Claude Opus 5 vs GPT-5 Pro
Full profiles: Claude Opus 5 (Anthropic) and GPT-5 Pro (OpenAI): every benchmark, price and rank.
Updated · Data from 13 sources
As of 26 Oct 2026, Claude Opus 5 (max) is the better pick for most workloads: it leads on quality (68.8 vs 59.8 on the BenchLeader Index) and costs 4.1× less. Claude Opus 5 leads in every category we measure both in.
Claude Opus 5 benchmarks 
GPT-5 Pro benchmarks Which 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 |
|---|---|---|---|
| Reasoning | Claude Opus 5 | 74 vs 56 category score; ARC-AGI-2 90.4% vs 18.3% | High |
| Knowledge | Claude Opus 5 | 72 vs 66 category score | Medium |
| Images and other media | Either | 68 vs 67 category score | Either |
| Chat quality (human preference) | – | Only Claude Opus 5 has an Arena rating (69 category score) | Not comparable |
| Lowest cost | Claude Opus 5 | $10.00 vs $41.25 per 1M blended; agentic coding session $0.400 vs $1.38 | – |
| 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 (max) leads on quality: 68.8 vs 59.8.
- Claude Opus 5 (max) is stronger in agents & tools, coding, composite, human preference, knowledge, long context, maths, multimodal, reasoning.
- Claude Opus 5 (max) is 4.1× cheaper ($10.00 vs $41.25 per 1M blended).
At a glance
| Spec | Claude Opus 5 | GPT-5 Pro |
|---|---|---|
| Developer | Anthropic | OpenAI |
| Released | 24 Jul 2026 | 7 Aug 2025 |
| Context window (tokens) | 1,000,000 | 400,000 |
| Compared at | Claude Opus 5 (max) | GPT-5 Pro |
| Open weights | No | No |
| Price in / out / cached input per 1M | $5.00 / $25.00 / $0.500 | $15.00 / $120.00 / – |
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 (max) | GPT-5 Pro | Leader |
|---|---|---|---|
| Reasoning | 74.1 | 56.1 | Claude Opus 5 |
| Coding | 70.2 | – | not comparable |
| Agents & tools | 64.3 | – | not comparable |
| Maths | 70.6 | – | not comparable |
| Knowledge | 71.6 | 65.8 | Claude Opus 5 |
| Human preference | 68.5 | – | not comparable |
| Multimodal | 67.9 | 67.4 | level |
| Long context | 64.7 | – | not comparable |
| Composite | 86.3 | – | not comparable |
Where sources disagree
Across the 2 benchmarks both have, Claude Opus 5 leads 2, GPT-5 Pro leads 0. Every overall index that rates both puts Claude Opus 5 ahead.
| Overall index | Claude Opus 5 (max) | GPT-5 Pro | Leader |
|---|---|---|---|
| BenchLeader Index | 68.8 | 59.8 | Claude Opus 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 (max) | GPT-5 Pro |
|---|---|---|
| Blended price per 1M tokens | $10.00 | $41.25 |
| Input / output per 1M | $5.00 / $25.00 | $15.00 / $120.00 |
| Cached input per 1M | $0.500 | – |
| Price per task: chat reply | $0.0095 | $0.042 |
| Price per task: summarize a 30-page report | $0.075 | $0.252 |
| Price per task: code edit | $0.068 | $0.270 |
| Price per task: agentic coding session | $0.400 | $1.38 |
| Price per task: structured extraction | $0.015 | $0.054 |
| Cost to run a full benchmark suite | $5.86 | – |
| Output speed | 51 tok/s | – |
| Time to first answer | 68.7 s | – |
| Time to a complete answer | 78.4 s | – |
