Claude Opus 5.5 vs GPT-6 Astra
Full profiles: Claude Opus 5.5 (Anthropic) and GPT-6 Astra (OpenAI): every benchmark, price and rank.
Updated · Data from 10 sources
As of 21 Oct 2026, Claude Opus 5.5 (max) and GPT-6 Astra (max) are neck and neck on quality (72.7 vs 70.6 on the BenchLeader Index, inside the ±6.7 margin of error), and Claude Opus 5.5 (max) costs 2.5× less, which makes it the better buy for most workloads. Pick Claude Opus 5.5 for coding (82 vs 74); pick GPT-6 Astra for agents & tools (65 vs 64).
Claude Opus 5.5 benchmarks max Anthropic
GPT-6 Astra benchmarks max OpenAIOpen in the comparison toolWhich to pick for…
The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.
| Use case | Pick | Why | Confidence |
|---|---|---|---|
| Coding | Claude Opus 5.5 | 82 vs 74 category score; Arena WebDev 1807 vs 1774 | High |
| Agents & tool use | GPT-6 Astra | 65 vs 64 category score; CWE-Bench (AA) 63.3% vs 58.3% | Medium |
| Maths | Claude Opus 5.5 | 74 vs 72 category score; FrontierMath Tiers 1–3 91.2% vs 93.7% | Medium |
| Reasoning | Either | 76 vs 76 category score; GPQA Diamond 90.6% vs 95.8% | Either |
| Knowledge | Either | 79 vs 79 category score; SimpleQA Verified 72.2% vs 75.6% | Either |
| Long documents | Claude Opus 5.5 | 68 vs 65 category score; AA-LCR 84.7% vs 80.7% | Medium |
| Images and other media | Claude Opus 5.5 | 71 vs 66 category score; MMMU-Pro 87.7% vs 86.9% | Medium |
| Chat quality (human preference) | – | Only GPT-6 Astra has an Arena rating (67 category score) | Not comparable |
| Lowest cost | Claude Opus 5.5 | $8.00 vs $20.00 per 1M blended; agentic coding session $0.320 vs $0.800 | – |
| Fastest first answer | GPT-6 Astra | 608.7 s (Claude Opus 5.5 (max)) vs 328.5 s (GPT-6 Astra (max)) to the first answer token | – |
| High volume on a budget | Neither flagship | A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs | – |
Key differences
- Claude Opus 5.5 (max) and GPT-6 Astra (max) are neck and neck on quality (72.7 vs 70.6, within the ±6.7 margin).
- Claude Opus 5.5 (max) is stronger in coding, composite, long context, maths, multimodal.
- GPT-6 Astra (max) is stronger in agents & tools, knowledge, reasoning, human preference.
- Claude Opus 5.5 (max) is 2.5× cheaper ($8.00 vs $20.00 per 1M blended).
- Claude Opus 5.5 (max) streams 1.5× faster (95 vs 64 tokens per second).
At a glance
| Spec | Claude Opus 5.5 | GPT-6 Astra |
|---|---|---|
| Developer | Anthropic | OpenAI |
| Released | 22 Sept 2026 | 2 Sept 2026 |
| Context window (tokens) | 1,000,000 | 1,050,000 |
| Max output (tokens) | 128,000 (up to 300K on the Message Batches API (beta)) | – |
| Input types | text, image | – |
| Reasoning effort settings | low, medium, high, xhigh, max | – |
| Compared at | Claude Opus 5.5 (max) | GPT-6 Astra (max) |
| Open weights | No | No |
| Price in / out / cached input per 1M | $4.00 / $20.00 / $0.200 | $10.00 / $50.00 / $1.00 |
| API model ID | claude-opus-5-5 | – |
| Where to use it | Claude API, Amazon Bedrock, Google Cloud, Microsoft Foundry | – |
Limits, availability and announced prices from the vendors' own pages: docs.anthropic.com (checked 20 Oct 2026). Everything else is from the day's data.
