BenchLeader

Claude Fable 5.2 vs Gemini 3.1 Pro

Full profiles: Claude Fable 5.2 (Anthropic) and Gemini 3.1 Pro (Google): every benchmark, price and rank.

Updated · Data from 11 sources

As of 9 Nov 2026, Claude Fable 5.2 is ahead of Gemini 3.1 Pro on quality (69.4 vs 60.6 on the BenchLeader Index), but Gemini 3.1 Pro is 3.6× cheaper at $4.50 vs $16.00 per 1M tokens blended. Claude Fable 5.2 leads in every category we measure both in. Gemini 3.1 Pro streams ~1.5× faster.

Key facts (as of 9 Nov 2026)

  • Claude Fable 5.2 scores 69.4 on the BenchLeader Index and Gemini 3.1 Pro scores 60.6 (BenchLeader, 9 Nov 2026).
  • Claude Fable 5.2 costs $16.00 per 1M tokens blended (list price, 9 Nov 2026).
  • Gemini 3.1 Pro costs $4.50 per 1M tokens blended (list price, 9 Nov 2026).
  • Gemini 3.1 Pro streams ~1.5× faster than Claude Fable 5.2 (Artificial Analysis, 7-day median, 9 Nov 2026).
  • Of the 14 benchmarks both models have, Claude Fable 5.2 leads 13 (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 57 category score; SciCode (AA) 67.7% vs 58.7%High
ReasoningClaude Fable 5.278 vs 66 category score; HLE-Diamond (AA) 80.2% vs 31.4%High
KnowledgeClaude Fable 5.282 vs 56 category scoreHigh
Long documentsEither66 vs 66 category score; AA-LCR v1.1 83.3% vs 82.0%Either
Chat quality (human preference)–Only Gemini 3.1 Pro has an Arena rating (58 category score)Not comparable
Lowest costGemini 3.1 Pro$4.50 vs $16.00 per 1M blended; agentic coding session $0.168 vs $0.640–
Fastest first answerClaude Fable 5.23.0 s (Claude Fable 5.2 (max)) vs 16.0 s (Gemini 3.1 Pro) 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 60.6.
  • Claude Fable 5.2 (max) is stronger in coding, knowledge, long context, reasoning.
  • Gemini 3.1 Pro is stronger in agents & tools, human preference, instruction following, maths, multimodal.
  • Gemini 3.1 Pro is 3.6× cheaper ($4.50 vs $16.00 per 1M blended).
  • Gemini 3.1 Pro streams 1.5× faster (110 vs 72 tokens per second).

At a glance

SpecClaude Fable 5.2Gemini 3.1 Pro
DeveloperAnthropicGoogle
Released9 Nov 202619 Feb 2026
Context window (tokens)1,000,0001,048,576
Compared atClaude Fable 5.2 (max)Gemini 3.1 Pro
Open weightsNoNo
Price in / out / cached input per 1M$8.00 / $40.00 / $0.200$2.00 / $12.00 / $0.200

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)Gemini 3.1 ProLeader
Reasoning78.465.9Claude Fable 5.2
Coding80.256.7Claude Fable 5.2
Agents & tools–57.2not comparable
Maths–60.8not comparable
Knowledge81.756.2Claude Fable 5.2
Instruction following–67.1not comparable
Human preference–58.4not comparable
Multimodal–64.5not comparable
Long context66.465.7level

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: 66.4Gemini 3.1 Pro, Reasoning: 65.9Gemini 3.1 Pro, Coding: 56.7Gemini 3.1 Pro, Knowledge: 56.2Gemini 3.1 Pro, Long context: 65.7

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

ModelIndex

Where sources disagree

Across the 14 benchmarks both have, Claude Fable 5.2 leads 13, Gemini 3.1 Pro leads 1. Every overall index that rates both puts Claude Fable 5.2 ahead.

