Model comparison
Claude Opus 4.1 vs GPT-6 Astra
GPT-6 Astra is the stronger model overall, scoring 70.8 to 41.0 on the Noometry Index.
Last verified . 32 shared benchmarks.
Summary
- They share 32 benchmarks with published results for both. Claude Opus 4.1 scores higher in 0 categories and GPT-6 Astra in 10 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6 Astra leads 93.5 to 22.3.
- The biggest single-benchmark swing is FrontierMath Tier 4: 2.4% for Claude Opus 4.1 and 97.6% for GPT-6 Astra.
- GPT-6 Astra is cheaper at $10 / $50 per million input/output tokens, against $15 / $75 for Claude Opus 4.1.
- GPT-6 Astra accepts more context: 1.05M tokens versus 200K.
Side by side
| Claude Opus 4.1 | GPT-6 Astra | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 41.0 | 70.8 |
| Released | 2025-08-05 | 2026-09-03 |
| Weights | Proprietary | Proprietary |
| Context window | 200K | 1.05M |
| Max output | 32K | 128K |
| Input $ / M tokens | $15 | $10 |
| Output $ / M tokens | $75 | $50 |
| Results tracked | 48 | 56 |
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Category by category
Coding GPT-6 Astra leads
Claude Opus 4.1: 44.4 (#73), GPT-6 Astra: 73.7 (#2)
| Benchmark | Claude Opus 4.1 | GPT-6 Astra |
|---|---|---|
| LMArena WebDev | 1390 | 1786 |
| WeirdML | 45.9% | 93.6% |
| LMArena Coding | 1479 | 1487 |
| ALE-Bench | 674.77 | 2,951 |
| SWE-bench Verified | 73.3% | — |
| DeepSWE | — | 74.1% |
| FrontierCode | — | 53.3% |
| FrontierSWE | — | 65.5% |
| SciCode | — | 56.5% |
| GSO | — | 79.4% |
| MirrorCode | — | 46.7% |
| AlgoTune | 1.34 | — |
Agentic & Tool Use GPT-6 Astra leads
Claude Opus 4.1: 35.0 (#41), GPT-6 Astra: 52.9 (#3)
| Benchmark | Claude Opus 4.1 | GPT-6 Astra |
|---|---|---|
| Terminal-Bench | 38% | — |
| APEX-Agents | — | 64.7% |
| GDPval | 43.6% | — |
| Remote Labor Index | — | 20.8% |
| Cybench | 42% | — |
| DeepResearch Bench | 48.3% | — |
| BALROG | — | 68.3% |
| GDP.pdf | — | 34.2% |
| LMArena Search | 1148 | — |
| METR Time Horizons | 66.8% | — |
| Vending-Bench 2 | — | 15,515 |
Reasoning GPT-6 Astra leads
Claude Opus 4.1: 32.2 (#76), GPT-6 Astra: 85.1 (#1)
| Benchmark | Claude Opus 4.1 | GPT-6 Astra |
|---|---|---|
| Chess Puzzles | 7% | 72% |
| EBR-Bench | 7.9% | 76.2% |
| LMArena Hard Prompts | 1443 | 1462 |
| Mystery Game Puzzles | 21% | 84% |
| DTBench | 80% | 97.3% |
| LMCA | 37.1% | 64.4% |
| Epoch Capabilities Index | 144.12 | 166.45 |
| ARC-AGI-2 | — | 95% |
| SimpleBench | 60% | — |
| NYT Connections (extended) | — | 98.1% |
| ARC-AGI-1 | — | 98.5% |
| CritPt | — | 31.7% |
| EnigmaEval | 7.2% | — |
| Bench to the Future 3 | — | 0.14 |
| ForecastBench | 62 | — |
Math GPT-6 Astra leads
Claude Opus 4.1: 22.3 (#277), GPT-6 Astra: 93.5 (#2)
| Benchmark | Claude Opus 4.1 | GPT-6 Astra |
|---|---|---|
| FrontierMath (Tiers 1-3) | 12.6% | 93.7% |
