BenchLeader

Claude Fable 5

Reasoning effort

Claude Fable 5 is an Anthropic proprietary reasoning model, released 9 Jun 2026. Its best configuration (max reasoning effort) ranks #11 of 775 on the BenchLeader Index at 69.4 ±4.4, in the top 25. The ± is the point: 52 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 (85) and lowest in instruction following (63). At $20.00 per million tokens blended it is among the most expensive ranked models. Output speed of 67 tokens per second puts it slower than most, with a first answer in 74.7 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 9 Jun 2026.

Blended price
$20.00/M
$10.00 in · $50.00 out
Output speed
67 tok/s
measured by Artificial Analysis
First answer
75 s
first token 3.61 s
Context
1M
Full answer
82 s
median, reasoning included
Cost per run
$8.75
one full Intelligence Index run
Released
9 Jun 2026
How it scores by categoryDashed line = average model (50). One step of 15 = one standard deviation.
  1. Overall index69
  2. Reasoning74
  3. Coding74
  4. Agents & tools65
  5. Maths73
  6. Knowledge81
  7. Instruction following63
  8. Long context66
  9. Composite85

Versions

Anthropic has shipped 2 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 Fable 5.1max1 Sept 202670.6#5
Claude Fable 5maxthis page9 Jun 202669.4#11

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
low––60 tok/s3.61 s$0.019Maths 66 · Reasoning 62
medium––60 tok/s3.61 s$0.019Reasoning 68
high64.8#4560 tok/s3.61 s$0.019Agents & tools 65 · Coding 69 · Human preference 70 · Maths 70 · Multimodal 68 · Reasoning 67
xhigh––60 tok/s3.61 s$0.019Knowledge 74 · Reasoning 70
maxbest69.4#1167 tok/s75 s$0.019Agents & tools 65 · Coding 74 · Composite 85 · Instruction following 63 · Knowledge 81 · Long context 66 · Maths 73 · Reasoning 74
thinking––60 tok/s3.61 s$0.019Reasoning 82
not stated67.1#2860 tok/s3.61 s$0.019Agents & tools 65 · Coding 70 · Composite 68 · Human preference 71 · Knowledge 67 · Reasoning 80

How its index has moved

8 Sept 2026 to 20 Oct 2026
596775
  • max
  • not stated
  • high

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

Benchmarklowmediumhighxhighmaxthinkingnot statedSourceTrend
GPQA Diamond78.8%#131–83.3%#102–85.9%#83––Epoch AI Benchmarking Hub
SimpleBench––––81.9%#1––SimpleBench
Arena Hard Prompts––1529#4––––Arena (LMArena)
LiveBench 2.0 Reasoningnot in indexeffort not stated––––––89.7%#14LiveBench
LiveBench 1.0 Reasoningnot in index––––89.7%#15––LiveBench
GPQA Diamond (AA)not in index––––92.6%#32––Artificial Analysis
Humanity's Last Exam (AA)not in index––––55.5%#8––Artificial Analysis
GPQA Diamond (Vals)not in indexeffort not stated––––––93.2%#10Vals AI
EnigmaEval––39.3%#1––––Scale AI SEAL
Kagi LLM Benchmark–––––91.4%#188.8%#2Kagi LLM Benchmark
ARC-AGI-190.5%#6892.5%#5195.5%#3198.5%#198.5%#1––ARC Prize
ARC-AGI-276.8%#4482.5%#3987.5%#2388.3%#2189.2%#18––ARC Prize
CritPt––––28.6%#24––Artificial Analysis
Chess Puzzlesnot in index31.0%#65–45.0%#28–47.0%#24––Epoch AI Benchmarking Hub
Mystery Game Puzzlesnot in index––––52.0%#11––Epoch AI Benchmarking Hub
LMCAnot in index59.6%#3460.3%#3361.1%#3061.0%#3160.3%#32––Epoch AI Benchmarking Hub
DTBenchnot in index91.5%#7295.7%#3596.5%#2297.3%#998.4%#2––Epoch AI Benchmarking Hub
ForecastBenchnot in index––65.7%#9–66.0%#7––ForecastBench
BTF-3not in index––13.0%#12––––Epoch AI Benchmarking Hub

