BenchLeader

Claude Opus 5

Reasoning effort

Claude Opus 5 is an Anthropic proprietary reasoning model, released 24 Jul 2026. Its best configuration (max reasoning effort) ranks #15 of 775 on the BenchLeader Index at 68.9 ±2.7, in the top 25. The ± is the point: 54 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 (87) and lowest in agents & tools (64). At $10.00 per million tokens blended it is among the most expensive ranked models. Output speed of 54 tokens per second puts it slower than most, with a first answer in 68.8 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
$10.00/M
$5.00 in · $25.00 out
Output speed
54 tok/s
measured by Artificial Analysis
First answer
69 s
first token 3.48 s
Context
1M
Full answer
78 s
median, reasoning included
Cost per run
$5.86
one full Intelligence Index run
Released
24 Jul 2026
How it scores by categoryDashed line = average model (50). One step of 15 = one standard deviation.
  1. Overall index69
  2. Reasoning74
  3. Coding70
  4. Agents & tools64
  5. Maths71
  6. Knowledge72
  7. Human preference69
  8. Multimodal68
  9. Long context65
  10. Composite87

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.

ModelReleasedIndexRank
Claude Opus 5.5max22 Sept 202672.7#1
Claude Opus 5maxthis page24 Jul 202668.9#15
Claude Opus 4.8max28 May 202663.4#64
Claude Opus 4.716 Apr 202663.4#63
Claude Opus 4.6high5 Feb 202662.9#76
Claude Opus 4.5thinking24 Nov 202560.0#119
Claude Opus 4.1thinking5 Aug 202556.5#199
Claude Opus 4thinking22 May 202555.1#230
Claude 3 Opus4 Mar 202439.2#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.

EffortIndexRankSpeedFirst answerChat reply costCategories
low61.4#9853 tok/s2.06 s$0.0095Agents & tools 53 · Coding 51 · Composite 74 · Knowledge 74 · Long context 66 · Maths 64 · Multimodal 63 · Reasoning 71
medium64.6#4755 tok/s4.41 s$0.0095Agents & tools 60 · Coding 55 · Composite 80 · Knowledge 76 · Long context 66 · Multimodal 65 · Reasoning 85
high68.0#1751 tok/s20 s$0.0095Agents & tools 65 · Coding 69 · Composite 84 · Human preference 69 · Knowledge 77 · Long context 65 · Maths 71 · Multimodal 66 · Reasoning 72
xhigh67.5#2453 tok/s28 s$0.0095Agents & tools 66 · Coding 61 · Composite 85 · Knowledge 77 · Long context 65 · Multimodal 67 · Reasoning 87
maxbest68.9#1554 tok/s69 s$0.0095Agents & tools 64 · Coding 70 · Composite 87 · Human preference 69 · Knowledge 72 · Long context 65 · Maths 71 · Multimodal 68 · Reasoning 74
not stated65.4#3864 tok/s3.48 s$0.0095Agents & tools 66 · Coding 68 · Composite 66 · Human preference 78 · Knowledge 66 · Maths 66 · Reasoning 71

What more thinking costs

Turning the effort up buys index points and multiplies the bill. Here max costs 5.3× low for +7.5 on the index — 3.1 points per doubling of spend. Compare that with other models.

