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Claude Fable 5.2 vs Kimi K3.1 Pro

Full profiles: Claude Fable 5.2 (Anthropic) and Kimi K3.1 Pro (Moonshot AI): every benchmark, price and rank.

Updated · Data from 9 sources

As of 9 Nov 2026, Claude Fable 5.2 is ahead of Kimi K3.1 Pro on quality (69.4 vs 61.2 on the BenchLeader Index), but Kimi K3.1 Pro is 4.0× cheaper at $4.00 vs $16.00 per 1M tokens blended. Choose Claude Fable 5.2 for coding (80 vs 60), knowledge (82 vs 61), and reasoning (78 vs 60) and fast first answers (3.0 s vs 167.4 s), where it also streams ~2× faster; choose Kimi K3.1 Pro for long context (68 vs 66).

Key facts (as of 9 Nov 2026)

  • Claude Fable 5.2 scores 69.4 on the BenchLeader Index and Kimi K3.1 Pro scores 61.2 (BenchLeader, 9 Nov 2026).
  • Claude Fable 5.2 costs $16.00 per 1M tokens blended (list price, 9 Nov 2026).
  • Kimi K3.1 Pro costs $4.00 per 1M tokens blended (list price, 9 Nov 2026).
  • Claude Fable 5.2 streams ~2× faster than Kimi K3.1 Pro (Artificial Analysis, 7-day median, 9 Nov 2026).
  • Of the 18 benchmarks both models have, Claude Fable 5.2 leads 13 (BenchLeader, 9 Nov 2026).
Claude Fable 5.2 benchmarks max Anthropic Kimi K3.1 Pro benchmarks Moonshot AIAdd a third model

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 60 category score; FrontierCode 2.0 (AA) 48.8% vs 25.4%High
ReasoningClaude Fable 5.278 vs 60 category score; HLE-Diamond (AA) 80.2% vs 37.3%High
KnowledgeClaude Fable 5.282 vs 61 category score; AA-Omniscience v1.1 66.8 vs 29.9High
Long documentsKimi K3.1 Pro68 vs 66 category score; AA-LCR v1.1 86.3% vs 83.3%Medium
Lowest costKimi K3.1 Pro$4.00 vs $16.00 per 1M blended; agentic coding session $0.160 vs $0.640–
Fastest first answerClaude Fable 5.23.0 s (Claude Fable 5.2 (max)) vs 167.4 s (Kimi K3.1 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 61.2.
  • Claude Fable 5.2 (max) is stronger in coding, knowledge, reasoning.
  • Kimi K3.1 Pro is stronger in long context, agents & tools, composite, maths, multimodal.
  • Kimi K3.1 Pro is 4.0× cheaper ($4.00 vs $16.00 per 1M blended).
  • Claude Fable 5.2 (max) streams 2.3× faster (72 vs 32 tokens per second).

At a glance

SpecClaude Fable 5.2Kimi K3.1 Pro
DeveloperAnthropicMoonshot AI
Released9 Nov 202623 Oct 2026
Context window (tokens)1,000,0001,048,576
Compared atClaude Fable 5.2 (max)Kimi K3.1 Pro
Open weightsNoYes
Price in / out / cached input per 1M$8.00 / $40.00 / $0.200$2.00 / $10.00 / $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)Kimi K3.1 ProLeader
Reasoning78.459.6Claude Fable 5.2
Coding80.259.7Claude Fable 5.2
Agents & tools–67.9not comparable
Maths–74.1not comparable
Knowledge81.761.3Claude Fable 5.2
Multimodal–66.4not comparable
Long context66.468.0Kimi K3.1 Pro
Composite–54.8not comparable

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: 66.4Kimi K3.1 Pro, Reasoning: 59.6Kimi K3.1 Pro, Coding: 59.7Kimi K3.1 Pro, Knowledge: 61.3Kimi K3.1 Pro, Long context: 68.0

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

ModelIndex

Where sources disagree

Across the 18 benchmarks both have, Claude Fable 5.2 leads 13, Kimi K3.1 Pro leads 5. Every overall index that rates both puts Claude Fable 5.2 ahead.

