AnthropicClaude Opus 4.7
Reasoning effort
Claude Opus 4.7 is an Anthropic proprietary reasoning model, released 16 Apr 2026. Its best configuration ranks #66 of 785 on the BenchLeader Index at 63.3 ±2.7, in the upper half. The ± is the point: 140 other configurations score within that range, so they and this one cannot be told apart on quality alone — price and speed are what separate them. It scores highest in human preference (68) and lowest in coding (61). At $10.00 per million tokens blended it is among the most expensive ranked models. Output speed of 60 tokens per second puts it slower than most, with a first token in 1.2 s. It has been measured at 7 reasoning-effort settings; this summary describes the best-scoring one, and the tabs above switch between them. Last measured 22 Oct 2026.
- Blended price
- $10.00/M
- $5.00 in · $25.00 out
- Output speed
- 60 tok/s
- OpenRouter traffic, 7-day median; not yet measured by Artificial Analysis
- First answer
- 1.22 s
- Context
- 1M
- Full answer
- –
- Cost per run
- –
- Released
- 16 Apr 2026
- Overall index63
- Reasoning65
- Coding61
- Agents & tools65
- Maths67
- Knowledge62
- Human preference68
- Multimodal67
Versions
Anthropic has shipped 9 models under this name. Each is ranked on its own results; a newer version often has fewer results so far, which holds its index nearer the average until more arrive.
| Model | Released | Index | Rank |
|---|---|---|---|
| Claude Opus 5.5max | 22 Sept 2026 | 72.6 | #1 |
| Claude Opus 5max | 24 Jul 2026 | 68.8 | #15 |
| Claude Opus 4.8max | 28 May 2026 | 63.3 | #67 |
| Claude Opus 4.7this page | 16 Apr 2026 | 63.3 | #66 |
| Claude Opus 4.6high | 5 Feb 2026 | 62.7 | #78 |
| Claude Opus 4.5thinking | 24 Nov 2025 | 59.9 | #119 |
| Claude Opus 4.1thinking | 5 Aug 2025 | 56.4 | #204 |
| Claude Opus 4thinking | 22 May 2025 | 55.0 | #236 |
| Claude 3 Opus | 4 Mar 2024 | 39.2 | #691 |
Reasoning-effort configurations
The same model behaves differently depending on how much it is allowed to think. Each row is one setting, scored only on the benchmarks that were run at that setting. “Not stated” collects results from publishers that did not say which setting they used; for a reasoning model that is usually its thinking mode, but we do not assume it. Pick a setting here or at the top of the page to see its price, speed and category scores.
| Effort | Index | Rank | Speed | First answer | Chat reply cost | Categories |
|---|---|---|---|---|---|---|
| no reasoning | 58.1 | #159 | 50 tok/s | 1.25 s | $0.0095 | Agents & tools 81 · Composite 64 · Instruction following 46 · Knowledge 68 · Long context 63 · Multimodal 59 · Reasoning 49 |
| low | – | – | 60 tok/s | 1.22 s | $0.0095 | |
| high | 61.0 | #101 | 60 tok/s | 1.22 s | $0.0095 | Coding 64 · Human preference 70 · Maths 69 · Multimodal 66 · Reasoning 55 |
| xhigh | 57.4 | #180 | 60 tok/s | 1.22 s | $0.0095 | Knowledge 58 · Maths 60 · Reasoning 65 |
| max | 62.4 | #85 | 54 tok/s | 21 s | $0.0095 | Agents & tools 60 · Coding 65 · Composite 75 · Instruction following 59 · Knowledge 74 · Long context 64 · Maths 58 · Multimodal 62 · Reasoning 61 |
| thinking | – | – | 60 tok/s | 1.22 s | $0.0095 | Reasoning 73 |
| not statedbest | 63.3 | #66 | 60 tok/s | 1.22 s | $0.0095 | Agents & tools 65 · Coding 61 · Human preference 68 · Knowledge 62 · Maths 67 · Multimodal 67 · Reasoning 65 |
How its index has moved
8 Sept 2026 to 21 Oct 2026- not stated
- max
- high
- no reasoning
The index is recomputed from scratch every day, so a line moves when a new benchmark result lands, when a publisher revises a score, or when the models it is normalised against change. Early movement usually means the score is still settling.