low $1.10max $5.86

How its index has moved

8 Sept 2026 to 19 Oct 2026
636873
  • max
  • high
  • xhigh
  • not stated

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

Benchmarklowmediumhighxhighmaxnot statedSourceTrend
GPQA Diamond87.9%#64–––93.9%#1592.9%#22Epoch AI Benchmarking Hub
SimpleBencheffort not stated–––––80.6%#2SimpleBench
Arena Hard Prompts––1514#13–1514#14–Arena (LMArena)
LiveBench 2.0 Reasoningnot in indexeffort not stated–––––91.2%#8LiveBench
LiveBench 1.0 Reasoningnot in index––––91.2%#8–LiveBench
GPQA Diamond (AA)not in index88.9%#8491.9%#4493.7%#1193.7%#1193.2%#22–Artificial Analysis
Humanity's Last Exam (AA)not in index43.4%#5751.3%#2352.8%#1954.4%#1454.9%#10–Artificial Analysis
GPQA Diamond (Vals)not in indexeffort not stated–––––93.4%#7Vals AI
ARC-AGI-1––97.5%#12–97.5%#12–ARC Prize
ARC-AGI-2––88.3%#21–90.4%#13–ARC Prize
ARC-AGI-3––30.2%#16–––ARC Prize
CritPt23.1%#5126.9%#3628.3%#2627.7%#2929.1%#20–Artificial Analysis
MysteryMechanismnot in indexeffort not stated–––––37.4%#7Vals AI
Chess Puzzlesnot in index27.0%#71–––43.0%#33–Epoch AI Benchmarking Hub
Mystery Game Puzzlesnot in index––––59.0%#637.0%#18Epoch AI Benchmarking Hub
LMCAnot in index62.6%#2862.9%#2363.7%#2064.5%#1563.3%#22–Epoch AI Benchmarking Hub
DTBenchnot in index93.1%#6794.9%#4697.9%#397.9%#397.6%#5–Epoch AI Benchmarking Hub
ForecastBenchnot in index––––66.5%#2–ForecastBench
BTF-3not in index–––12.0%#13––Epoch AI Benchmarking Hub

Coding

Benchmarklowmediumhighxhighmaxnot statedSourceTrend
SciCode48.0%#12250.7%#10254.3%#6255.0%#5256.4%#39–SciCode
WeirdML––91.6%#8–91.8%#786.3%#13WeirdML
FrontierCode––––53.4%#3–Cognition
Arena Coding––1533#18–1529#22–Arena (LMArena)
Arena WebDev––1659#14–1689#8–Arena (LMArena)
LiveBench 2.0 Codingnot in indexeffort not stated–––––90.8%#11LiveBench
LiveBench 1.0 Codingnot in index––––81.5%#14–LiveBench
SciCode (AA)not in index49.2%#11651.5%#9555.4%#5055.7%#4656.4%#38–Artificial Analysis
LiveCodeBencheffort not stated–––––89.0%#4Vals AI
IOIeffort not stated–––––84.3%#8Vals AI
SWE-bench (Vals)not in indexeffort not stated–––––97.0%#1Vals AI
Code Migrationnot in indexeffort not stated–––––57.5%#8Vals AI
ProgramBenchnot in indexeffort not stated–––––3.0%#5Vals AI
Vibe Code Bench 1-100not in indexeffort not stated–––––28.5%#3Vals AI
Vibe Code Bench v1.1not in indexeffort not stated–––––88.4%#9Vals AI
SWE Atlas: Codebase QnAnot in index–––63.2%#1––Scale AI SEAL
SWE Atlas: Test Writingnot in index–––62.2%#2––Scale AI SEAL
DeepSWE v1.1not in index58.1%#3568.9%#1772.8%#773.2%#673.7%#3–Epoch AI Benchmarking Hub
CursorBenchnot in index40.7%#3843.3%#2944.7%#2546.1%#2146.6%#19–Cursor
ALE-Benchnot in index––2164.6#5–––Epoch AI Benchmarking Hub
FrontierSWEnot in index––––52.0%#6–Epoch AI Benchmarking Hub
Terminal-Bench 4.0 (AA)not in index26.3%#5034.3%#3646.0%#2346.5%#2249.0%#20–Artificial Analysis
Terminal-Bench 2.1 (AA)not in index76.4%#5986.1%#2187.6%#1888.0%#1289.1%#7–Artificial Analysis
Startrise Frontendnot in indexeffort not stated–––––82.3%#1Startrise