Overall indexClaude Fable 5.2 (max)Gemini 3.1 ProLeader
BenchLeader Index69.460.6Claude 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)Gemini 3.1 Pro
Blended price per 1M tokens$16.00$4.50
Input / output per 1M$8.00 / $40.00$2.00 / $12.00
Cached input per 1M$0.200$0.200
Price per task: chat reply$0.015$0.0044
Price per task: summarize a 30-page report$0.120$0.031
Price per task: code edit$0.108$0.030
Price per task: agentic coding session$0.640$0.168
Price per task: structured extraction$0.024$0.0064
Agentic coding session, input mostly cached$0.289$0.087
Cost per benchmark task (AA Index)$26.54–
Output tokens per task (AA Index)274k–
Of which reasoning193k–
Output speed72 tok/s110 tok/s
Time to first answer3.0 s16.0 s
Time to a complete answer–35.5 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. Gemini 3.1 Pro scores 60.6 and takes 16 s to its first answer token; Gemini 3.1 Pro (high) scores 60.2 in 16 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

175 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)Gemini 3.1 Pro
BenchLeader IndexBenchLeader69.460.6
Coding scoreBenchLeader80.256.7
Knowledge scoreBenchLeader81.756.2
Long context scoreBenchLeader66.465.7
Reasoning scoreBenchLeader78.465.9
Agents & tools scoreBenchLeader–57.2
Human preference scoreBenchLeader–58.4
Instruction following scoreBenchLeader–67.1
Maths scoreBenchLeader–60.8
Multimodal scoreBenchLeader–64.5
Blended price $/MBenchLeader$16.00$4.50
Output speedBenchLeader72 tok/s110 tok/s
Time to first answerBenchLeader3.0 s16.0 s
Context windowBenchLeader1,000,000 tokens1,048,576 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub–94.1%
Humanity's Last ExamScale AI / CAIS–46.4%
SimpleBenchSimpleBench–79.6%
Arena Hard PromptsArena (LMArena)–1508
LiveBench 2.0 ReasoningLiveBench88.8%†–
LiveBench 1.0 ReasoningLiveBench–84.0%†
GPQA Diamond (AA)Artificial Analysis–94.1%
Humanity's Last Exam (AA)Artificial Analysis74.3%47.0%
HLE-Diamond (AA)Artificial Analysis80.2%31.4%
GPQA Diamond (Vals)Vals AI–95.5%†
EnigmaEvalScale AI SEAL–36.8%†
ARC-AGI-1ARC Prize97.5%98.0%
ARC-AGI-2ARC Prize92.5%77.1%
ARC-AGI-3ARC Prize94.9%0.4%
CritPtArtificial Analysis35.4%17.7%
CritPt v2 hard subset (AA)Artificial Analysis76.5%–
MysteryMechanismVals AI51.8%†20.7%†
Chess PuzzlesEpoch AI Benchmarking Hub–51.0%†
Mystery Game PuzzlesEpoch AI Benchmarking Hub–34.0%†
CL-benchEpoch AI Benchmarking Hub–20.8%
CL-bench LifeEpoch AI Benchmarking Hub–16.9%
LMCAEpoch AI Benchmarking Hub–53.8%†
DTBenchEpoch AI Benchmarking Hub–95.5%†
ForecastBenchForecastBench–64.3%
Coding
SciCodeSciCode–58.7%
Show all 175 benchmarks
MetricPublisherClaude Fable 5.2 (max)Gemini 3.1 Pro
Coding
WeirdMLWeirdML–72.1%
GSO-BenchGSO-Bench–22.6%
Arena CodingArena (LMArena)–1520
Arena WebDevArena (LMArena)–1446
LiveBench 2.0 CodingLiveBench79.2%†–
LiveBench 1.0 CodingLiveBench–76.5%†
SciCode (AA)Artificial Analysis67.7%58.7%
LiveCodeBenchVals AI–88.5%†
IOIVals AI–51.8%†
SWE-bench (Vals)Vals AI–78.8%†
SWE-Bench ProScale AI SEAL–46.1%†
Code MigrationVals AI–17.3%†
Code Migration v1.1Vals AI83.3%†–
ProgramBenchVals AI19.0%†0.0%†
SWE-bench MultimodalVals AI62.3%†–
Vibe Code Bench 1-100Vals AI–6.7%†
Vibe Code Bench v1.1Vals AI93.8%†32.0%†
SWE-Bench Pro (private)Scale AI SEAL–46.1%†
SWE Atlas: Codebase QnAScale AI SEAL–13.5%
SWE Atlas: RefactoringScale AI SEAL–33.8%
SWE Atlas: Test WritingScale AI SEAL–29.8%
MirrorCodeEpoch AI Benchmarking Hub–8.9%†
DeepSWE v1.1Epoch AI Benchmarking Hub–11.7%
ALE-BenchEpoch AI Benchmarking Hub–1160.6
AlgoTuneAlgoTune–2.0
Terminal-Bench 4.0 (AA)Artificial Analysis59.6%4.0%
Terminal-Bench 2.1 (AA)Artificial Analysis–73.8%
Design Arena WebsiteDesign Arena–1230
FrontierCode 1.1 (AA)Artificial Analysis56.2%–
FrontierCode 2.0 (AA)Artificial Analysis48.8%–
Agents & tools
Terminal-BenchTerminal-Bench–80.2%
APEX-AgentsMercor–35.1%
Arena AgentArena (LMArena)–-4.3
LiveBench Long AgenticLiveBench82.9%†–
LiveBench BrowserLiveBench86.9%†–
LiveBench Agentic CodingLiveBench–44.1%†
Terminal-Bench HardArtificial Analysis–53.8%
τ²-Bench Telecom (AA)Artificial Analysis–95.6%
Terminal-Bench 2.1 (Vals)Vals AI–70.8%†