Benchmark results
See all LLM benchmarks. One column per reasoning effort. Rank is among every configuration of every model on that benchmark. Hover a score for the run it came from.
Reasoning
| Benchmark | no reasoning | low | high | xhigh | max | thinking | not stated | Source | Trend |
|---|---|---|---|---|---|---|---|---|---|
| GPQA Diamond | – | – | – | 90.2%#45 | 86.4%#78 | – | – | Epoch AI Benchmarking Hub | |
| Humanity's Last Exameffort not stated | – | – | – | – | – | – | 36.2%#10 | Scale AI / CAIS | |
| SimpleBencheffort not stated | – | – | – | – | – | – | 61.7%#23 | SimpleBench | |
| Arena Hard Prompts | – | – | 1525#6 | – | – | – | 1519#9 | Arena (LMArena) | |
| LiveBench 1.0 Reasoningnot in index | – | – | – | 87.2%#28 | – | – | – | LiveBench | |
| GPQA Diamond (AA)not in index | 88.5%#90 | – | – | – | 91.4%#47 | – | – | Artificial Analysis | |
| Humanity's Last Exam (AA)not in index | 33.3%#137 | – | – | – | 42.3%#71 | – | – | Artificial Analysis | |
| GPQA Diamond (Vals)not in indexeffort not stated | – | – | – | – | – | – | 90.2%#25 | Vals AI | |
| Kagi LLM Benchmark | – | – | – | – | – | 80.7%#7 | 73.3%#18 | Kagi LLM Benchmark | |
| ARC-AGI-3 | – | – | 0.2%#58 | – | – | – | – | ARC Prize | |
| CritPt | 5.1%#154 | – | – | – | 12.0%#109 | – | – | Artificial Analysis | |
| Chess Puzzlesnot in index | – | 26.0%#76 | – | 36.0%#49 | 41.0%#40 | – | – | Epoch AI Benchmarking Hub | |
| Mystery Game Puzzlesnot in index | – | – | – | – | 28.0%#39 | – | 13.0%#102 | Epoch AI Benchmarking Hub | |
| LMCAnot in index | – | – | – | – | 52.2%#56 | – | – | Epoch AI Benchmarking Hub | |
| DTBenchnot in index | – | – | – | – | 94.7%#55 | – | – | Epoch AI Benchmarking Hub | |
| ForecastBenchnot in indexeffort not stated | – | – | – | – | – | – | 63.1%#48 | ForecastBench |
Coding
| Benchmark | high | xhigh | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|
| SWE-bench Verified (Epoch) | – | – | 83.5%#1 | – | Epoch AI Benchmarking Hub | |
| SciCode | – | – | 54.5%#60 | – | SciCode | |
| WeirdML | 76.4%#25 | – | 75.5%#28 | 76.4%#26 | WeirdML | |
| FrontierCodeeffort not stated | – | – | – | 38.5%#29 | Cognition | |
| GSO-Bench | 44.1%#6 | – | – | 44.1%#6 | GSO-Bench | |
| Arena Coding | 1551#3 | – | – | 1546#7 | Arena (LMArena) | |
| Arena WebDev | 1558#38 | – | – | 1555#40 | Arena (LMArena) | |
| LiveBench 1.0 Codingnot in index | – | 82.1%#11 | – | – | LiveBench | |
| LiveCodeBencheffort not stated | – | – | – | 85.1%#34 | Vals AI | |
| SWE-bench (Vals)not in indexeffort not stated | – | – | – | 82.0%#21 | Vals AI | |
| Code Migrationnot in indexeffort not stated | – | – | – | 43.9%#25 | Vals AI | |
| ProgramBenchnot in indexeffort not stated | – | – | – | 0.0%#32 | Vals AI | |
| Vibe Code Bench v1.1not in indexeffort not stated | – | – | – | 71.0%#40 | Vals AI | |
| SWE Atlas: Codebase QnAnot in indexeffort not stated | – | – | – | 40.3%#11 | Scale AI SEAL | |
| SWE Atlas: Refactoringnot in indexeffort not stated | – | – | – | 48.6%#4 | Scale AI SEAL | |
| SWE Atlas: Test Writingnot in indexeffort not stated | – | – | – | 38.5%#13 | Scale AI SEAL | |
| MirrorCodenot in index | 31.1%#6 | – | – | – | Epoch AI Benchmarking Hub | |
