BenchLeader

Claude Fable 5.2 vs o3

Full profiles: Claude Fable 5.2 (Anthropic) and o3 (OpenAI): every benchmark, price and rank.

Updated · Data from 16 sources

As of 9 Nov 2026, Claude Fable 5.2 is ahead of o3 on quality (69.4 vs 61.0 on the BenchLeader Index), but o3 is 4.6× cheaper at $3.50 vs $16.00 per 1M tokens blended. Claude Fable 5.2 leads in every category we measure both in. o3 streams ~1.5× faster.

Key facts (as of 9 Nov 2026)

  • Claude Fable 5.2 scores 69.4 on the BenchLeader Index and o3 scores 61.0 (BenchLeader, 9 Nov 2026).
  • Claude Fable 5.2 costs $16.00 per 1M tokens blended (list price, 9 Nov 2026).
  • o3 costs $3.50 per 1M tokens blended (list price, 9 Nov 2026).
  • o3 streams ~1.5× faster than Claude Fable 5.2 (Artificial Analysis, 7-day median, 9 Nov 2026).
  • Of the 3 benchmarks both models have, Claude Fable 5.2 leads 3 (BenchLeader, 9 Nov 2026).

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 casePickWhyConfidence
CodingClaude Fable 5.280 vs 62 category scoreHigh
ReasoningClaude Fable 5.278 vs 61 category score; Humanity's Last Exam (AA) 74.3% vs 20.1%High
KnowledgeClaude Fable 5.282 vs 57 category scoreHigh
Long documentsClaude Fable 5.266 vs 62 category score; AA-LCR v1.1 83.3% vs 74.7%Medium
Chat quality (human preference)–Only o3 has an Arena rating (61 category score)Not comparable
Lowest costo3$3.50 vs $16.00 per 1M blended; agentic coding session $0.152 vs $0.640–
Fastest first answerClaude Fable 5.23.0 s (Claude Fable 5.2 (max)) vs 5.3 s (o3) to the first answer token–
High volume on a budgetNeither flagshipA smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs–

Key differences

  • Claude Fable 5.2 (max) leads on quality: 69.4 vs 61.0.
  • Claude Fable 5.2 (max) is stronger in coding, knowledge, long context, reasoning.
  • o3 is stronger in agents & tools, human preference, instruction following, maths, multimodal.
  • o3 is 4.6× cheaper ($3.50 vs $16.00 per 1M blended).
  • o3 streams 1.6× faster (112 vs 72 tokens per second).

At a glance

SpecClaude Fable 5.2o3
DeveloperAnthropicOpenAI
Released9 Nov 202616 Apr 2025
Context window (tokens)1,000,000200,000
Compared atClaude Fable 5.2 (max)o3
Open weightsNoNo
Price in / out / cached input per 1M$8.00 / $40.00 / $0.200$2.00 / $8.00 / $0.500

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.

CategoryClaude Fable 5.2 (max)o3Leader
Reasoning78.460.9Claude Fable 5.2
Coding80.261.5Claude Fable 5.2
Agents & tools–70.3not comparable
Maths–70.6not comparable
Knowledge81.756.5Claude Fable 5.2
Instruction following–65.2not comparable
Human preference–61.1not comparable
Multimodal–56.6not comparable
Long context66.461.9Claude Fable 5.2

On one chart

Each domain on the index's own scale, where 50 is an average model. Click a domain to see the benchmarks behind it. Pick up to 5 models from the list.

2550 avg75ReasoningCodingKnowledgeLong contextClaude Fable 5.2, Reasoning: 78.4Claude Fable 5.2, Coding: 80.2Claude Fable 5.2, Knowledge: 81.7Claude Fable 5.2, Long context: 66.4o3, Reasoning: 60.9o3, Coding: 61.5o3, Knowledge: 56.5o3, Long context: 61.9

Not drawn, measured for fewer than two of these models: Agents & tools, Maths, Instruction following, Multimodal, Human preference.

ModelIndex

Where sources disagree

Across the 3 benchmarks both have, Claude Fable 5.2 leads 3, o3 leads 0. Every overall index that rates both puts Claude Fable 5.2 ahead.