Coding

Benchmarklowmediumhighxhighmaxnot statedSourceTrend
SciCode––––61.0%#5–SciCode
WeirdML––87.8%#11–91.9%#6–WeirdML
FrontierCodeeffort not stated–––––53.5%#2Cognition
GSO-Bencheffort not stated–––––78.4%#3GSO-Bench
Arena Coding––1551#2–––Arena (LMArena)
Arena WebDev––1624#21–––Arena (LMArena)
LiveBench 2.0 Codingnot in indexeffort not stated–––––98.3%#1LiveBench
LiveBench 1.0 Codingnot in index––––86.0%#6–LiveBench
SciCode (AA)not in index––––61.0%#6–Artificial Analysis
LiveCodeBencheffort not stated–––––89.8%#2Vals AI
SWE-bench (Vals)not in indexeffort not stated–––––95.0%#7Vals AI
Code Migrationnot in indexeffort not stated–––––55.1%#10Vals AI
ProgramBenchnot in indexeffort not stated–––––2.0%#10Vals AI
Vibe Code Bench v1.1not in indexeffort not stated–––––90.3%#4Vals AI
SWE Atlas: Codebase QnAnot in index–––39.0%#12––Scale AI SEAL
SWE Atlas: Refactoringnot in index–––54.8%#3––Scale AI SEAL
SWE Atlas: Test Writingnot in index–––55.6%#3––Scale AI SEAL
MirrorCodenot in index––63.9%#3–––Epoch AI Benchmarking Hub
Surface Evolver Benchnot in index––95.0%#1–––Epoch AI Benchmarking Hub
DeepSWE v1.1not in index59.6%#3365.4%#2668.6%#1869.9%#1269.7%#13–Epoch AI Benchmarking Hub
ALE-Benchnot in index––2041.3#9–––Epoch AI Benchmarking Hub
FrontierSWEnot in index––––47.0%#7–Epoch AI Benchmarking Hub
Terminal-Bench 4.0 (AA)not in index––––42.4%#27–Artificial Analysis
Terminal-Bench 2.1 (AA)not in index––––84.6%#28–Artificial Analysis
Startrise Frontendnot in indexeffort not stated–––––73.8%#11Startrise

Agents & tools

Benchmarklowmediumhighmaxnot statedSourceTrend
Terminal-Bench–––44.5%#42–Terminal-Bench
Remote Labor Indexeffort not stated––––15.8%#4Scale AI / CAIS
APEX-Agentseffort not stated––––63.6%#10Mercor
Arena Agent––8.4#8––Arena (LMArena)
LiveBench Long Agenticnot in indexeffort not stated––––53.2%#10LiveBench
LiveBench Browsernot in indexeffort not stated––––92.0%#3LiveBench
LiveBench Agentic Codingnot in index–––62.2%#10–LiveBench
Terminal-Bench Hard–––62.9%#2–Artificial Analysis
τ²-Bench Telecom (AA)not in index–––98.5%#4–Artificial Analysis
Terminal-Bench 2.1 (Vals)effort not stated––––80.5%#10Vals AI
MCP Atlaseffort not stated––––83.3%#7Scale AI SEAL
HiL-Bencheffort not stated––––56.3%#11Scale AI SEAL
τ³-bench Bankingnot in index–––39.7%#8–τ²-bench
GDPval-AA v2.1not in index–––55.5%#29–Artificial Analysis
τ³-Banking (AA)–––38.1%#38–Artificial Analysis
Analyst Agent (AA)not in index–––48.8%#12–Artificial Analysis
Finance Agent v2not in indexeffort not stated––––56.3%#19Vals AI
Legal Research Benchnot in indexeffort not stated––––49.5%#8Vals AI
Tax Agent Benchnot in indexeffort not stated––––38.3%#10Vals AI
Terminal-Bench 4.0 (Vals)not in indexeffort not stated––––41.4%#11Vals AI
Terminal-Bench Sciencenot in indexeffort not stated––––15.7%#12Vals AI
Web Search Indexnot in indexeffort not stated––––46.9%#2Vals AI
Arena Searchnot in index––1229#6––Arena (LMArena)
PostTrainBenchnot in index–––41.8%#1–Epoch AI Benchmarking Hub
GBAEvalnot in indexeffort not stated––––74.5%#2Epoch AI Benchmarking Hub
Vending-Bench 2not in index5018.5#334339.8#395680.3#244966.6#354529.9#37Andon Labs
AutomationBenchnot in index–––54.1%#61–Artificial Analysis
GDP.pdf (AA)not in index–––24.0%#37–Artificial Analysis
EnterpriseOps-Gymnot in index–––51.1%#1–Artificial Analysis
AA-Briefcase v1.1not in index–––1539#24–Artificial Analysis