| ALE-Benchnot in indexeffort not stated | – | – | – | 1323.0#30 | Epoch AI Benchmarking Hub | |
| Terminal-Bench 2.1 (AA)not in index | – | – | 83.2%#36 | – | Artificial Analysis |
Agents & tools
| Benchmark | no reasoning | xhigh | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|
| Terminal-Bencheffort not stated | – | – | – | 80.2%#3 | Terminal-Bench | |
| OSWorld-Verified 2.0 | – | – | 18.2%#8 | – | OSWorld | |
| APEX-Agents | – | – | 49.2%#28 | – | Mercor | |
| LiveBench Agentic Codingnot in index | – | 50.7%#42 | – | – | LiveBench | |
| Terminal-Bench Hard | 54.5%#15 | – | 51.5%#21 | – | Artificial Analysis | |
| τ²-Bench Telecom (AA)not in index | 74.0%#144 | – | 88.6%#72 | – | Artificial Analysis | |
| Terminal-Bench 2.1 (Vals)effort not stated | – | – | – | 68.5%#31 | Vals AI | |
| MCP Atlas | – | – | 79.1%#13 | – | Scale AI SEAL | |
| HiL-Bencheffort not stated | – | – | – | 41.7%#16 | Scale AI SEAL | |
| τ³-bench Bankingnot in index | – | – | 40.2%#7 | – | τ²-bench | |
| τ³-Banking (AA) | – | – | 34.6%#50 | – | Artificial Analysis | |
| ITBench SRE (AA)not in index | – | – | 46.7%#11 | – | Artificial Analysis | |
| Analyst Agent (AA)not in index | – | – | 43.8%#20 | – | Artificial Analysis | |
| Finance Agent v2not in indexeffort not stated | – | – | – | 51.5%#40 | Vals AI | |
| Harvey's Legal Agent Benchmark v1not in indexeffort not stated | – | – | – | 6.7%#30 | Vals AI | |
| Legal Research Benchnot in indexeffort not stated | – | – | – | 38.5%#34 | Vals AI | |
| Tax Agent Benchnot in indexeffort not stated | – | – | – | 23.7%#40 | Vals AI | |
| Terminal-Bench 2.0 (Vals)not in indexeffort not stated | – | – | – | 68.5%#3 | Vals AI | |
| Arena Searchnot in indexeffort not stated | – | – | – | 1210#12 | Arena (LMArena) | |
| PostTrainBenchnot in index | – | 28.6%#8 | – | – | Epoch AI Benchmarking Hub | |
| ExploitBenchnot in indexeffort not stated | – | – | – | 26.5%#3 | Epoch AI Benchmarking Hub | |
| GBAEvalnot in indexeffort not stated | – | – | – | 43.8%#12 | Epoch AI Benchmarking Hub | |
| Vending-Bench 2not in indexeffort not stated | – | – | – | 10936.8#6 | Andon Labs |
Maths
| Benchmark | high | xhigh | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|
| FrontierMath Tiers 1–3 | – | – | 70.2%#28 | – | Epoch AI Benchmarking Hub | |
| FrontierMath Tier 4 | – | – | 31.7%#36 | – | Epoch AI Benchmarking Hub | |
| OTIS Mock AIME | – | 97.8%#30 | 86.7%#86 | – | Epoch AI Benchmarking Hub | |
| ProofBench | – | – | 54.0%#27 | – | Vals AI | |
| LiveBench Mathematicsnot in index | – | 92.8%#26 | – | – | LiveBench | |
| AIME (Vals)effort not stated | – | – | – | 96.3%#7 | Vals AI | |
| AIME 2026possible contamination | – | 95.8%#13 | – | – | MathArena | |
| HMMT February 2026possible contamination | – | 93.9%#10 | – | – | MathArena | |
| MathArena Apexpossible contamination | – | 40.6%#7 | – | – | MathArena | |
| Arena Maths | 1504#14 | – | – | 1491#28 | Arena (LMArena) |
Knowledge
| Benchmark | no reasoning | xhigh | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|
| SimpleQA Verified | – | 51.7%#25 | – | – | Epoch AI Benchmarking Hub | |
| LiveBench 1.0 Data Analysisnot in index | – | 78.3%#25 | – | – | LiveBench | |
| AA-Omniscience | 14.8#83 | – | 27.3#42 | – | Artificial Analysis | |