Category by category
Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.
| Category | Claude Opus 5.5 (max) | GPT-6 Astra (max) | Leader |
|---|---|---|---|
| Reasoning | 75.8 | 76.3 | level |
| Coding | 82.2 | 74.0 | Claude Opus 5.5 |
| Agents & tools | 63.5 | 64.8 | GPT-6 Astra |
| Maths | 74.4 | 72.0 | Claude Opus 5.5 |
| Knowledge | 78.7 | 79.4 | level |
| Human preference | – | 67.2 | not comparable |
| Multimodal | 71.0 | 66.1 | Claude Opus 5.5 |
| Long context | 67.5 | 65.4 | Claude Opus 5.5 |
| Composite | 94.2 | 88.6 | Claude Opus 5.5 |
Where sources disagree
Across the 48 benchmarks both have, Claude Opus 5.5 leads 22, GPT-6 Astra leads 23 and 3 are tied. Every overall index that rates both puts Claude Opus 5.5 ahead.
| Overall index | Claude Opus 5.5 (max) | GPT-6 Astra (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 72.7 | 70.6 | neck and neck |
| AA Intelligence Index v4.3.2 | 57.6 | 52.7 | Claude Opus 5.5 |
| Vals Index | 70.2† | 65.0 | Claude Opus 5.5 |
| Arena Text | 1508† | 1477 | Claude Opus 5.5 |
Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).
Price, speed and latency
List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page; suite cost is what Artificial Analysis paid to run its whole Intelligence Index.
| Measure | Claude Opus 5.5 (max) | GPT-6 Astra (max) |
|---|---|---|
| Blended price per 1M tokens | $8.00 | $20.00 |
| Input / output per 1M | $4.00 / $20.00 | $10.00 / $50.00 |
| Cached input per 1M | $0.200 | $1.00 |
| Price per task: chat reply | $0.0076 | $0.019 |
| Price per task: summarize a 30-page report | $0.060 | $0.150 |
| Price per task: code edit | $0.054 | $0.135 |
| Price per task: agentic coding session | $0.320 | $0.800 |
| Price per task: structured extraction | $0.012 | $0.030 |
| Cost to run a full benchmark suite | $5.98 | $3.26 |
| Output speed | 95 tok/s | 64 tok/s |
| Time to first answer | 608.7 s | 328.5 s |
| Time to a complete answer | 613.9 s | 336.3 s |
Per token is not per task: on Artificial Analysis' full suite Claude Opus 5.5 (max) cost $5.98 and GPT-6 Astra (max) $3.26, because Claude Opus 5.5 (max) used about 4.6× as many tokens for the same work, which a per-token price hides.
Each model is compared at its best-ranked reasoning-effort setting. Claude Opus 5.5 (max) scores 72.7 and takes 609 s to its first answer token; Claude Opus 5.5 (xhigh) scores 70.1 in 114 s, Claude Opus 5.5 (high) scores 69.4 in 34 s. GPT-6 Astra (max) scores 70.6 and takes 328 s to its first answer token; GPT-6 Astra (high) scores 69.7 in 64 s, GPT-6 Astra (xhigh) scores 69.0 in 159 s. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.
Every benchmark
123 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.
| Metric | Publisher | Claude Opus 5.5 (max) | GPT-6 Astra (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 72.7 | 70.6 |
| Agents & tools score | BenchLeader | 63.5 | 64.8 |
| Coding score | BenchLeader | 82.2 | 74.0 |
| Composite score | BenchLeader | 94.2 | 88.6 |
| Knowledge score | BenchLeader | 78.7 | 79.4 |
| Long context score | BenchLeader | 67.5 | 65.4 |
| Maths score | BenchLeader | 74.4 | 72.0 |
| Multimodal score | BenchLeader | 71.0 | 66.1 |
| Reasoning score | BenchLeader | 75.8 | 76.3 |
| Human preference score | BenchLeader | – | 67.2 |
| Blended price $/M | BenchLeader | $8.00 | $20.00 |
| Output speed | BenchLeader | 95 tok/s | 64 tok/s |
| Time to first answer | BenchLeader | 608.7 s | 328.5 s |
