5% |
Multimodal Claude Opus 5.5 leads
Claude Opus 5.5: 57.8 (#1), GPT-6 Sol: 47.6 (#10)
| Benchmark | Claude Opus 5.5 | GPT-6 Sol |
|---|---|---|
| LMArena Vision | 1321 | 1245 |
| Blueprint-Bench 2 | 51.2% | 36.9% |
| Furniture Assembly | 83.3% | 58.3% |
Multilingual Claude Opus 5.5 leads
Claude Opus 5.5: 59.1 (#2), GPT-6 Sol: 50.5 (#118)
| Benchmark | Claude Opus 5.5 | GPT-6 Sol |
|---|---|---|
| LMArena Non-English | 1507 | 1385 |
| LMArena Chinese | 1588 | 1405 |
| LMArena French | 1514 | 1410 |
| LMArena Russian | 1520 | 1401 |
| LMArena Spanish | 1507 | 1384 |
| LMArena German | — | 1390 |
| LMArena Japanese | — | 1385 |
| LMArena Korean | — | 1341 |
Instruction Following Claude Opus 5.5 leads
Claude Opus 5.5: 80.0 (#3), GPT-6 Sol: 74.5 (#94)
| Benchmark | Claude Opus 5.5 | GPT-6 Sol |
|---|---|---|
| LMArena Instruction Following | 1537 | 1412 |
Long Context Claude Opus 5.5 leads
Claude Opus 5.5: 47.1 (#19), GPT-6 Sol: 43.1 (#108)
| Benchmark | Claude Opus 5.5 | GPT-6 Sol |
|---|---|---|
| LMArena Longer Query | 1532 | 1411 |
Writing & Preference Claude Opus 5.5 leads
Claude Opus 5.5: 78.2 (#3), GPT-6 Sol: 71.9 (#18)
| Benchmark | Claude Opus 5.5 | GPT-6 Sol |
|---|---|---|
| LMArena Text | 1515 | 1395 |
| LMArena Creative Writing | 1533 | 1378 |
| EQ-Bench Creative Writing | 2050 | 2125 |
| LMArena Multi-Turn | 1499 | 1412 |
Frequently asked questions
Is Claude Opus 5.5 better than GPT-6 Sol?
Claude Opus 5.5 is the stronger model overall, scoring 68.6 to 61.8 on the Noometry Index. GPT-6 Sol costs 2.0× less per token, which makes it the better buy when Claude Opus 5.5's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 5.5 or GPT-6 Sol?
GPT-6 Sol is cheaper. It lists at $2 per million input tokens and $10 per million output tokens; Claude Opus 5.5 lists at $4 and $20.
Is Claude Opus 5.5 or GPT-6 Sol better for coding?
Claude Opus 5.5 scores higher on coding benchmarks: 71.9 versus 60.1 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Sol does, with 1.05M tokens against 1M.
How many benchmarks do Claude Opus 5.5 and GPT-6 Sol share?
40 benchmarks have published results for both models. Claude Opus 5.5 has 44 scored results on Noometry and GPT-6 Sol has 45.