Agents & tools

Benchmarklowmediumhighxhighmaxnot statedSourceTrend
Terminal-Bench34.9%#5544.9%#4150.3%#3353.9%#2751.8%#31–Terminal-Bench
OSWorld-Verified 2.022.3%#625.3%#529.0%#330.2%#231.4%#1–OSWorld
APEX-Agents––––65.8%#6–Mercor
Arena Agent––––8.1#9–Arena (LMArena)
LiveBench Long Agenticnot in indexeffort not stated–––––62.1%#8LiveBench
LiveBench Browsernot in indexeffort not stated–––––84.0%#10LiveBench
LiveBench Agentic Codingnot in index––––65.2%#5–LiveBench
Terminal-Bench 2.1 (Vals)effort not stated–––––84.6%#5Vals AI
MCP Atlas–––85.8%#3––Scale AI SEAL
HiL-Bencheffort not stated–––––57.0%#10Scale AI SEAL
τ³-bench Bankingnot in index––––48.7%#2–τ²-bench
GDPval-AA v2.1not in index40.1%#10349.6%#5254.8%#3459.5%#1461.1%#10–Artificial Analysis
τ³-Banking (AA)30.3%#6438.6%#3644.7%#1643.3%#1942.1%#23–Artificial Analysis
Analyst Agent (AA)not in index––––53.8%#6–Artificial Analysis
CUA-benchnot in index––––9.0%#4–Vals AI
CyberBenchnot in indexeffort not stated–––––65.4%#30Vals AI
Finance Agent v2not in indexeffort not stated–––––58.6%#10Vals AI
Legal Research Benchnot in indexeffort not stated–––––55.3%#1Vals AI
SkillsBenchnot in indexeffort not stated–––––60.4%#8Vals AI
SREBenchnot in indexeffort not stated–––––12.2%#11Vals AI
Tax Agent Benchnot in indexeffort not stated–––––45.5%#3Vals AI
Terminal-Bench 4.0 (Vals)not in indexeffort not stated–––––53.5%#8Vals AI
Terminal-Bench Sciencenot in indexeffort not stated–––––27.1%#9Vals AI
Time Horizon Index: KSPnot in indexeffort not stated–––––18.8%#6Vals AI
Arena Searchnot in index––1214#10–––Arena (LMArena)
BALROGnot in index––––63.4%#2–BALROG
PostTrainBenchnot in indexeffort not stated–––––35.0%#3Epoch AI Benchmarking Hub
GBAEvalnot in indexeffort not stated–––––79.6%#1Epoch AI Benchmarking Hub
Vending-Bench 2not in indexeffort not stated–––––11181.9#4Andon Labs
AutomationBenchnot in index51.8%#7354.3%#6053.6%#6453.2%#6656.6%#52–Artificial Analysis
GDP.pdf (AA)not in index17.2%#8220.0%#6419.6%#6721.0%#5521.6%#52–Artificial Analysis
EnterpriseOps-Gymnot in index––––47.5%#7–Artificial Analysis
AA-Briefcase v1.1not in index–1435#381561#201634#131659#8–Artificial Analysis
Terminal-Bench-Science 0.1 (AA)not in index––––28.6%#13–Artificial Analysis
DeepSec-Bench (AA)––––25.9%#7–Artificial Analysis
FACTS Searchnot in indexeffort not stated–––––85.3%#6Google

Maths

Benchmarklowhighmaxnot statedSourceTrend
FrontierMath Tiers 1–3––85.6%#12–Epoch AI Benchmarking Hub
FrontierMath Tier 4––73.2%#18–Epoch AI Benchmarking Hub
OTIS Mock AIME93.3%#58–98.9%#1897.8%#30Epoch AI Benchmarking Hub
ProofBench––99.0%#4–Vals AI
LiveBench Mathematicsnot in index––95.7%#15–LiveBench
Arena Maths–1522#41514#7–Arena (LMArena)

Knowledge

Benchmarklowmediumhighxhighmaxnot statedSourceTrend
SimpleQA Verified––––59.9%#17–Epoch AI Benchmarking Hub
LiveBench 2.0 Data Analysisnot in indexeffort not stated–––––74.6%#28LiveBench
LiveBench Researchnot in indexeffort not stated–––––88.9%#1LiveBench
LiveBench 1.0 Data Analysisnot in index––––74.5%#37–LiveBench
AA-Omniscience28.6#3831.0#2933.7#2535.4#2337.1#22–Artificial Analysis
MMLU-Proeffort not stated–––––91.6%#2Vals AI
LegalBencheffort not stated–––––87.0%#9Vals AI
CorpFineffort not stated–––––73.2%#1Vals AI
TaxEvaleffort not stated–––––75.1%#22Vals AI
BioMysteryBenchnot in indexeffort not stated–––––79.3%#3Vals AI
Excel Modeling Benchmarknot in indexeffort not stated–––––73.6%#6Vals AI
MedCodenot in indexeffort not stated–––––63.6%#1Vals AI
MedScribenot in indexeffort not stated–––––91.0%#4Vals AI
Public Benefits Benchnot in indexeffort not stated–––––76.9%#1Vals AI
DrugDiscoveryBenchnot in index––––53.7%#4–Scale AI SEAL
EBR-benchnot in index––––45.7%#7–Epoch AI Benchmarking Hub
GDP.pdfnot in index––––24.0%#19–Epoch AI Benchmarking Hub
AA-Omniscience: accuracynot in index56.0%#3557.1%#3158.9%#2459.5%#2260.9%#15–Artificial Analysis
AA-Omniscience: non-hallucinationnot in index37.8%#17339.3%#16138.8%#16640.5%#15739.2%#162–Artificial Analysis

