AnthropicClaude Opus 5.5
Reasoning effort
Claude Opus 5.5 is an Anthropic proprietary reasoning model, released 22 Sept 2026. Its best configuration (max reasoning effort) ranks #1 of 775 on the BenchLeader Index at 72.7 ±5.6, in the top ten. The ± is the point: 27 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 composite (94) and lowest in agents & tools (64). At $8.00 per million tokens blended it is among the most expensive ranked models. Output speed of 95 tokens per second puts it faster than most, with a first answer in 608.7 s. It has been measured at 6 reasoning-effort settings; this summary describes the best-scoring one, and the tabs above switch between them. Last measured 19 Oct 2026.
- Blended price
- $8.00/M
- $4.00 in · $20.00 out
- Output speed
- 95 tok/s
- measured by Artificial Analysis
- First answer
- 609 s
- first token 4.10 s
- Context
- 1M
- Full answer
- 614 s
- median, reasoning included
- Cost per run
- $5.98
- one full Intelligence Index run
- Released
- 22 Sept 2026
- Overall index73
- Reasoning76
- Coding82
- Agents & tools64
- Maths74
- Knowledge79
- Multimodal71
- Long context68
- Composite94
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 5.5maxthis page | 22 Sept 2026 | 72.7 | #1 |
| Claude Opus 5max | 24 Jul 2026 | 68.9 | #15 |
| Claude Opus 4.8max | 28 May 2026 | 63.4 | #64 |
| Claude Opus 4.7 | 16 Apr 2026 | 63.4 | #63 |
| Claude Opus 4.6high | 5 Feb 2026 | 62.9 | #76 |
| Claude Opus 4.5thinking | 24 Nov 2025 | 60.0 | #119 |
| Claude Opus 4.1thinking | 5 Aug 2025 | 56.5 | #199 |
| Claude Opus 4thinking | 22 May 2025 | 55.1 | #230 |
| Claude 3 Opus | 4 Mar 2024 | 39.2 | #681 |
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 |
|---|---|---|---|---|---|---|
| low | 64.7 | #46 | 80 tok/s | 5.98 s | $0.0076 | Coding 66 · Composite 77 · Knowledge 79 · Long context 65 · Multimodal 68 · Reasoning 66 |
| medium | 66.5 | #31 | 81 tok/s | 23 s | $0.0076 | Agents & tools 53 · Coding 68 · Composite 87 · Knowledge 80 · Long context 67 · Multimodal 69 · Reasoning 77 |
| high | 69.4 | #12 | 80 tok/s | 34 s | $0.0076 | Coding 69 · Composite 90 · Human preference 71 · Knowledge 80 · Long context 67 · Maths 69 · Multimodal 68 · Reasoning 78 |
| xhigh | 70.1 | #6 | 84 tok/s | 114 s | $0.0076 | Coding 75 · Composite 92 · Knowledge 81 · Long context 68 · Multimodal 70 · Reasoning 80 |
| maxbest | 72.7 | #1 | 95 tok/s | 609 s | $0.0076 | Agents & tools 64 · Coding 82 · Composite 94 · Knowledge 79 · Long context 68 · Maths 74 · Multimodal 71 · Reasoning 76 |
| not stated | 61.9 | #93 | 73 tok/s | 4.10 s | $0.0076 | Agents & tools 72 · Coding 74 · Composite 71 · Knowledge 55 |
What more thinking costs
Turning the effort up buys index points and multiplies the bill. Here max costs 11× low for +8.0 on the index — 2.3 points per doubling of spend. Compare that with other models.