MCP AtlasScale AI SEAL–78.2%†
HiL-BenchScale AI SEAL–35.3%
τ³-bench Bankingτ²-bench–26.0%†
GDPval-AA v2.1, normalised scoreArtificial Analysis–14.6%
GDPval-AA v2.1Artificial Analysis1831799
τ³-Banking (AA)Artificial Analysis–21.4%
ITBench SRE (AA)Artificial Analysis–30.3%
Analyst Agent (AA)Artificial Analysis–41.3%
APEX-Agents (AA)Artificial Analysis–32.0%
Finance Agent v2Vals AI–43.0%†
Finance Agent v2.1Vals AI69.5%†–
Harvey's Legal Agent Benchmark v1.1Vals AI5.0%†–
Harvey's Legal Agent Benchmark v1Vals AI–0.0%†
Legal Research BenchVals AI46.1%†20.7%†
SREBenchVals AI–0.0%†
Tax Agent BenchVals AI32.1%†9.3%†
Terminal-Bench 2.0 (Vals)Vals AI–67.4%†
Terminal-Bench 4.0 (Vals)Vals AI65.2%†2.5%†
Terminal-Bench ScienceVals AI55.7%†1.4%†
Arena SearchArena (LMArena)–1209
BALROGBALROG–57.0%
DeepResearch BenchDeepResearch Bench–47.8%†
PostTrainBenchEpoch AI Benchmarking Hub–22.0%
ExploitBenchEpoch AI Benchmarking Hub–26.1%
METR Time HorizonsMETR–77.0%
GBAEvalEpoch AI Benchmarking Hub–0.8%
Vending-Bench 2Andon Labs–911.2
AutomationBenchArtificial Analysis76.4%35.4%
GDP.pdf (AA)Artificial Analysis24.2%17.8%
Harvey LAB-AA v1.1Harvey7.2%0.0%
EnterpriseOps-GymArtificial Analysis–42.2%
AA-Briefcase v1.1Artificial Analysis1785457
Design Arena AgenticDesign Arena–1083
Terminal-Bench-Science 0.1 (AA)Artificial Analysis73.3%–
BrowseCompOpenAI–31.2%
DeepSearchQAGoogle–60.2%
FACTS SearchGoogle–90.2%
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub–59.6%
FrontierMath Tier 4Epoch AI Benchmarking Hub–26.8%
OTIS Mock AIMEEpoch AI Benchmarking Hub–95.6%
ProofBenchVals AI–26.0%
LiveBench MathematicsLiveBench–91.0%†
AIME (Vals)Vals AI–98.1%†
AIME 2026MathArena–98.3%
HMMT February 2026MathArena–94.7%
USAMO 2026MathArena–74.4%
MathArena ApexMathArena–60.9%
Arena MathsArena (LMArena)–1488
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub–73.5%†
LiveBench 2.0 Data AnalysisLiveBench81.5%†–
LiveBench ResearchLiveBench94.5%†–
LiveBench 1.0 Data AnalysisLiveBench–78.5%†
AA-Omniscience v1.1Artificial Analysis66.8–
MMLU-ProVals AI–91.0%†
LegalBenchVals AI–87.4%†
CorpFinVals AI–64.5%†
TaxEvalVals AI–72.9%†
MedQAVals AI–96.4%†
PRBench FinanceScale AI SEAL–41.9%
PRBench LegalScale AI SEAL–44.0%
MultiNRCScale AI SEAL–64.7%
BioMysteryBenchVals AI83.7%†60.0%†
CaseLaw v2Vals AI–64.8%†
Excel Modeling BenchmarkVals AI–52.6%†
Excel Modeling Benchmark v1.1Vals AI77.4%†–
MedCodeVals AI–59.1%†
MedScribeVals AI–76.1%†
Public Benefits Bench v1.1Vals AI–53.8%†
DrugDiscoveryBenchScale AI SEAL–41.9%†
EBR-benchEpoch AI Benchmarking Hub–14.3%
GDP.pdfEpoch AI Benchmarking Hub–17.0%
AA-Omniscience v1.1: accuracyArtificial Analysis79.1%–
AA-Omniscience v1.1: non-hallucinationArtificial Analysis40.7%–
Global-MMLU-Lite (AA)Artificial Analysis–93.2%
HealthBench Professional (AA)OpenAI67.7%–
Instruction following
LiveBench LanguageLiveBench–85.4%†
LiveBench Instruction FollowingLiveBench–79.1%†
IFBenchArtificial Analysis–77.1%
MultiChallengeScale AI SEAL–71.4%
TutorBenchScale AI SEAL–53.0%
Arena Instruction FollowingArena (LMArena)–1480
Human preference
Arena TextArena (LMArena)–1487
EQ-Bench 4EQ-Bench–1132
Arena Creative WritingArena (LMArena)–1482
Arena Multi-turnArena (LMArena)–1495
Arena Longer QueriesArena (LMArena)–1499
Multimodal
Arena VisionArena (LMArena)–1296
LiveBench DesignLiveBench85.1%†–
MMMU-ProArtificial Analysis–82.4%
MMMU-Pro (official)MMMU–80.5%†
MMMU-Pro (Vals)Vals AI–88.2%†
MortgageTaxVals AI–69.4%†
SAGEVals AI–83.2%†
VTBScale AI SEAL–29.0%
Blueprint-Bench 2Epoch AI Benchmarking Hub–26.5%
AA-3DArtificial Analysis1271–
Long context
AA-LCR v1.1Artificial Analysis83.3%82.0%
Arena DocumentArena (LMArena)–1459
MLCRArtificial Analysis–11.1%
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub–156.2
LiveBench 2.0LiveBench84.9%†–
LiveBench 1.0LiveBench–77.0%†
AA Intelligence Index v5.0Artificial Analysis64.6–
AA Intelligence Index v4.3.2Artificial Analysis–29.7
AA Progress Index v1Artificial Analysis–296.1
Vals IndexVals AI71.3†–
Vals Finance IndexVals AI63.6%†–
Vals Science IndexVals AI63.7%†27.4%†
Vals Multimodal IndexVals AI–56.1%†
Safety & honesty
FORTRESSScale AI SEAL–29.8%
MASKScale AI SEAL–42.4%