Overall indexClaude Fable 5.2 (max)o3Leader
BenchLeader Index69.461.0Claude Fable 5.2

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. Cost, tokens and time per benchmark task are measured: Artificial Analysis’ averages over its whole Intelligence Index run.

MeasureClaude Fable 5.2 (max)o3
Blended price per 1M tokens$16.00$3.50
Input / output per 1M$8.00 / $40.00$2.00 / $8.00
Cached input per 1M$0.200$0.500
Price per task: chat reply$0.015$0.0032
Price per task: summarize a 30-page report$0.120$0.029
Price per task: code edit$0.108$0.024
Price per task: agentic coding session$0.640$0.152
Price per task: structured extraction$0.024$0.0056
Agentic coding session, input mostly cached$0.289$0.085
Cost per benchmark task (AA Index)$26.54–
Output tokens per task (AA Index)274k–
Of which reasoning193k–
Output speed72 tok/s112 tok/s
Time to first answer3.0 s5.3 s
Time to a complete answer–16.7 s

Each model is compared at its best-ranked reasoning-effort setting. Claude Fable 5.2 (max) scores 69.4 and takes 3 s to its first answer token; Claude Fable 5.2 (high) scores 68.9 in 3 s, Claude Fable 5.2 (xhigh) scores 68.7 in 3 s. o3 scores 61.0 and takes 5 s to its first answer token; o3 (high) scores 53.9 in 5 s, o3 (medium) scores 53.3 in 5 s. 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

136 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.