Each model is compared at its best-ranked reasoning-effort setting. Claude Opus 5 (max) scores 68.8 and takes 69 s to its first answer token; Claude Opus 5 (high) scores 67.9 in 17 s, Claude Opus 5 (xhigh) scores 67.4 in 31 s. GPT-5 Pro scores 59.8. 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
130 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 (max) | GPT-5 Pro |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 68.8 | 59.8 |
| Agents & tools score | BenchLeader | 64.3 | – |
| Coding score | BenchLeader | 70.2 | – |
| Composite score | BenchLeader | 86.3 | – |
| Human preference score | BenchLeader | 68.5 | – |
| Knowledge score | BenchLeader | 71.6 | 65.8 |
| Long context score | BenchLeader | 64.7 | – |
| Maths score | BenchLeader | 70.6 | – |
| Multimodal score | BenchLeader | 67.9 | 67.4 |
| Reasoning score | BenchLeader | 74.1 | 56.1 |
| Blended price $/M | BenchLeader | $10.00 | $41.25 |
| Output speed | BenchLeader | 51 tok/s | – |
| Time to first answer | BenchLeader | 68.7 s | – |
| Context window | BenchLeader | 1,000,000 tokens | 400,000 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 93.9% | – |
| Humanity's Last Exam | Scale AI / CAIS | – | 31.6% |
| SimpleBench | SimpleBench | 80.6%† | 61.6% |
| Arena Hard Prompts | Arena (LMArena) | 1515 | – |
| LiveBench 1.0 Reasoning | LiveBench | 91.2% | – |
| GPQA Diamond (AA) | Artificial Analysis | 93.2% | – |
| Humanity's Last Exam (AA) | Artificial Analysis | 54.9% | – |
| GPQA Diamond (Vals) | Vals AI | 93.4%† | – |
| Kagi LLM Benchmark | Kagi LLM Benchmark | – | 76.8% |
| ARC-AGI-1 | ARC Prize | 97.5% | 70.2% |
| ARC-AGI-2 | ARC Prize | 90.4% | 18.3% |
| ARC-AGI-3 | ARC Prize | 30.2%† | – |
| CritPt | Artificial Analysis | 29.1% | – |
| MysteryMechanism | Vals AI | 37.4%† | – |
| Chess Puzzles | Epoch AI Benchmarking Hub | 43.0% | 48.0%† |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 59.0% | – |
| LMCA | Epoch AI Benchmarking Hub | 63.3% | – |
| DTBench | Epoch AI Benchmarking Hub | 97.6% | – |
| ForecastBench | ForecastBench | 66.5% | – |
| BTF-3 | Epoch AI Benchmarking Hub | 12.0%† | – |
| Coding | |||
| SciCode | SciCode | 56.4% | – |
| WeirdML | WeirdML | 91.8% | 60.4%† |
| FrontierCode | Cognition | 53.4% | – |
| Arena Coding | Arena (LMArena) | 1528 | – |
| Arena WebDev | Arena (LMArena) | 1691 | – |
Show all 130 benchmarks
| Metric | Publisher | Claude Opus 5 (max) | GPT-5 Pro |
|---|---|---|---|
| Coding | |||
| LiveBench 1.0 Coding | LiveBench | 81.5% | – |
| LiveCodeBench | Vals AI | 89.0%† | – |
| IOI | Vals AI | 84.3%† | – |
| SWE-bench (Vals) | Vals AI | 97.0%† | – |
| Code Migration | Vals AI | 57.5%† | – |
| ProgramBench | Vals AI | 3.0%† | – |
| Vibe Code Bench 1-100 | Vals AI | 28.5%† | – |
| Vibe Code Bench v1.1 | Vals AI | 88.4%† | – |
| SWE Atlas: Codebase QnA | Scale AI SEAL | 63.2%† | – |
| SWE Atlas: Test Writing | Scale AI SEAL | 62.2%† | – |
| DeepSWE v1.1 | Epoch AI Benchmarking Hub | 73.7% | – |
| CursorBench | Cursor | 46.6% | – |
| ALE-Bench | Epoch AI Benchmarking Hub | 2164.6† | – |
| AlgoTune | AlgoTune | – | 1.3† |
| FrontierSWE | Epoch AI Benchmarking Hub | 52.0% | – |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 49.0% | – |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | 89.1% | – |
