Model comparison
Claude Opus 5.5 vs GPT-6 Astra
GPT-6 Astra is the stronger model overall, scoring 70.8 to 68.6 on the Noometry Index. Claude Opus 5.5 costs 2.5× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.
Last verified . 43 shared benchmarks.
Summary
- They share 43 benchmarks with published results for both. Claude Opus 5.5 scores higher in 5 categories and GPT-6 Astra in 5 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-6 Astra leads 75.3 to 66.4.
- The biggest single-benchmark swing is MirrorCode: 77.4% for Claude Opus 5.5 and 46.7% for GPT-6 Astra.
- Claude Opus 5.5 is cheaper at $4 / $20 per million input/output tokens, against $10 / $50 for GPT-6 Astra.
- GPT-6 Astra accepts more context: 1.05M tokens versus 1M.
Side by side
| Claude Opus 5.5 | GPT-6 Astra | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 68.6 | 70.8 |
| Released | 2026-09-22 | 2026-09-03 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 1.05M |
| Max output | 128K | 128K |
| Input $ / M tokens | $4 | $10 |
| Output $ / M tokens | $20 | $50 |
| Results tracked | 44 | 56 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-6 Astra leads
Claude Opus 5.5: 71.9 (#3), GPT-6 Astra: 73.7 (#2)
| Benchmark | Claude Opus 5.5 | GPT-6 Astra |
|---|---|---|
| FrontierCode | 54.6% | 53.3% |
| LMArena WebDev | 1813 | 1786 |
| FrontierSWE | 62.3% | 65.5% |
| SciCode | 66.9% | 56.5% |
| LMArena Coding | 1547 | 1487 |
| MirrorCode | 77.4% | 46.7% |
| ALE-Bench | 2,147 | 2,951 |
| DeepSWE | — | 74.1% |
| CursorBench | 57.8% | — |
| GSO | — | 79.4% |
| WeirdML | — | 93.6% |
Agentic & Tool Use GPT-6 Astra leads
Claude Opus 5.5: 45.3 (#15), GPT-6 Astra: 52.9 (#3)
| Benchmark | Claude Opus 5.5 | GPT-6 Astra |
|---|---|---|
| APEX-Agents | 73.5% | 64.7% |
| GDP.pdf | 30.6% | 34.2% |
| Vending-Bench 2 | 9,235 | 15,515 |
| Remote Labor Index | — | 20.8% |
| BALROG | — | 68.3% |
Reasoning GPT-6 Astra leads
Claude Opus 5.5: 80.2 (#3), GPT-6 Astra: 85.1 (#1)
| Benchmark | Claude Opus 5.5 | GPT-6 Astra |
|---|---|---|
| ARC-AGI-2 | 93.3% | 95% |
| NYT Connections (extended) | 88.5% | 98.1% |
| ARC-AGI-1 | 98.5% | 98.5% |
| CritPt | 31.7% | 31.7% |
| EBR-Bench | 71.4% | 76.2% |
| LMArena Hard Prompts | 1535 | 1462 |
| Mystery Game Puzzles | 71% | 84% |
| DTBench | 98.9% | 97.3% |
| LMCA | 68.2% | 64.4% |
| Epoch Capabilities Index | 167.33 | 166.45 |
| Chess Puzzles | — | 72% |
| Bench to the Future 3 | — | 0.14 |
Math GPT-6 Astra leads
Claude Opus 5.5: 91.8 (#3), GPT-6 Astra: 93.5 (#2)
| Benchmark | Claude Opus 5.5 | GPT-6 Astra |
|---|---|---|
| FrontierMath (Tiers 1-3) | 91.2% | 93.7% |
| FrontierMath Tier 4 | 95% | 97.6% |
| OTIS Mock AIME 2024-2025 | 100% | 100% |
| ProofBench | 100% | 99% |
| LMArena Math | 1506 | 1465 |
| FrontierMath Erdős | 2.9% | 2.9% |
Knowledge GPT-6 Astra leads
Claude Opus 5.5: 66.4 (#10), GPT-6 Astra: 75.3 (#1)
| Benchmark | Claude Opus 5.5 | GPT-6 Astra |
|---|---|---|
| GPQA Diamond | 90.6% | 95.8% |
| SimpleQA Verified | 72.2% | 75.6% |
| LMArena Expert | 1547 | 1483 |
| Humanity's Last Exam | — | 54.8% |
| Vectara Hallucination Rate | — | 8.7% |
Multimodal Claude Opus 5.5 leads
Claude Opus 5.5: 57.8 (#1), GPT-6 Astra: 55.0 (#3)
| Benchmark | Claude Opus 5.5 | GPT-6 Astra |
|---|---|---|
| LMArena Vision | 1321 | 1281 |
| Blueprint-Bench 2 | 51.2% | 49.7% |
| Furniture Assembly | 83.3% | 80% |
| LMArena Document | — | 1468 |
Multilingual Claude Opus 5.5 leads
Claude Opus 5.5: 59.1 (#2), GPT-6 Astra: 53.7 (#61)
| Benchmark | Claude Opus 5.5 | GPT-6 Astra |
|---|---|---|
| LMArena Non-English | 1507 | 1430 |
| LMArena Chinese | 1588 | 1484 |
| LMArena French | 1514 | 1456 |
| LMArena Russian | 1520 | 1436 |
| LMArena Spanish | 1507 | 1407 |
| LMArena German | — | 1440 |
| LMArena Japanese | — | 1379 |
| LMArena Korean | — | 1426 |
Instruction Following Claude Opus 5.5 leads
Claude Opus 5.5: 80.0 (#3), GPT-6 Astra: 76.3 (#44)
| Benchmark | Claude Opus 5.5 | GPT-6 Astra |
|---|---|---|
| LMArena Instruction Following | 1537 | 1450 |
Long Context Claude Opus 5.5 leads
Claude Opus 5.5: 47.1 (#19), GPT-6 Astra: 44.5 (#62)
| Benchmark | Claude Opus 5.5 | GPT-6 Astra |
|---|---|---|
| LMArena Longer Query | 1532 | 1456 |
Writing & Preference Claude Opus 5.5 leads
Claude Opus 5.5: 78.2 (#3), GPT-6 Astra: 75.3 (#7)
| Benchmark | Claude Opus 5.5 | GPT-6 Astra |
|---|---|---|
| LMArena Text | 1515 | 1441 |
| LMArena Creative Writing | 1533 | 1418 |
| EQ-Bench Creative Writing | 2050 | 2173 |
| LMArena Multi-Turn | 1499 | 1448 |
Frequently asked questions
Is Claude Opus 5.5 better than GPT-6 Astra?
GPT-6 Astra is the stronger model overall, scoring 70.8 to 68.6 on the Noometry Index. Claude Opus 5.5 costs 2.5× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 5.5 or GPT-6 Astra?
Claude Opus 5.5 is cheaper. It lists at $4 per million input tokens and $20 per million output tokens; GPT-6 Astra lists at $10 and $50.
Is Claude Opus 5.5 or GPT-6 Astra better for coding?
GPT-6 Astra scores higher on coding benchmarks: 73.7 versus 71.9 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Astra does, with 1.05M tokens against 1M.
How many benchmarks do Claude Opus 5.5 and GPT-6 Astra share?
43 benchmarks have published results for both models. Claude Opus 5.5 has 44 scored results on Noometry and GPT-6 Astra has 56.