How its index has moved
22 Sept 2026 to 20 Oct 2026- max
- xhigh
- high
- medium
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 | low | medium | high | xhigh | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|---|---|
| GPQA Diamond | – | – | – | – | 90.6%#40 | – | Epoch AI Benchmarking Hub | |
| Arena Hard Prompts | – | – | 1533#2 | – | – | – | Arena (LMArena) | |
| LiveBench 2.0 Reasoningnot in indexeffort not stated | – | – | – | – | – | 92.2%#4 | LiveBench | |
| LiveBench 1.0 Reasoningnot in index | – | – | – | 90.7%#10 | 92.2%#3 | – | LiveBench | |
| Humanity's Last Exam (AA)not in index | 48.3%#33 | 54.7%#11 | 55.6%#7 | 57.5%#4 | 61.4%#1 | – | Artificial Analysis | |
| ARC-AGI-1 | 88.5%#81 | 97.5%#12 | 98.5%#1 | 97.5%#12 | 97.5%#12 | – | ARC Prize | |
| ARC-AGI-2 | 70.1%#56 | 87.5%#23 | 93.3%#3 | 92.5%#5 | 91.7%#9 | – | ARC Prize | |
| CritPt | 17.7%#73 | 27.7%#29 | 30.9%#12 | 31.7%#3 | 31.7%#3 | – | Artificial Analysis | |
| MysteryMechanismnot in indexeffort not stated | – | – | – | – | – | 49.5%#2 | Vals AI | |
| Chess Puzzlesnot in index | – | – | – | – | 67.0%#5 | – | Epoch AI Benchmarking Hub | |
| Mystery Game Puzzlesnot in index | – | – | – | – | 71.0%#3 | – | Epoch AI Benchmarking Hub | |
| LMCAnot in index | 64.9%#13 | 65.7%#7 | 65.9%#6 | 66.2%#4 | 68.2%#2 | – | Epoch AI Benchmarking Hub | |
| DTBenchnot in index | 95.5%#38 | 96.5%#22 | 96.5%#22 | 97.3%#9 | 98.9%#1 | – | Epoch AI Benchmarking Hub |
Coding
| Benchmark | low | medium | high | xhigh | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|---|---|
| SciCode | 58.6%#22 | 59.3%#14 | 60.4%#9 | 65.0%#2 | 66.9%#1 | – | SciCode | |
| FrontierCode | – | 54.6%#1 | – | – | – | – | Cognition | |
| Arena Coding | – | – | 1548#6 | – | – | – | Arena (LMArena) | |
| Arena WebDev | – | – | – | – | 1807#1 | – | Arena (LMArena) | |
| LiveBench 2.0 Codingnot in indexeffort not stated | – | – | – | – | – | 96.3%#3 | LiveBench | |
| LiveBench 1.0 Codingnot in index | – | – | – | 89.3%#2 | 89.3%#2 | – | LiveBench | |
| SciCode (AA)not in index | 58.6%#22 | 59.3%#15 | 60.4%#10 | 65.0%#2 | 66.9%#1 | – | Artificial Analysis | |
| IOIeffort not stated | – | – | – | – | – | 95.1%#4 | Vals AI | |
| Code Migrationnot in indexeffort not stated | – | – | – | – | – | 66.7%#4 | Vals AI | |
| ProgramBenchnot in indexeffort not stated | – | – | – | – | – | 18.5%#1 | Vals AI | |
| Vibe Code Bench 1-100not in indexeffort not stated | – | – | – | – | – | 30.4%#2 | Vals AI | |
| Vibe Code Bench v1.1not in indexeffort not stated | – | – | – | – | – | 90.3%#5 | Vals AI | |
| MirrorCodenot in index | – | – | – | – | 77.4%#1 | – | Epoch AI Benchmarking Hub | |
| CursorBenchnot in index | 43.7%#28 | 52.5%#8 | 56.0%#2 | 56.0%#2 | 57.8%#1 | – | Cursor | |
| ALE-Benchnot in index | – | – | 2147.4#6 | – | – | – | Epoch AI Benchmarking Hub | |
| FrontierSWEnot in index | – | – | – | – | 62.3%#2 | – | Epoch AI Benchmarking Hub | |
| Terminal-Bench 4.0 (AA)not in index | 31.3%#43 | 52.5%#14 | 56.6%#9 | 59.6%#2 | 59.6%#2 | – | Artificial Analysis | |
| Startrise Frontendnot in index | – | – | 80.2%#2 | – | – | 71.1%#17 | Startrise | |
| FrontierCode 1.1 (AA)not in index | 42.7%#19 | 57.0%#1 | 54.0%#2 | 53.5%#3 | 52.2%#4 | – | Artificial Analysis |
Agents & tools
| Benchmark | low | medium | high | xhigh | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|---|---|
| Terminal-Bench | – | – | – | – | 64.8%#11 | – | Terminal-Bench | |
| Remote Labor Indexeffort not stated | – | – | – | – | – | 21.3%#1 | Scale AI / CAIS | |
| APEX-Agents | – | 52.5%#25 | – | – | 73.5%#3 | – | Mercor | |