| MMLU-Proeffort not stated | – | – | – | 89.9%#8 | Vals AI | |
| LegalBencheffort not stated | – | – | – | 85.3%#24 | Vals AI | |
| CorpFineffort not stated | – | – | – | 66.1%#22 | Vals AI | |
| TaxEvaleffort not stated | – | – | – | 75.3%#20 | Vals AI | |
| CaseLaw v2not in indexeffort not stated | – | – | – | 68.4%#5 | Vals AI | |
| Excel Modeling Benchmarknot in indexeffort not stated | – | – | – | 63.7%#27 | Vals AI | |
| MedCodenot in indexeffort not stated | – | – | – | 54.9%#7 | Vals AI | |
| MedScribenot in indexeffort not stated | – | – | – | 83.0%#47 | Vals AI | |
| EBR-benchnot in index | – | – | 19.1%#17 | – | Epoch AI Benchmarking Hub | |
| GDP.pdfnot in index | – | – | 21.0%#30 | – | Epoch AI Benchmarking Hub | |
| AA-Omniscience: accuracynot in index | 44.7%#92 | – | 48.9%#68 | – | Artificial Analysis | |
| AA-Omniscience: non-hallucinationnot in index | 45.9%#140 | – | 57.7%#85 | – | Artificial Analysis |
Instruction following
| Benchmark | no reasoning | high | xhigh | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|---|
| LiveBench Languagenot in index | – | – | 77.9%#40 | – | – | LiveBench | |
| LiveBench Instruction Followingnot in index | – | – | 66.7%#39 | – | – | LiveBench | |
| IFBench | 43.6%#221 | – | – | 58.6%#131 | – | Artificial Analysis | |
| Arena Instruction Followingnot in index | – | 1502#5 | – | – | 1493#11 | Arena (LMArena) |
Human preference
| Benchmark | high | not stated | Source | Trend |
|---|---|---|---|---|
| Arena Text | 1501#7 | 1494#11 | Arena (LMArena) | |
| EQ-Bench 4effort not stated | – | 1311#5 | EQ-Bench | |
| Arena Creative Writingnot in index | 1489#7 | 1482#11 | Arena (LMArena) | |
| Arena Multi-turnnot in index | 1516#5 | 1514#6 | Arena (LMArena) | |
| Arena Longer Queriesnot in index | 1515#6 | 1508#9 | Arena (LMArena) |
Multimodal
| Benchmark | no reasoning | high | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|
| Arena Vision | – | 1313#9 | – | 1317#5 | Arena (LMArena) | |
| MMMU-Pro | 76.4%#89 | – | 78.8%#68 | – | Artificial Analysis | |
| MMMU-Pro (Vals)not in indexeffort not stated | – | – | – | 85.5%#24 | Vals AI | |
| MortgageTaxnot in indexeffort not stated | – | – | – | 70.3%#3 | Vals AI | |
| SAGEnot in indexeffort not stated | – | – | – | 56.1%#1 | Vals AI | |
| Blueprint-Bench 2not in indexeffort not stated | – | – | – | 24.5%#24 | Epoch AI Benchmarking Hub |
Long context
| Benchmark | no reasoning | high | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|
| AA-LCR | 75.7%#154 | – | 78.7%#110 | – | Artificial Analysis | |
| Arena Documentnot in index | – | 1493#5 | – | 1494#3 | Arena (LMArena) |
Composite
| Benchmark | no reasoning | xhigh | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|
| Epoch Capabilities Indexnot in indexeffort not stated | – | – | – | 156.8#26 | Epoch AI Benchmarking Hub | |
| LiveBench 1.0not in index | – | 76.5%#29 | – | – | LiveBench | |
| AA Intelligence Index v4.3.2 | 30.9#116 | – | 40.7#62 | – | Artificial Analysis | |
| Vals RSI Indexnot in index | – | – | 19.1%#19 | – | Vals AI | |
| Vals Multimodal Indexnot in indexeffort not stated | – | – | – | 67.4%#10 | Vals AI |
Where it wins
Benchmarks where this configuration ranks in the top five of every configuration measured.