Instruction following

BenchmarkhighmaxSourceTrend
LiveBench Languagenot in index–88.7%#5LiveBench
LiveBench Instruction Followingnot in index–63.8%#49LiveBench
Arena Instruction Followingnot in index1496#81494#9Arena (LMArena)

Human preference

Benchmarkhighmaxnot statedSourceTrend
Arena Text1490#151490#14–Arena (LMArena)
EQ-Bench 4effort not stated––1385#1EQ-Bench
Arena Creative Writingnot in index1471#141471#15–Arena (LMArena)
Arena Multi-turnnot in index1484#311486#28–Arena (LMArena)
Arena Longer Queriesnot in index1503#111502#13–Arena (LMArena)

Multimodal

Benchmarklowmediumhighxhighmaxnot statedSourceTrend
Arena Vision––1320#3–––Arena (LMArena)
LiveBench Designnot in indexeffort not stated–––––83.0%#7LiveBench
MMMU-Pro79.8%#5581.6%#3782.4%#3284.0%#2284.7%#15–Artificial Analysis
MMMU-Pro (Vals)not in indexeffort not stated–––––89.9%#2Vals AI
MortgageTaxnot in indexeffort not stated–––––72.1%#1Vals AI
SAGEnot in indexeffort not stated–––––49.4%#21Vals AI
Blueprint-Bench 2not in indexeffort not stated–––––30.4%#18Epoch AI Benchmarking Hub

Long context

BenchmarklowmediumhighxhighmaxSourceTrend
AA-LCR81.3%#5582.0%#4679.0%#10580.3%#7079.3%#97Artificial Analysis
Arena Documentnot in index––1490#7––Arena (LMArena)
MLCRnot in index53.9%#1156.1%#859.4%#658.3%#755.6%#9Artificial Analysis

Composite

Benchmarklowmediumhighxhighmaxnot statedSourceTrend
Epoch Capabilities Indexnot in indexeffort not stated–––––163.9#7Epoch AI Benchmarking Hub
LiveBench 2.0effort not stated–––––82.1%#8LiveBench
LiveBench 1.0not in index––––80.1%#13–LiveBench
AA Intelligence Index v4.3.239.4#6944.8#3848.1#2449.7#2050.8#18–Artificial Analysis
Vals Multimodal Indexnot in indexeffort not stated–––––73.9%#2Vals AI

Safety & honesty

Benchmarknot statedSourceTrend
FORTRESSnot in index16.8%#49Scale AI SEAL

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.

ProviderSpeedFirst tokenInput $/MOutput $/MContextQuantisation
Anthropic145 tok/s0.86 s$10.00$50.001M–
Google Vertex73 tok/s2.38 s$5.00$25.001M–
Google Vertex73 tok/s1.39 s$5.50$27.501M–
Amazon Bedrock67 tok/s4.09 s$5.00$25.001M–
Claude Platform on AWS66 tok/s3.55 s$5.00$25.001M–
Anthropic60 tok/s0.73 s$5.00$25.001M–
Azure52 tok/s1.36 s$5.00$25.001M–

Price history

Listed price per 1M tokens over time, as recorded by OpenRouter for the provider with the longest history.

$0.00$7.56$15.13$22.69$30.25Aug 26Sept 26Oct 26
input outputnow $5.50 in · $27.50 out

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.

WorkloadTokens in / outCostWith cachingTime
Chat reply400 / 300$0.0095$0.00811.2 min
Summarize a 30-page report12,000 / 600$0.075$0.0351.3 min
Code edit6,000 / 1,500$0.068$0.0471.6 min
Agentic coding session60,000 / 4,000$0.400$0.1982.4 min
Structured extraction2,000 / 200$0.015$0.00831.2 min

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See also

Data as of 21 Oct 2026. Compare these configurations.

Cite as: BenchLeader, “Claude Opus 5: benchmarks, pricing, speed and rank”, https://www.benchleader.com/models/claude-opus-5, data as of 21 Oct 2026.