| Context window | BenchLeader | 1,000,000 tokens | 1,050,000 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 90.6% | 95.8% |
| Humanity's Last Exam | Scale AI / CAIS | – | 54.8%† |
| Arena Hard Prompts | Arena (LMArena) | 1533† | 1502 |
| LiveBench 2.0 Reasoning | LiveBench | 92.2%† | 92.7%† |
| LiveBench 1.0 Reasoning | LiveBench | 92.2% | 92.7% |
| GPQA Diamond (AA) | Artificial Analysis | – | 96.1% |
| Humanity's Last Exam (AA) | Artificial Analysis | 61.4% | 54.7% |
| ARC-AGI-1 | ARC Prize | 97.5% | 97.5% |
| ARC-AGI-2 | ARC Prize | 91.7% | 95.0% |
| ARC-AGI-3 | ARC Prize | – | 98.6% |
| CritPt | Artificial Analysis | 31.7% | 31.7% |
| MysteryMechanism | Vals AI | 49.5%† | 53.1% |
| Chess Puzzles | Epoch AI Benchmarking Hub | 67.0% | 74.0% |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 71.0% | 84.0% |
| LMCA | Epoch AI Benchmarking Hub | 68.2% | 64.1%† |
| DTBench | Epoch AI Benchmarking Hub | 98.9% | 97.1%† |
| BTF-3 | Epoch AI Benchmarking Hub | – | 13.5%† |
| Coding | |||
| SciCode | SciCode | 66.9% | 56.5% |
| WeirdML | WeirdML | – | 93.3% |
| FrontierCode | Cognition | 54.6%† | 53.3% |
| GSO-Bench | GSO-Bench | – | 79.4%† |
| Arena Coding | Arena (LMArena) | 1548† | 1543 |
| Arena WebDev | Arena (LMArena) | 1807 | 1774 |
| LiveBench 2.0 Coding | LiveBench | 96.3%† | 93.7%† |
| LiveBench 1.0 Coding | LiveBench | 89.3% | 80.4% |
Show all 123 benchmarks
| Metric | Publisher | Claude Opus 5.5 (max) | GPT-6 Astra (max) |
|---|---|---|---|
| Coding | |||
| IOI | Vals AI | 95.1%† | 100.0% |
| Code Migration | Vals AI | 66.7%† | 67.7% |
| ProgramBench | Vals AI | 18.5%† | 5.5% |
| Vibe Code Bench 1-100 | Vals AI | 30.4%† | 27.6% |
| Vibe Code Bench v1.1 | Vals AI | 90.3%† | 89.6% |
| SWE Atlas: Codebase QnA | Scale AI SEAL | – | 59.1%† |
| SWE Atlas: Refactoring | Scale AI SEAL | – | 59.0%† |
| SWE Atlas: Test Writing | Scale AI SEAL | – | 50.7%† |
| MirrorCode | Epoch AI Benchmarking Hub | 77.4% | 46.7%† |
| DeepSWE v1.1 | Epoch AI Benchmarking Hub | – | 73.2% |
| CursorBench | Cursor | 57.8% | – |
| ALE-Bench | Epoch AI Benchmarking Hub | 2147.4† | 2951.3 |
| FrontierSWE | Epoch AI Benchmarking Hub | 62.3% | 65.5% |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 59.6% | 59.1% |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | – | 88.4% |
| Startrise Frontend | Startrise | 71.1%† | 79.9%† |
| FrontierCode 1.1 (AA) | Artificial Analysis | 52.2% | 47.0% |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 64.8% | 58.2% |
| Remote Labor Index | Scale AI / CAIS | 21.3%† | 20.8%† |
| APEX-Agents | Mercor | 73.5% | 64.7%† |
| Arena Agent | Arena (LMArena) | 20.4 | 15.1 |
| LiveBench Long Agentic | LiveBench | 85.0%† | 82.4%† |
| LiveBench Browser | LiveBench | 80.0%† | 84.0%† |
| LiveBench Agentic Coding | LiveBench | 71.7% | 57.3% |
| Terminal-Bench 2.1 (Vals) | Vals AI | 87.6%† | 87.3% |
| HiL-Bench | Scale AI SEAL | 59.0%† | 65.3%† |
| GDPval-AA v2.1 | Artificial Analysis | 68.3% | 53.6% |
| τ³-Banking (AA) | Artificial Analysis | – | 41.4% |
| ITBench SRE (AA) | Artificial Analysis | 38.2% | 48.6% |
| Analyst Agent (AA) | Artificial Analysis | 56.3% | 51.3% |
| CUA-bench | Vals AI | 14.0% | 19.2% |
| CyberBench | Vals AI | 55.4%† | 41.1% |
| Finance Agent v2 | Vals AI | 58.6%† | 53.5% |
| Harvey's Legal Agent Benchmark | Vals AI | 9.2%† | 7.1% |
| Legal Research Bench | Vals AI | 50.5%† | 39.4% |
| SREBench | Vals AI | 33.6%† | 56.9% |
| Tax Agent Bench | Vals AI | 45.6%† | 20.7% |
| Terminal-Bench 4.0 (Vals) | Vals AI | 65.2%† | 59.6% |