| FrontierMath Tier 4 | 2.4% | 97.6% |
| OTIS Mock AIME 2024-2025 | 68.9% | 100% |
| LMArena Math | 1431 | 1465 |
| ProofBench | — | 99% |
| FrontierMath (Feb 2025 set) | 7.2% | — |
| FrontierMath Erdős | — | 2.9% |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge GPT-6 Astra leads
Claude Opus 4.1: 42.0 (#101), GPT-6 Astra: 75.3 (#1)
| Benchmark | Claude Opus 4.1 | GPT-6 Astra |
|---|---|---|
| GPQA Diamond | 77.3% | 95.8% |
| Humanity's Last Exam | 11.5% | 54.8% |
| Vectara Hallucination Rate | 11.8% | 8.7% |
| LMArena Expert | 1439 | 1483 |
| SimpleQA Verified | — | 75.6% |
| Confabulations | 17.1% | — |
Multimodal GPT-6 Astra leads
Claude Opus 4.1: 26.8 (#119), GPT-6 Astra: 55.0 (#3)
| Benchmark | Claude Opus 4.1 | GPT-6 Astra |
|---|---|---|
| LMArena Vision | — | 1281 |
| VPCT | 35% | — |
| Blueprint-Bench 2 | — | 49.7% |
| Furniture Assembly | — | 80% |
| LMArena Document | — | 1468 |
Multilingual GPT-6 Astra leads
Claude Opus 4.1: 52.0 (#95), GPT-6 Astra: 53.7 (#61)
| Benchmark | Claude Opus 4.1 | GPT-6 Astra |
|---|---|---|
| LMArena Non-English | 1405 | 1430 |
| LMArena Chinese | 1427 | 1484 |
| LMArena French | 1431 | 1456 |
| LMArena German | 1413 | 1440 |
| LMArena Japanese | 1378 | 1379 |
| LMArena Korean | 1380 | 1426 |
| LMArena Russian | 1422 | 1436 |
| LMArena Spanish | 1448 | 1407 |
Instruction Following Too close to call
Claude Opus 4.1: 75.6 (#58), GPT-6 Astra: 76.3 (#44)
| Benchmark | Claude Opus 4.1 | GPT-6 Astra |
|---|---|---|
| LMArena Instruction Following | 1435 | 1450 |
Long Context Too close to call
Claude Opus 4.1: 44.5 (#63), GPT-6 Astra: 44.5 (#62)
| Benchmark | Claude Opus 4.1 | GPT-6 Astra |
|---|---|---|
| LMArena Longer Query | 1455 | 1456 |
Writing & Preference GPT-6 Astra leads
Claude Opus 4.1: 62.4 (#74), GPT-6 Astra: 75.3 (#7)
| Benchmark | Claude Opus 4.1 | GPT-6 Astra |
|---|---|---|
| LMArena Text | 1419 | 1441 |
| LMArena Creative Writing | 1412 | 1418 |
| LMArena Multi-Turn | 1444 | 1448 |
| Short-Story Creative Writing | 84.7% | — |
| EQ-Bench Creative Writing | — | 2173 |
Frequently asked questions
Is Claude Opus 4.1 better than GPT-6 Astra?
GPT-6 Astra is the stronger model overall, scoring 70.8 to 41.0 on the Noometry Index.
Which is cheaper, Claude Opus 4.1 or GPT-6 Astra?
GPT-6 Astra is cheaper. It lists at $10 per million input tokens and $50 per million output tokens; Claude Opus 4.1 lists at $15 and $75.
Is Claude Opus 4.1 or GPT-6 Astra better for coding?
GPT-6 Astra scores higher on coding benchmarks: 73.7 versus 44.4 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Astra does, with 1.05M tokens against 200K.
How many benchmarks do Claude Opus 4.1 and GPT-6 Astra share?
32 benchmarks have published results for both models. Claude Opus 4.1 has 48 scored results on Noometry and GPT-6 Astra has 56.