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

What changed

  • Gemini 3.1 Pro: 1 new result (Arena Search).
  • Gemini 3.1 Pro: 1 score revision.
  • Gemini 3.1 Pro: 2 score revisions.
  • Gemini 3.1 Pro: BenchLeader Index 61.6 → 60.5.
  • Gemini 3.1 Pro: 2 new results (AA Progress Index v1, HLE-Diamond (AA)).
  • Gemini 3.1 Pro: BenchLeader Index 59.3 → 61.6.
  • Gemini 3.1 Pro: Gemini 3.1 Pro cost per task moved from $1.30/M to $1.44/M (11% up).
  • Gemini 3.1 Pro: 2 score revisions.
  • Gemini 3.1 Pro: 2 score revisions.
  • Gemini 3.1 Pro: 1 score revision.

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

Claude Fable 5.2 vs Gemini 3.1 Pro: questions

Is Claude Fable 5.2 better than Gemini 3.1 Pro?
Claude Fable 5.2 (max) leads on quality: 69.4 vs 60.6. 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 Gemini 3.1 Pro: which is cheaper, and will that change?
Gemini 3.1 Pro is cheaper today: $4.50 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 Gemini 3.1 Pro better for coding?
Claude Fable 5.2 scores higher in coding (80 vs 57 on the category index, where 50 is average).
Which is faster, Claude Fable 5.2 or Gemini 3.1 Pro?
Gemini 3.1 Pro streams ~1.5× faster (110 vs 72 output tokens per second, Artificial Analysis 7-day median).
Which is better for long documents?
They are level on long-context benchmarks (66 vs 66). Both take about 1M tokens: Claude Fable 5.2 1,000,000, Gemini 3.1 Pro 1,048,576.
More questions (3)
Which has lower latency?
Claude Fable 5.2 answers first: 3.0 s against 16.0 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 Gemini 3.1 Pro?
Across the 14 benchmarks both have, Claude Fable 5.2 leads 13, Gemini 3.1 Pro leads 1. 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.