Where to run it
Every provider serving this model through OpenRouter, with throughput and first-token latency measured on live traffic over the last 30 minutes and each provider’s own price. Purple marks the best in each column.
| Provider | Speed | First token | Input $/M | Output $/M | Context | Quantisation |
|---|---|---|---|---|---|---|
| Google Vertex | 82 tok/s | 1.92 s | $5.00 | $25.00 | 1M | – |
| Amazon Bedrock | 60 tok/s | 1.19 s | $5.00 | $25.00 | 1M | – |
| Claude Platform on AWS | 48 tok/s | 1.05 s | $5.00 | $25.00 | 1M | – |
| Anthropic | 41 tok/s | 0.62 s | $5.00 | $25.00 | 1M | – |
What a task costs
Estimates from list price, output speed and time to first answer for the best configuration. “With caching” assumes three-quarters of the input is served from the prompt cache at $0.500 per 1M. Reasoning tokens are not modelled.
| Workload | Tokens in / out | Cost | With caching | Time |
|---|---|---|---|---|
| Chat reply | 400 / 300 | $0.0095 | $0.0081 | 6.2 s |
| Summarize a 30-page report | 12,000 / 600 | $0.075 | $0.035 | 11.2 s |
| Code edit | 6,000 / 1,500 | $0.068 | $0.047 | 26.2 s |
| Agentic coding session | 60,000 / 4,000 | $0.400 | $0.198 | 1.1 min |
| Structured extraction | 2,000 / 200 | $0.015 | $0.0083 | 4.6 s |
More from Anthropic
Compare Claude Opus 4.7 with…
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- Claude Opus 4.7 vs GPT-5.3-Codex
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- Claude Opus 4.7 vs Qwen3.8 Max
- Claude Opus 4.7 vs Claude Opus 4.8
- Claude Opus 4.7 vs GPT-5.4 Pro
- Claude Opus 4.7 vs Muse Spark 1.2
- Claude Opus 4.7 vs Gemini 3.5 Flash
- Claude Opus 4.7 vs Qwen3.8 2.4T A95B
- Claude Opus 4.7 vs Claude Opus 4.6
- Claude Opus 4.7 vs GLM 5.3 Flash
- Claude Opus 4.7 vs Muse Spark 1.1
- Claude Opus 4.7 vs GLM 5.2
- Claude Opus 4.7 vs Qwen3.6 Max
See also
Questions people ask
- What are Claude Opus 4.7's benchmark scores?
- As of 24 Oct 2026, Claude Opus 4.7 scores 63.3 ±2.7 on the BenchLeader Index, top 100, strongest in human preference (68) and weakest in coding (61). That rests on 22 independent benchmark results, and every score on this page links to its publisher.
- How does Claude Opus 4.7 rank?
- Claude Opus 4.7 is #66 of 785 ranked configurations on 24 Oct 2026 (top 100). 140 other configurations score within its margin, so the exact position matters less than the band. The leader is Claude Opus 5.5 (max effort) at 72.6.
- How much does Claude Opus 4.7 cost per 1M tokens?
- As of 24 Oct 2026, Claude Opus 4.7 costs $5.00 per 1M input tokens and $25.00 per 1M output tokens, $10.00 blended (three input tokens per output token).
- Is Claude Opus 4.7 better than Qwen3.8 Max?
- As of 24 Oct 2026, Claude Opus 4.7 and Qwen3.8 Max (max) are neck and neck on quality (63.3 vs 63.3 on the BenchLeader Index, inside the ±4.5 margin of error), and Qwen3.8 Max (max) costs 3.3× less, which makes it the better buy for most workloads. The head-to-head page has the benchmark-by-benchmark detail.
- When was Claude Opus 4.7 released?
- Anthropic released Claude Opus 4.7 on 16 Apr 2026. BenchLeader has results for it at 7 reasoning-effort settings.
Data as of 24 Oct 2026. Compare these configurations.
Cite as: BenchLeader, “Claude Opus 4.7: benchmarks, pricing, speed and rank”, data as of 24 Oct 2026, https://www.benchleader.com/models/claude-opus-4-7.