MetricPublisherClaude Fable 5.2 (max)o3
BenchLeader IndexBenchLeader69.461.0
Coding scoreBenchLeader80.261.5
Knowledge scoreBenchLeader81.756.5
Long context scoreBenchLeader66.461.9
Reasoning scoreBenchLeader78.460.9
Agents & tools scoreBenchLeader–70.3
Human preference scoreBenchLeader–61.1
Instruction following scoreBenchLeader–65.2
Maths scoreBenchLeader–70.6
Multimodal scoreBenchLeader–56.6
Blended price $/MBenchLeader$16.00$3.50
Output speedBenchLeader72 tok/s112 tok/s
Time to first answerBenchLeader3.0 s5.3 s
Context windowBenchLeader1,000,000 tokens200,000 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub–81.8%†
Humanity's Last ExamScale AI / CAIS–20.3%†
SimpleBenchSimpleBench–53.1%†
Arena Hard PromptsArena (LMArena)–1441
LiveBench 2.0 ReasoningLiveBench88.8%†–
GPQA Diamond (AA)Artificial Analysis–82.7%
Humanity's Last Exam (AA)Artificial Analysis74.3%20.1%
HLE-Diamond (AA)Artificial Analysis80.2%–
GPQA Diamond (Vals)Vals AI–84.1%†
Kagi LLM BenchmarkKagi LLM Benchmark–67.6%
GPQA Diamond (HELM)HELM Capabilities–75.3%
ARC-AGI-1ARC Prize97.5%60.8%†
ARC-AGI-2ARC Prize92.5%6.5%†
ARC-AGI-3ARC Prize94.9%–
CritPtArtificial Analysis35.4%1.1%
CritPt v2 hard subset (AA)Artificial Analysis76.5%–
MysteryMechanismVals AI51.8%†–
SciPredictScale AI SEAL–17.9%
Chess PuzzlesEpoch AI Benchmarking Hub–36.0%†
Mystery Game PuzzlesEpoch AI Benchmarking Hub–29.0%†
CL-benchEpoch AI Benchmarking Hub–17.8%†
LMCAEpoch AI Benchmarking Hub–39.7%†
DTBenchEpoch AI Benchmarking Hub–84.8%†
ForecastBenchForecastBench–64.6%
Coding
SWE-bench Verified (Epoch)Epoch AI Benchmarking Hub–62.3%†
Show all 136 benchmarks
MetricPublisherClaude Fable 5.2 (max)o3
Coding
WeirdMLWeirdML–52.4%†
GSO-BenchGSO-Bench–8.8%†
Arena CodingArena (LMArena)–1460
LiveBench 2.0 CodingLiveBench79.2%†–
SciCode (AA)Artificial Analysis67.7%–
LiveCodeBenchVals AI–83.9%†
Aider PolyglotAider polyglot leaderboard–81.3%
SWE-bench Verified (bash only)SWE-bench–58.4%
SWE-bench Verified (any scaffold)SWE-bench–58.4%
Code Migration v1.1Vals AI83.3%†–
ProgramBenchVals AI19.0%†–
SWE-bench MultimodalVals AI62.3%†–
Vibe Code Bench v1.1Vals AI93.8%†–
CadEvalEpoch AI Benchmarking Hub–74.0%†
ALE-BenchEpoch AI Benchmarking Hub–933.5†
Terminal-Bench 4.0 (AA)Artificial Analysis59.6%–
GameBench 2 OverallDuelLab GameBench 2–34.6
GameBench 2 by reasoning settingDuelLab GameBench 2–30.5†
Design Arena WebsiteDesign Arena–1033
FrontierCode 1.1 (AA)Artificial Analysis56.2%–
FrontierCode 2.0 (AA)Artificial Analysis48.8%–
LiveCodeBench (AA)Artificial Analysis–80.8%
Agents & tools
GDPvalOpenAI–30.8%†
LiveBench Long AgenticLiveBench82.9%†–
LiveBench BrowserLiveBench86.9%†–
Terminal-Bench HardArtificial Analysis–37.1%
τ²-Bench Telecom (AA)Artificial Analysis–80.7%
BFCL OverallBerkeley Function Calling Leaderboard–63.0%
GDPval-AA v2.1Artificial Analysis1831–
Finance Agent v2.1Vals AI69.5%†–
Harvey's Legal Agent Benchmark v1.1Vals AI5.0%†–
Legal Research BenchVals AI46.1%†–
Tax Agent BenchVals AI32.1%†–
Terminal-Bench 4.0 (Vals)Vals AI65.2%†–
Terminal-Bench ScienceVals AI55.7%†–
Arena SearchArena (LMArena)–1197
DeepResearch BenchDeepResearch Bench–45.2%†
METR Time HorizonsMETR–63.6%
AutomationBenchArtificial Analysis76.4%–
GDP.pdf (AA)Artificial Analysis24.2%–
Harvey LAB-AA v1.1Harvey7.2%–
AA-Briefcase v1.1Artificial Analysis1785–
Terminal-Bench-Science 0.1 (AA)Artificial Analysis73.3%–
BrowseComp-PlusBrowseComp-Plus–50.5%
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub–33.3%†
OTIS Mock AIMEEpoch AI Benchmarking Hub–83.9%†
MATH Level 5Epoch AI Benchmarking Hub–97.8%†
AIME (Vals)Vals AI–85.3%†
MGSMVals AI–91.8%†
IMO 2025MathArena–16.7%†
Omni-MATH (HELM)HELM Capabilities–71.4%
MATH 500Vals AI–94.6%†
Arena MathsArena (LMArena)–1448
AIME 2025 (AA)Artificial Analysis–88.3%
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub–49.4%†
LiveBench 2.0 Data AnalysisLiveBench81.5%†–
LiveBench ResearchLiveBench94.5%†–
AA-Omniscience v1.1Artificial Analysis66.8–
MMLU-ProVals AI–85.6%†
LegalBenchVals AI–83.8%†
CorpFinVals AI–59.7%†
TaxEvalVals AI–74.6%†
MedQAVals AI–96.1%†
PRBench FinanceScale AI SEAL–47.7%
PRBench LegalScale AI SEAL–48.6%
MultiNRCScale AI SEAL–45.5%†
MMLU-Pro (HELM)HELM Capabilities–85.9%
BioMysteryBenchVals AI83.7%†–
Excel Modeling Benchmark v1.1Vals AI77.4%†–
MedCodeVals AI–47.3%†
MedScribeVals AI–76.7%†
AA-Omniscience v1.1: accuracyArtificial Analysis79.1%–
AA-Omniscience v1.1: non-hallucinationArtificial Analysis40.7%–
HealthBench Professional (AA)OpenAI67.7%–
Instruction following
IFBenchArtificial Analysis–71.4%
MultiChallengeScale AI SEAL–56.6%†
TutorBenchScale AI SEAL–52.1%†
IFEval (HELM)HELM Capabilities–86.9%
WildBench (HELM)HELM Capabilities–86.1%
Arena Instruction FollowingArena (LMArena)–1403
Human preference
Arena TextArena (LMArena)–1432
Arena Creative WritingArena (LMArena)–1383
Arena Multi-turnArena (LMArena)–1420
Arena Longer QueriesArena (LMArena)–1411
Lech Mazur Creative WritingLech Mazur–83.9%†
Multimodal
Arena VisionArena (LMArena)–1214
LiveBench DesignLiveBench85.1%†–
MMMU-ProArtificial Analysis–70.1%
VISTAScale AI SEAL–50.1%†
MMMU (validation)MMMU–82.9%
MMMU-Pro (official)MMMU–76.4%
MMMU-Pro (Vals)Vals AI–80.4%†
MortgageTaxVals AI–65.7%†
VTBScale AI SEAL–13.7%
GeoBenchGeoBench–60.0%†
VPCTEpoch AI Benchmarking Hub–52.0%†
AA-3DArtificial Analysis1271–
Long context
Fiction.LiveBench 120kFiction.live–100.0%†
AA-LCR v1.1Artificial Analysis83.3%74.7%
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub–147.0
LiveBench 2.0LiveBench84.9%†–
AA Intelligence Index v5.0Artificial Analysis64.6–
AA Intelligence Index v4.3.2Artificial Analysis–20.2
AA Progress Index v1Artificial Analysis–258.3
Vals IndexVals AI71.3†–
HELM Capabilities meanHELM Capabilities–81.1%
Vals Finance IndexVals AI63.6%†–
Vals Science IndexVals AI63.7%†–
Safety & honesty
FORTRESSScale AI SEAL–16.0%
MASKScale AI SEAL–84.5%†
PropensityBenchScale AI SEAL–10.5%