| Terminal-Bench Science | Vals AI | 47.1%† | 62.9% |
| Time Horizon Index: KSP | Vals AI | 91.3%† | 90.5% |
| Arena Search | Arena (LMArena) | 1211† | 1246 |
| BALROG | BALROG | – | 68.3% |
| Vending-Bench 2 | Andon Labs | 9235.3† | 15514.7† |
| AutomationBench | Artificial Analysis | 69.5% | 68.5% |
| GDP.pdf (AA) | Artificial Analysis | 26.2% | 31.0% |
| Harvey LAB-AA v1.1 | Harvey | 4.2% | 8.6% |
| AA-Briefcase v1.1 | Artificial Analysis | 1803 | 1569 |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 59.0% | 63.3% |
| CWE-Bench (AA) | Artificial Analysis | 58.3% | 63.3% |
| DeepSec-Bench (AA) | Artificial Analysis | 26.9% | 36.9% |
| CyberGym end-to-end (AA) | Artificial Analysis | 0.8% | 0.0% |
| FACTS Search | 86.5%† | 89.9%† | |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 91.2% | 93.7% |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 95.0% | 97.6% |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 100.0% | 100.0% |
| ProofBench | Vals AI | 100.0% | 99.0%† |
| LiveBench Mathematics | LiveBench | 97.1% | 96.8% |
| Arena Maths | Arena (LMArena) | 1502† | 1486 |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 72.2% | 75.6% |
| LiveBench 2.0 Data Analysis | LiveBench | 80.3%† | 83.0%† |
| LiveBench Research | LiveBench | 85.0%† | 85.2%† |
| LiveBench 1.0 Data Analysis | LiveBench | 80.3% | 83.0% |
| AA-Omniscience | Artificial Analysis | 46.4 | 43.4 |
| PRBench Finance | Scale AI SEAL | – | 47.5%† |
| PRBench Legal | Scale AI SEAL | 47.6%† | 48.4%† |
| BioMysteryBench | Vals AI | 79.3%† | 79.3% |
| Excel Modeling Benchmark | Vals AI | 75.9%† | 71.7% |
| MedCode | Vals AI | 49.8%† | 48.5% |
| MedScribe | Vals AI | 91.4%† | 87.9% |
| Public Benefits Bench | Vals AI | 70.6%† | – |
| DrugDiscoveryBench | Scale AI SEAL | – | 68.7% |
| EBR-bench | Epoch AI Benchmarking Hub | 71.4% | 76.2% |
| GDP.pdf | Epoch AI Benchmarking Hub | 30.6% | 34.2% |
| AA-Omniscience: accuracy | Artificial Analysis | 66.2% | 62.6% |
| AA-Omniscience: non-hallucination | Artificial Analysis | 41.4% | 48.7% |
| Instruction following | |||
| LiveBench Language | LiveBench | 86.3% | 89.4% |
| LiveBench Instruction Following | LiveBench | 65.7% | 75.6% |
| Arena Instruction Following | Arena (LMArena) | 1518† | 1473 |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1508† | 1477 |
| Arena Creative Writing | Arena (LMArena) | 1519† | 1450 |
| Arena Multi-turn | Arena (LMArena) | 1501† | 1486 |
| Arena Longer Queries | Arena (LMArena) | 1523† | 1489 |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1321† | 1280 |
| LiveBench Design | LiveBench | 86.9%† | 82.0%† |
| MMMU-Pro | Artificial Analysis | 87.7% | 86.9% |
| SAGE | Vals AI | 45.8%† | 46.4% |
| Blueprint-Bench 2 | Epoch AI Benchmarking Hub | 51.2%† | 49.7%† |
| AA-3D | Artificial Analysis | 1191 | 1166 |
| Long context | |||
| AA-LCR | Artificial Analysis | 84.7% | 80.7% |
| Arena Document | Arena (LMArena) | – | 1473 |
| MLCR | Artificial Analysis | 66.7% | 35.0% |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 168.8† | 168.8† |
| LiveBench 2.0 | LiveBench | 86.5%† | 86.1%† |
| LiveBench 1.0 | LiveBench | 83.2% | 82.2% |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 57.6 | 52.7 |
| Vals Index | Vals AI | 70.2† | 65.0 |
| AA Cyber Index | Artificial Analysis | 28.7 | 33.4 |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | 5.8% | – |
Data as of 2026-10-21. Best configuration of each model; every score links to its source on the model pages.