| Startrise Frontend | Startrise | 82.3%† | – |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 51.8% | – |
| OSWorld-Verified 2.0 | OSWorld | 31.4% | – |
| APEX-Agents | Mercor | 65.8% | – |
| Arena Agent | Arena (LMArena) | 8.2 | – |
| LiveBench Agentic Coding | LiveBench | 65.2% | – |
| Terminal-Bench 2.1 (Vals) | Vals AI | 84.6%† | – |
| MCP Atlas | Scale AI SEAL | 85.8%† | – |
| HiL-Bench | Scale AI SEAL | 57.0%† | – |
| τ³-bench Banking | τ²-bench | 48.7% | – |
| τ³-Banking (AA) | Artificial Analysis | 42.1% | – |
| Analyst Agent (AA) | Artificial Analysis | 53.8% | – |
| CUA-bench | Vals AI | 9.0% | – |
| CyberBench | Vals AI | 65.4%† | – |
| Finance Agent v2 | Vals AI | 58.6%† | – |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 6.7%† | – |
| Legal Research Bench | Vals AI | 55.3%† | – |
| SkillsBench | Vals AI | 60.4%† | – |
| SREBench | Vals AI | 12.2%† | – |
| Tax Agent Bench | Vals AI | 45.5%† | – |
| Terminal-Bench 4.0 (Vals) | Vals AI | 53.5%† | – |
| Terminal-Bench Science | Vals AI | 27.1%† | – |
| Time Horizon Index: KSP | Vals AI | 18.8%† | – |
| Arena Search | Arena (LMArena) | 1214† | – |
| BALROG | BALROG | 63.4% | – |
| PostTrainBench | Epoch AI Benchmarking Hub | 35.0%† | – |
| GBAEval | Epoch AI Benchmarking Hub | 79.6%† | – |
| Vending-Bench 2 | Andon Labs | 11181.9† | – |
| AutomationBench | Artificial Analysis | 56.6% | – |
| GDP.pdf (AA) | Artificial Analysis | 21.6% | – |
| EnterpriseOps-Gym | Artificial Analysis | 47.5% | – |
| AA-Briefcase v1.1 | Artificial Analysis | 1657 | – |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 28.6% | – |
| DeepSec-Bench (AA) | Artificial Analysis | 25.9% | – |
| DeepSearchQA | – | 65.2% | |
| FACTS Search | 85.3%† | – | |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 85.6% | 55.8%† |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 73.2% | 19.5%† |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 98.9% | – |
| ProofBench | Vals AI | 99.0% | – |
| LiveBench Mathematics | LiveBench | 95.7% | – |
| Arena Maths | Arena (LMArena) | 1517 | – |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 59.9% | – |
| LiveBench 1.0 Data Analysis | LiveBench | 74.5% | – |
| AA-Omniscience | Artificial Analysis | 37.1 | – |
| MMLU-Pro | Vals AI | 91.6%† | – |
| LegalBench | Vals AI | 87.0%† | – |
| CorpFin | Vals AI | 73.2%† | – |
| TaxEval | Vals AI | 75.1%† | – |
| PRBench Finance | Scale AI SEAL | – | 51.1% |
| PRBench Legal | Scale AI SEAL | – | 49.9% |
| MultiNRC | Scale AI SEAL | – | 65.2% |
| BioMysteryBench | Vals AI | 79.3%† | – |
| Excel Modeling Benchmark | Vals AI | 73.6%† | – |
| MedCode | Vals AI | 63.6%† | – |
| MedScribe | Vals AI | 91.0%† | – |
| Public Benefits Bench v1.1 | Vals AI | 76.9%† | – |
| DrugDiscoveryBench | Scale AI SEAL | 53.7% | – |
| EBR-bench | Epoch AI Benchmarking Hub | 45.7% | – |
| GDP.pdf | Epoch AI Benchmarking Hub | 24.0% | – |
| AA-Omniscience: accuracy | Artificial Analysis | 60.9% | – |
| AA-Omniscience: non-hallucination | Artificial Analysis | 39.2% | – |
| Instruction following | |||
| LiveBench Language | LiveBench | 88.7% | – |
| LiveBench Instruction Following | LiveBench | 63.8% | – |