Data as of 2026-11-09. Best configuration of each model; every score links to its source on the model pages.

DuelLab GameBench 2, release gb2-20261103-eaea31df94e6 (https://benchmarks.duellab.org/releases/gb2-20261103-eaea31df94e6/), CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Scores mapped to BenchLeader model names; not endorsed by DuelLab.

What changed

  • o3: 1 new result (Arena Search).
  • o3: 1 score revision.
  • o3: 1 new result (AA Progress Index v1).
  • o3: 1 score revision.
  • o3: 1 new result (PRBench Legal).
  • o3: 1 new result (VTB).
  • o3: 1 new result (PRBench Legal).
  • o3: 1 new result (PRBench Finance).

Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs

Claude Fable 5.2 vs o3: questions

Is Claude Fable 5.2 better than o3?
Claude Fable 5.2 (max) leads on quality: 69.4 vs 61.0. The BenchLeader Index combines every independent quality benchmark; Claude Fable 5.2 (max) is ahead overall as of 9 Nov 2026, but check the category scores for your use.
Claude Fable 5.2 vs o3: which is cheaper, and will that change?
o3 is cheaper today: $3.50 against $16.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
Is Claude Fable 5.2 or o3 better for coding?
Claude Fable 5.2 scores higher in coding (80 vs 62 on the category index, where 50 is average).
Which is faster, Claude Fable 5.2 or o3?
o3 streams ~1.5× faster (112 vs 72 output tokens per second, Artificial Analysis 7-day median).
Which is better for long documents?
Claude Fable 5.2 scores higher on long-context benchmarks (66 vs 62). Claude Fable 5.2 accepts more context: 1,000,000 against 200,000 tokens for o3.
More questions (3)
Which has lower latency?
Claude Fable 5.2 answers first: 3.0 s against 5.3 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.
Do independent benchmarks agree on Claude Fable 5.2 vs o3?
Across the 3 benchmarks both have, Claude Fable 5.2 leads 3, o3 leads 0. Every overall index that rates both puts Claude Fable 5.2 ahead.
When was Claude Fable 5.2 released?
Claude Fable 5.2 was released on 9 Nov 2026.