What changed
- Claude Opus 5.5 (max): 2 score revisions.
- GPT-6 Astra (max): 4 score revisions.
- Claude Opus 5.5 (max): BenchLeader Index 71.9 → 72.6.
- GPT-6 Astra (max): BenchLeader Index 69.8 → 70.6.
- Claude Opus 5.5 (max): 1 new result (FORTRESS).
- Claude Opus 5.5 (max): BenchLeader Index 71.3 → 71.9.
- Claude Opus 5.5 (max): 1 score revision.
- GPT-6 Astra (max): 1 score revision.
- Claude Opus 5.5 (max): 1 new result (Chess Puzzles); 1 score revision.
- GPT-6 Astra (max): 1 new result (Arena Search); 3 score revisions.
Related comparisons
- Claude Opus 5.5 vs Gemini 4 Argon
- Claude Opus 5.5 vs Muse Wonder Full
- Claude Opus 5.5 vs Claude Fable 5.1
- GPT-6 Astra vs Gemini 4 Argon
- GPT-6 Astra vs Muse Wonder Full
- GPT-6 Astra vs Claude Fable 5.1
- Claude Opus 5.5 vs GPT-5.6 Sol
- Claude Opus 5.5 vs GPT-6.1 Sol
Rankings: Best LLM overall · Best LLM for coding · Best LLM for agents · Best cheap LLMs
Claude Opus 5.5 vs GPT-6 Astra: questions
- Is Claude Opus 5.5 better than GPT-6 Astra?
- Claude Opus 5.5 (max) and GPT-6 Astra (max) are neck and neck on quality (72.7 vs 70.6, within the ±6.7 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2026-10-21, so check the category scores for your use.
- Which is cheaper, Claude Opus 5.5 or GPT-6 Astra, and will that change?
- Claude Opus 5.5 is cheaper today: $8.00 against $20.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
- Is Claude Opus 5.5 better than GPT-6 Astra for coding?
- Claude Opus 5.5 scores higher in coding (82 vs 74 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1807 for Claude Opus 5.5 against 1774 for GPT-6 Astra.
- Is Claude Opus 5.5 better than GPT-6 Astra for agents and tool use?
- GPT-6 Astra scores higher in agentic tasks (65 vs 64 on the category index, where 50 is average). On Terminal-Bench, the top shared agents & tools benchmark, it is 64.8% for Claude Opus 5.5 against 58.2% for GPT-6 Astra.
- Which is better for long documents?
- Claude Opus 5.5 scores higher on long-context benchmarks (68 vs 65). Both take about 1.1M tokens: Claude Opus 5.5 1,000,000, GPT-6 Astra 1,050,000.
- Which has lower latency?
- GPT-6 Astra (max) answers first: 328.5 s against 608.7 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.
- Which is faster, Claude Opus 5.5 or GPT-6 Astra?
- Claude Opus 5.5 streams faster: 95 against 64 output tokens per second.
- Do independent benchmarks agree on Claude Opus 5.5 vs GPT-6 Astra?
- Across the 48 benchmarks both have, Claude Opus 5.5 leads 22, GPT-6 Astra leads 23 and 3 are tied. Every overall index that rates both puts Claude Opus 5.5 ahead.
- When was Claude Opus 5.5 released?
- Claude Opus 5.5 was released on 22 Sept 2026.