Knowledge

Benchmarkxhighmaxnot statedSourceTrend
SimpleQA Verified70.7%#7––Epoch AI Benchmarking Hub
LiveBench 2.0 Data Analysisnot in indexeffort not stated––80.5%#7LiveBench
LiveBench Researchnot in indexeffort not stated––86.9%#3LiveBench
LiveBench 1.0 Data Analysisnot in index–80.5%#7–LiveBench
AA-Omniscience–43.3#6–Artificial Analysis
MMLU-Proeffort not stated––91.5%#3Vals AI
LegalBencheffort not stated––88.6%#1Vals AI
CorpFineffort not stated––71.8%#2Vals AI
TaxEvaleffort not stated––76.9%#5Vals AI
PRBench Financeeffort not stated––53.9%#4Scale AI SEAL
PRBench Legaleffort not stated––52.6%#5Scale AI SEAL
Excel Modeling Benchmarknot in indexeffort not stated––73.7%#5Vals AI
MedCodenot in indexeffort not stated––56.1%#4Vals AI
MedScribenot in indexeffort not stated––88.5%#12Vals AI
Public Benefits Benchnot in indexeffort not stated––70.4%#5Vals AI
EBR-benchnot in index–39.5%#10–Epoch AI Benchmarking Hub
GDP.pdfnot in index–29.8%#930.0%#8Epoch AI Benchmarking Hub
AA-Omniscience: accuracynot in index–65.3%#5–Artificial Analysis
AA-Omniscience: non-hallucinationnot in index–36.4%#180–Artificial Analysis

Instruction following

BenchmarkhighmaxSourceTrend
LiveBench Languagenot in index–90.7%#1LiveBench
LiveBench Instruction Followingnot in index–75.8%#6LiveBench
IFBench–63.5%#113Artificial Analysis
Arena Instruction Followingnot in index1508#4–Arena (LMArena)

Human preference

Benchmarkhighnot statedSourceTrend
Arena Text1504#4–Arena (LMArena)
EQ-Bench 4effort not stated–1340#2EQ-Bench
Arena Creative Writingnot in index1501#3–Arena (LMArena)
Arena Multi-turnnot in index1518#3–Arena (LMArena)
Arena Longer Queriesnot in index1522#4–Arena (LMArena)

Multimodal

Benchmarkhighnot statedSourceTrend
Arena Vision1325#1–Arena (LMArena)
LiveBench Designnot in indexeffort not stated–84.7%#3LiveBench
MMMU-Pro (Vals)not in indexeffort not stated–89.3%#3Vals AI
MortgageTaxnot in indexeffort not stated–68.9%#8Vals AI
SAGEnot in indexeffort not stated–51.9%#9Vals AI
Blueprint-Bench 2not in indexeffort not stated–38.6%#6Epoch AI Benchmarking Hub

Long context

Benchmarkmaxnot statedSourceTrend
AA-LCR82.3%#40–Artificial Analysis
Arena Documentnot in indexeffort not stated–1499#1Arena (LMArena)
MLCRnot in index64.4%#4–Artificial Analysis

Composite

Benchmarkmaxnot statedSourceTrend
Epoch Capabilities Indexnot in indexeffort not stated–163.4#9Epoch AI Benchmarking Hub
LiveBench 2.0effort not stated–83.6%#6LiveBench
LiveBench 1.0not in index83.0%#3–LiveBench
AA Intelligence Index v4.3.249.6#21–Artificial Analysis
Vals Multimodal Indexnot in indexeffort not stated–74.2%#1Vals 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.

ProviderSpeedFirst tokenInput $/MOutput $/MContextQuantisation
Google Vertex51 tok/s3.83 s$10.00$50.001M–
Anthropic49 tok/s3.62 s$10.00$50.001M–
Azure (BYOK Only)48 tok/s4.64 s$10.00$50.001M–

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 $1.00 per 1M. Reasoning tokens are not modelled.

WorkloadTokens in / outCostWith cachingTime
Chat reply400 / 300$0.019$0.0161.3 min
Summarize a 30-page report12,000 / 600$0.150$0.0691.4 min
Code edit6,000 / 1,500$0.135$0.0951.6 min
Agentic coding session60,000 / 4,000$0.800$0.3952.2 min
Structured extraction2,000 / 200$0.030$0.0171.3 min

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See also

Data as of 21 Oct 2026. Compare these configurations.

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