| Arena Agent | – | – | – | – | 20.4#1 | – | Arena (LMArena) | |
| LiveBench Long Agenticnot in indexeffort not stated | – | – | – | – | – | 85.0%#1 | LiveBench | |
| LiveBench Browsernot in indexeffort not stated | – | – | – | – | – | 80.0%#16 | LiveBench | |
| LiveBench Agentic Codingnot in index | – | – | – | 65.3%#4 | 71.7%#2 | – | LiveBench | |
| Terminal-Bench 2.1 (Vals)effort not stated | – | – | – | – | – | 87.6%#1 | Vals AI | |
| HiL-Bencheffort not stated | – | – | – | – | – | 59.0%#8 | Scale AI SEAL | |
| GDPval-AA v2.1not in index | 36.8%#114 | 54.2%#38 | 60.2%#13 | 66.5%#4 | 68.3%#1 | – | Artificial Analysis | |
| ITBench SRE (AA)not in index | – | – | – | – | 38.2%#23 | – | Artificial Analysis | |
| Analyst Agent (AA)not in index | – | – | – | – | 56.3%#4 | – | Artificial Analysis | |
| CUA-benchnot in index | – | – | – | – | 14.0%#2 | – | Vals AI | |
| CyberBenchnot in indexeffort not stated | – | – | – | – | – | 55.4%#37 | Vals AI | |
| Finance Agent v2not in indexeffort not stated | – | – | – | – | – | 58.6%#11 | Vals AI | |
| Harvey's Legal Agent Benchmarknot in indexeffort not stated | – | – | – | – | – | 9.2%#15 | Vals AI | |
| Legal Research Benchnot in indexeffort not stated | – | – | – | – | – | 50.5%#6 | Vals AI | |
| SREBenchnot in indexeffort not stated | – | – | – | – | – | 33.6%#4 | Vals AI | |
| Tax Agent Benchnot in indexeffort not stated | – | – | – | – | – | 45.6%#2 | Vals AI | |
| Terminal-Bench 4.0 (Vals)not in indexeffort not stated | – | – | – | – | – | 65.2%#1 | Vals AI | |
| Terminal-Bench Sciencenot in indexeffort not stated | – | – | – | – | – | 47.1%#3 | Vals AI | |
| Time Horizon Index: KSPnot in indexeffort not stated | – | – | – | – | – | 91.3%#1 | Vals AI | |
| Arena Searchnot in index | – | 1211#11 | – | – | – | – | Arena (LMArena) | |
| Vending-Bench 2not in indexeffort not stated | – | – | – | – | – | 9235.3#10 | Andon Labs | |
| AutomationBenchnot in index | 52.9%#69 | 61.2%#31 | 63.2%#23 | 65.0%#17 | 69.5%#5 | – | Artificial Analysis | |
| GDP.pdf (AA)not in index | 25.6%#27 | 25.6%#27 | 28.8%#12 | 26.6%#20 | 26.2%#22 | – | Artificial Analysis | |
| Harvey LAB-AA v1.1not in index | – | – | – | – | 4.2%#9 | – | Harvey | |
| AA-Briefcase v1.1not in index | – | 1625#14 | 1686#6 | 1764#3 | 1803#2 | – | Artificial Analysis | |
| Terminal-Bench-Science 0.1 (AA)not in index | 24.3%#14 | 43.3%#9 | 49.0%#8 | 61.9%#2 | 59.0%#3 | – | Artificial Analysis | |
| CWE-Bench (AA) | – | – | – | – | 58.3%#6 | – | Artificial Analysis | |
| DeepSec-Bench (AA) | – | – | – | – | 26.9%#5 | – | Artificial Analysis | |
| CyberGym end-to-end (AA) | – | – | – | – | 0.8%#14 | – | Artificial Analysis | |
| FACTS Searchnot in indexeffort not stated | – | – | – | – | – | 86.5%#4 |
Maths
| Benchmark | high | xhigh | max | Source | Trend |
|---|---|---|---|---|---|
| FrontierMath Tiers 1–3 | – | – | 91.2%#3 | Epoch AI Benchmarking Hub | |
| FrontierMath Tier 4 | – | – | 95.0%#6 | Epoch AI Benchmarking Hub | |
| OTIS Mock AIME | – | – | 100.0%#1 | Epoch AI Benchmarking Hub | |
| ProofBench | – | – | 100.0%#1 | Vals AI | |
| LiveBench Mathematicsnot in index | – | 96.8%#5 | 97.1%#1 | LiveBench | |
| Arena Maths | 1502#14 | – | – | Arena (LMArena) |
Knowledge
| Benchmark | low | medium | high | xhigh | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|---|---|
| SimpleQA Verified | – | – | – | – | 72.2%#5 | – | Epoch AI Benchmarking Hub | |
| LiveBench 2.0 Data Analysisnot in indexeffort not stated | – | – | – | – | – | 80.3%#8 | LiveBench | |
| LiveBench Researchnot in indexeffort not stated | – | – | – | – | – | 85.0%#8 | LiveBench | |
