Model comparison
Claude Opus 4.6 vs GPT-5.5 Pro
GPT-5.5 Pro is the stronger model overall, scoring 64.3 to 58.2 on the Noometry Index. Claude Opus 4.6 costs 6.8× less per token, which makes it the better buy when GPT-5.5 Pro's lead doesn't matter for your workload.
Last verified . 13 shared benchmarks.
Summary
- They share 13 benchmarks with published results for both. Claude Opus 4.6 scores higher in 0 categories and GPT-5.5 Pro in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.5 Pro leads 84.0 to 63.0.
- The biggest single-benchmark swing is FrontierMath Tier 4: 26.8% for Claude Opus 4.6 and 78% for GPT-5.5 Pro.
- Claude Opus 4.6 is cheaper at $5 / $25 per million input/output tokens, against $30 / $180 for GPT-5.5 Pro.
- GPT-5.5 Pro accepts more context: 1.05M tokens versus 1M.
Side by side
| Claude Opus 4.6 | GPT-5.5 Pro | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 58.2 | 64.3 |
| Released | 2026-02-04 | 2026-04-23 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 1.05M |
| Max output | 128K | 128K |
| Input $ / M tokens | $5 | $30 |
| Output $ / M tokens | $25 | $180 |
| Results tracked | 68 | 14 |
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Category by category
Coding Not comparable
Claude Opus 4.6: 57.2 (#20), GPT-5.5 Pro: —
| Benchmark | Claude Opus 4.6 | GPT-5.5 Pro |
|---|---|---|
| SWE-bench Verified | 78.7% | — |
| FrontierCode | 26.6% | — |
| SWE-bench Verified (bash only) | 75.6% | — |
| LMArena WebDev | 1547 | — |
| SWE-bench Multilingual | 72% | — |
| GSO | 41.2% | — |
| WeirdML | 78% | — |
| LMArena Coding | 1536 | — |
| ALE-Bench | 996.5 | — |
| AlgoTune | 1.47 | — |
Agentic & Tool Use Not comparable
Claude Opus 4.6: 51.1 (#4), GPT-5.5 Pro: —
| Benchmark | Claude Opus 4.6 | GPT-5.5 Pro |
|---|---|---|
| Terminal-Bench | 79.8% | — |
| APEX-Agents | 46.3% | — |
| Remote Labor Index | 4.2% | — |
| τ²-bench Banking | 27.3% | — |
| Cybench | 93% | — |
| DeepResearch Bench | 55.3% | — |
| GBAEval | 44.1% | — |
| LMArena Search | 1253 | — |
| METR Time Horizons | 78.9% | — |
| Vending-Bench 2 | 8,018 | — |
Reasoning GPT-5.5 Pro leads
Claude Opus 4.6: 57.8 (#23), GPT-5.5 Pro: 73.3 (#10)
| Benchmark | Claude Opus 4.6 | GPT-5.5 Pro |
|---|---|---|
| ARC-AGI-2 | 69.2% | 84.6% |
| SimpleBench | 67.6% | 76.9% |
| ARC-AGI-1 | 94% | 96.5% |
| Chess Puzzles | 17% | 64% |
| DTBench | 91.2% | 96% |
| LMCA | 55.8% | 53.9% |
| Epoch Capabilities Index | 155.24 | 162.07 |
| Kagi LLM Benchmark | 83.6% | — |
| NYT Connections (extended) | 92.1% | — |
| CritPt | — | 30.6% |
| EnigmaEval | 7.6% | — |
| Thematic Generalization | 80.6% | — |
| EBR-Bench | 12.7% | — |
| LMArena Hard Prompts | 1527 | — |
| Mystery Game Puzzles | 25% | — |
| ForecastBench | 60 | — |
Math GPT-5.5 Pro leads
Claude Opus 4.6: 63.0 (#31), GPT-5.5 Pro: 84.0 (#10)
| Benchmark | Claude Opus 4.6 | GPT-5.5 Pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | 66% | 87.7% |
| FrontierMath Tier 4 | 26.8% | 78% |
| OTIS Mock AIME 2024-2025 | 94.4% | 100% |
| FrontierMath (Feb 2025 set) | 40.7% | 52.4% |
| FrontierMath Tier 4 (v1) | 22.9% | 39.6% |
| MathArena Final-Answer Competitions | 78.5% | — |
| ProofBench | 50% | — |
| LMArena Math | 1519 | — |
Knowledge GPT-5.5 Pro leads
Claude Opus 4.6: 61.9 (#26), GPT-5.5 Pro: 64.1 (#19)
| Benchmark | Claude Opus 4.6 | GPT-5.5 Pro |
|---|---|---|
| GPQA Diamond | 90.5% | 93.9% |
| Humanity's Last Exam | 34.4% | — |
| SimpleQA Verified | 47% | — |
| Vectara Hallucination Rate | 12.2% | — |
| LMArena Expert | 1546 | — |
Multimodal Not comparable
Claude Opus 4.6: 37.3 (#74), GPT-5.5 Pro: —
| Benchmark | Claude Opus 4.6 | GPT-5.5 Pro |
|---|---|---|
| LMArena Vision | 1316 | — |
| Furniture Assembly | 28.3% | — |
| LMArena Document | 1507 | — |
Multilingual Not comparable
Claude Opus 4.6: 57.9 (#6), GPT-5.5 Pro: —
| Benchmark | Claude Opus 4.6 | GPT-5.5 Pro |
|---|---|---|
| LMArena Non-English | 1489 | — |
| LMArena Chinese | 1551 | — |
| LMArena French | 1513 | — |
| LMArena German | 1502 | — |
| LMArena Japanese | 1484 | — |
| LMArena Korean | 1464 | — |
| LMArena Russian | 1497 | — |
| LMArena Spanish | 1510 | — |
Instruction Following Not comparable
Claude Opus 4.6: 79.5 (#4), GPT-5.5 Pro: —
| Benchmark | Claude Opus 4.6 | GPT-5.5 Pro |
|---|---|---|
| LMArena Instruction Following | 1523 | — |
Long Context Not comparable
Claude Opus 4.6: 48.1 (#13), GPT-5.5 Pro: —
| Benchmark | Claude Opus 4.6 | GPT-5.5 Pro |
|---|---|---|
| CL-bench | 20.7% | — |
| CL-bench Life | 17% | — |
| LMArena Longer Query | 1520 | — |
Writing & Preference Not comparable
Claude Opus 4.6: 73.5 (#10), GPT-5.5 Pro: —
| Benchmark | Claude Opus 4.6 | GPT-5.5 Pro |
|---|---|---|
| LMArena Text | 1503 | — |
| LMArena Creative Writing | 1505 | — |
| EQ-Bench Creative Writing | 1809 | — |
| EQ-Bench 4 | 1223 | — |
| LMArena Multi-Turn | 1513 | — |
Frequently asked questions
Is Claude Opus 4.6 better than GPT-5.5 Pro?
GPT-5.5 Pro is the stronger model overall, scoring 64.3 to 58.2 on the Noometry Index. Claude Opus 4.6 costs 6.8× less per token, which makes it the better buy when GPT-5.5 Pro's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 4.6 or GPT-5.5 Pro?
Claude Opus 4.6 is cheaper. It lists at $5 per million input tokens and $25 per million output tokens; GPT-5.5 Pro lists at $30 and $180.
Which has the bigger context window?
GPT-5.5 Pro does, with 1.05M tokens against 1M.
How many benchmarks do Claude Opus 4.6 and GPT-5.5 Pro share?
13 benchmarks have published results for both models. Claude Opus 4.6 has 68 scored results on Noometry and GPT-5.5 Pro has 14.