| Arena Instruction Following | Arena (LMArena) | 1495 | – |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1491 | – |
| EQ-Bench 4 | EQ-Bench | 1360† | – |
| Arena Creative Writing | Arena (LMArena) | 1474 | – |
| Arena Multi-turn | Arena (LMArena) | 1487 | – |
| Arena Longer Queries | Arena (LMArena) | 1503 | – |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1320† | – |
| MMMU-Pro | Artificial Analysis | 84.7% | – |
| VISTA | Scale AI SEAL | – | 52.4% |
| MMMU-Pro (Vals) | Vals AI | 89.9%† | – |
| MortgageTax | Vals AI | 72.1%† | – |
| SAGE | Vals AI | 49.4%† | – |
| Blueprint-Bench 2 | Epoch AI Benchmarking Hub | 30.4%† | – |
| Long context | |||
| AA-LCR | Artificial Analysis | 79.3% | – |
| Arena Document | Arena (LMArena) | 1490† | – |
| MLCR | Artificial Analysis | 11.1% | – |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 163.9† | 150.6 |
| LiveBench 1.0 | LiveBench | 80.1% | – |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 50.8 | – |
| Vals RSI Index | Vals AI | 33.0% | – |
| Vals Science Index | Vals AI | 47.9%† | – |
| Vals Multimodal Index | Vals AI | 73.9%† | – |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | 16.8%† | 15.2% |
| MASK | Scale AI SEAL | – | 86.0% |
Data as of 2026-10-26. Best configuration of each model; every score links to its source on the model pages.
What changed
- Claude Opus 5 (max): 1 new result (Vals RSI Index).
- Claude Opus 5 (max): 1 score revision.
- Claude Opus 5 (max): 1 new result (ForecastBench); 1 score revision.
- Claude Opus 5 (max): BenchLeader Index 68.3 → 68.9.
- Claude Opus 5 (max): 4 new results (GDPval-AA v2.1, AA-Omniscience: accuracy, AA-Omniscience: non-hallucination…).
- Claude Opus 5 (max): 1 score revision.
- Claude Opus 5 (max): 2 score revisions.
- GPT-5 Pro: 1 new result (PRBench Legal).
- Claude Opus 5 (max): 2 new results (Terminal-Bench-Science 0.1 (AA), DeepSec-Bench (AA)).
- Claude Opus 5 (max): 1 new result (DrugDiscoveryBench).
Related comparisons
- Claude Opus 5 vs Claude Opus 5.5
- Claude Opus 5 vs Gemini 4 Argon
- Claude Opus 5 vs Muse Wonder Full
- GPT-5 Pro vs Claude Opus 5.5
- GPT-5 Pro vs Gemini 4 Argon
- GPT-5 Pro vs Muse Wonder Full
- GPT-5 Pro vs Claude Fable 5.1
- Claude Fable 5 vs GPT-5 Pro
Rankings: Best LLM overall · Best LLM for coding · Best LLM for agents · Best cheap LLMs
Claude Opus 5 vs GPT-5 Pro: questions
- Is Claude Opus 5 better than GPT-5 Pro?
- Claude Opus 5 (max) leads on quality: 68.8 vs 59.8. The BenchLeader Index combines every independent quality benchmark; Claude Opus 5 (max) is ahead overall as of 2026-10-26, but check the category scores for your use.
- Which is cheaper, Claude Opus 5 or GPT-5 Pro, and will that change?
- Claude Opus 5 is cheaper today: $10.00 against $41.25 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
- Which is better for long documents?
- Claude Opus 5 accepts more context: 1,000,000 against 400,000 tokens for GPT-5 Pro.
- Do independent benchmarks agree on Claude Opus 5 vs GPT-5 Pro?
- Across the 2 benchmarks both have, Claude Opus 5 leads 2, GPT-5 Pro leads 0. Every overall index that rates both puts Claude Opus 5 ahead.
- When was Claude Opus 5 released?
- Claude Opus 5 was released on 24 Jul 2026.