| LiveBench 1.0 Data Analysisnot in index | – | – | – | 79.8%#11 | 80.3%#8 | – | LiveBench | |
| AA-Omniscience | 38.9#19 | 40.3#17 | 40.6#15 | 42.6#7 | 46.4#1 | – | Artificial Analysis | |
| PRBench Legaleffort not stated | – | – | – | – | – | 47.6%#20 | Scale AI SEAL | |
| BioMysteryBenchnot in indexeffort not stated | – | – | – | – | – | 79.3%#3 | Vals AI | |
| Excel Modeling Benchmarknot in indexeffort not stated | – | – | – | – | – | 75.9%#2 | Vals AI | |
| MedCodenot in indexeffort not stated | – | – | – | – | – | 49.8%#19 | Vals AI | |
| MedScribenot in indexeffort not stated | – | – | – | – | – | 91.4%#1 | Vals AI | |
| Public Benefits Benchnot in indexeffort not stated | – | – | – | – | – | 70.6%#4 | Vals AI | |
| EBR-benchnot in index | – | – | – | – | 71.4%#2 | – | Epoch AI Benchmarking Hub | |
| GDP.pdfnot in index | – | – | – | – | 30.6%#7 | – | Epoch AI Benchmarking Hub | |
| AA-Omniscience: accuracynot in index | 63.5%#9 | 64.5%#8 | 64.6%#7 | 65.4%#4 | 66.2%#2 | – | Artificial Analysis | |
| AA-Omniscience: non-hallucinationnot in index | 32.4%#207 | 31.6%#211 | 32.4%#206 | 34.3%#191 | 41.4%#152 | – | Artificial Analysis |
Instruction following
| Benchmark | high | xhigh | max | Source | Trend |
|---|---|---|---|---|---|
| LiveBench Languagenot in index | – | 85.5%#12 | 86.3%#10 | LiveBench | |
| LiveBench Instruction Followingnot in index | – | 67.0%#38 | 65.7%#42 | LiveBench | |
| Arena Instruction Followingnot in index | 1518#2 | – | – | Arena (LMArena) |
Human preference
| Benchmark | high | Source | Trend |
|---|---|---|---|
| Arena Text | 1508#3 | Arena (LMArena) | |
| Arena Creative Writingnot in index | 1519#1 | Arena (LMArena) | |
| Arena Multi-turnnot in index | 1501#10 | Arena (LMArena) | |
| Arena Longer Queriesnot in index | 1523#2 | Arena (LMArena) |
Multimodal
| Benchmark | low | medium | high | xhigh | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|---|---|
| Arena Vision | – | – | 1321#2 | – | – | – | Arena (LMArena) | |
| LiveBench Designnot in indexeffort not stated | – | – | – | – | – | 86.9%#1 | LiveBench | |
| MMMU-Pro | 84.7%#17 | 85.7%#8 | 85.8%#7 | 86.6%#3 | 87.7%#1 | – | Artificial Analysis | |
| SAGEnot in indexeffort not stated | – | – | – | – | – | 45.8%#37 | Vals AI | |
| Blueprint-Bench 2not in indexeffort not stated | – | – | – | – | – | 51.2%#2 | Epoch AI Benchmarking Hub | |
| AA-3Dnot in index | – | – | – | – | 1191#2 | – | Artificial Analysis |
Long context
| Benchmark | low | medium | high | xhigh | max | Source | Trend |
|---|---|---|---|---|---|---|---|
| AA-LCR | 80.7%#64 | 84.3%#8 | 82.7%#35 | 84.7%#5 | 84.7%#5 | Artificial Analysis | |
| MLCRnot in index | – | – | – | – | 66.7%#3 | Artificial Analysis |
Composite
| Benchmark | low | medium | high | xhigh | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|---|---|
| Epoch Capabilities Indexnot in indexeffort not stated | – | – | – | – | – | 168.8#1 | Epoch AI Benchmarking Hub | |
| LiveBench 2.0effort not stated | – | – | – | – | – | 86.5%#2 | LiveBench | |
| LiveBench 1.0not in index | – | – | – | 82.1%#5 | 83.2%#2 | – | LiveBench | |
| AA Intelligence Index v4.3.2 | 42.3#51 | 51.2#14 | 53.6#5 | 56.0#3 | 57.6#1 | – | Artificial Analysis | |
| Vals Indexnot in indexeffort not stated | – | – | – | – | – | 70.2#2 | Vals AI | |
| AA Cyber Indexnot in index | – | – | – | – | 28.7#13 | – | Artificial Analysis |
Safety & honesty
| Benchmark | max | not stated | Source | Trend |
|---|---|---|---|---|
| FORTRESSnot in index | 5.8%#68 | 13.2%#59 | Scale AI SEAL |
Where it wins
Benchmarks where this configuration ranks in the top five of every configuration measured.
- #1OTIS Mock AIME100.0% · of 275
- #1SciCode66.9% · of 216
- #1ProofBench100.0% · of 78
- #1Arena WebDev1807 · of 136
- #1Arena Agent20.4 · of 50
- #1AA Intelligence Index v4.3.257.6 · of 626
- #1MMMU-Pro87.7% · of 281
- #1AA-Omniscience46.4 · of 547
- #3FrontierMath Tiers 1–391.2% · of 117
- #3APEX-Agents73.5% · of 53
- #3CritPt31.7% · of 550
- #5SimpleQA Verified72.2% · of 86
- #5AA-LCR84.7% · of 542
- #5DeepSec-Bench (AA)26.9% · of 19
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 |
|---|---|---|---|---|---|---|
| Anthropic | 205 tok/s | 1.38 s | $8.00 | $40.00 | 1M | – |
| Google Vertex | 86 tok/s | 3.43 s | $4.00 | $20.00 | 1M | – |
| Google Vertex | 85 tok/s | 2.64 s | $4.40 | $22.00 | 1M | – |
| Claude Platform on AWS | 80 tok/s | 3.83 s | $4.00 | $20.00 | 1M | – |
| Amazon Bedrock | 79 tok/s | 4.35 s | $4.00 | $20.00 | 1M | – |
| Anthropic | 77 tok/s | 3.53 s | $4.00 | $20.00 | 1M | – |
| Amazon Bedrock | 76 tok/s | 3.44 s | $4.40 | $22.00 | 1M | – |
| Amazon Bedrock | 72 tok/s | 1.96 s | $4.40 | $22.00 | 1M | – |
| Azure | 69 tok/s | 2.93 s | $4.00 | $20.00 | 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 $0.200 per 1M. Reasoning tokens are not modelled.
| Workload | Tokens in / out | Cost | With caching | Time |
|---|---|---|---|---|
| Chat reply | 400 / 300 | $0.0076 | $0.0065 | 10.2 min |
| Summarize a 30-page report | 12,000 / 600 | $0.060 | $0.026 | 10.3 min |
| Code edit | 6,000 / 1,500 | $0.054 | $0.037 | 10.4 min |
| Agentic coding session | 60,000 / 4,000 | $0.320 | $0.149 | 10.8 min |
| Structured extraction | 2,000 / 200 | $0.012 | $0.0063 | 10.2 min |
More from Anthropic
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- Claude Opus 5.5 vs MiniMax-M3.1-Flash
- Claude Opus 5.5 vs Claude Haiku 5.5
- Claude Opus 5.5 vs Muse Spark Open
- Claude Opus 5.5 vs DeepSeek V4 Flash
- Claude Opus 5.5 vs Gemini 3.1 Pro
- Claude Opus 5.5 vs Qwen3 7
- Claude Opus 5.5 vs GPT-5.2
- Claude Opus 5.5 vs Step 5 Preview
- Claude Opus 5.5 vs Gemini 3 Pro
- Claude Opus 5.5 vs Claude Sonnet 5
- Claude Opus 5.5 vs Qwen3.8-Flash-Next
- Claude Opus 5.5 vs GPT-6 Luna
- Claude Opus 5.5 vs Claude Opus 4.5
- Claude Opus 5.5 vs GPT-5.6 Luna
- Claude Opus 5.5 vs MiMo-V2.6-Flash
- Claude Opus 5.5 vs GPT-5 Pro
- Claude Opus 5.5 vs o3
- Claude Opus 5.5 vs Kimi K2.6
- Claude Opus 5.5 vs GPT-5.2-Codex
See also
Data as of 21 Oct 2026. Compare these configurations.
Cite as: BenchLeader, “Claude Opus 5.5: benchmarks, pricing, speed and rank”, https://www.benchleader.com/models/claude-opus-5-5, data as of 21 Oct 2026.