Overall indexClaude Fable 5.2 (max)Kimi K3.1 ProLeader
BenchLeader Index69.461.2Claude Fable 5.2
AA Intelligence Index v5.064.646.5Claude Fable 5.2
Vals Index71.3†62.5Claude 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)Kimi K3.1 Pro
Blended price per 1M tokens$16.00$4.00
Input / output per 1M$8.00 / $40.00$2.00 / $10.00
Cached input per 1M$0.200$0.200
Price per task: chat reply$0.015$0.0038
Price per task: summarize a 30-page report$0.120$0.030
Price per task: code edit$0.108$0.027
Price per task: agentic coding session$0.640$0.160
Price per task: structured extraction$0.024$0.0060
Agentic coding session, input mostly cached$0.289$0.079
Cost per benchmark task (AA Index)$26.54$3.68
Output tokens per task (AA Index)274k72k
Of which reasoning193k44k
Time per task (AA Index)–38 min
Output speed72 tok/s32 tok/s
Time to first answer3.0 s167.4 s
Time to a complete answer–399.9 s

Per token is not per task: an average task of Artificial Analysis' Intelligence Index cost $26.54 on Claude Fable 5.2 (max) and $3.68 on Kimi K3.1 Pro, and Claude Fable 5.2 (max) wrote 3.8× as many output tokens for the same work, which a per-token price hides.

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. Kimi K3.1 Pro scores 61.2 and takes 167 s to its first answer token. 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

71 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)Kimi K3.1 Pro
BenchLeader IndexBenchLeader69.461.2
Coding scoreBenchLeader80.259.7
Knowledge scoreBenchLeader81.761.3
Long context scoreBenchLeader66.468.0
Reasoning scoreBenchLeader78.459.6
Agents & tools scoreBenchLeader–67.9
Composite scoreBenchLeader–54.8
Maths scoreBenchLeader–74.1
Multimodal scoreBenchLeader–66.4
Blended price $/MBenchLeader$16.00$4.00
Output speedBenchLeader72 tok/s32 tok/s
Time to first answerBenchLeader3.0 s167.4 s
Context windowBenchLeader1,000,000 tokens1,048,576 tokens
Reasoning
LiveBench 2.0 ReasoningLiveBench88.8%†91.1%
Humanity's Last Exam (AA)Artificial Analysis74.3%52.5%
HLE-Diamond (AA)Artificial Analysis80.2%37.3%
ARC-AGI-1ARC Prize97.5%–
ARC-AGI-2ARC Prize92.5%–
ARC-AGI-3ARC Prize94.9%–
CritPtArtificial Analysis35.4%24.6%
CritPt v2 hard subset (AA)Artificial Analysis76.5%49.5%
MysteryMechanismVals AI51.8%†26.1%†
Coding
SciCodeSciCode–60.8%
Arena WebDevArena (LMArena)–1687†
LiveBench 2.0 CodingLiveBench79.2%†67.8%
SciCode (AA)Artificial Analysis67.7%60.8%
IOIVals AI–81.9%†
Code Migration v1.1Vals AI83.3%†–
ProgramBenchVals AI19.0%†–
SWE-bench MultimodalVals AI62.3%†–
Vibe Code Bench v1.1Vals AI93.8%†84.9%†
ALE-BenchEpoch AI Benchmarking Hub–1932.8†
Terminal-Bench 4.0 (AA)Artificial Analysis59.6%67.2%
Startrise FrontendStartrise–82.5%
GameBench 2 OverallDuelLab GameBench 2–78.2
GameBench 2 by reasoning settingDuelLab GameBench 2–79.2†
Design Arena WebsiteDesign Arena–1320
FrontierCode 1.1 (AA)Artificial Analysis56.2%47.1%
Show all 71 benchmarks
MetricPublisherClaude Fable 5.2 (max)Kimi K3.1 Pro
Coding
FrontierCode 2.0 (AA)Artificial Analysis48.8%25.4%
Agents & tools
Arena AgentArena (LMArena)–5.2†
LiveBench Long AgenticLiveBench82.9%†38.7%
LiveBench BrowserLiveBench86.9%†75.9%
GDPval-AA v2.1, normalised scoreArtificial Analysis–67.3%
GDPval-AA v2.1Artificial Analysis18311858
Analyst Agent (AA)Artificial Analysis–38.8%
Finance Agent v2.1Vals AI69.5%†61.5%†
Harvey's Legal Agent Benchmark v1.1Vals AI5.0%†11.7%†
Legal Research BenchVals AI46.1%†37.5%†
SREBenchVals AI–27.1%†
Tax Agent BenchVals AI32.1%†24.9%†
Terminal-Bench 4.0 (Vals)Vals AI65.2%†63.6%†
Terminal-Bench ScienceVals AI55.7%†31.4%†
AutomationBenchArtificial Analysis76.4%73.3%
GDP.pdf (AA)Artificial Analysis24.2%31.4%
Harvey LAB-AA v1.1Harvey7.2%–
AA-Briefcase v1.1Artificial Analysis17851674
Design Arena AgenticDesign Arena–1284
Terminal-Bench-Science 0.1 (AA)Artificial Analysis73.3%34.3%
CWE-Bench (AA)Artificial Analysis–60.8%
DeepSec-Bench (AA)Artificial Analysis–36.7%
CyberGym end-to-end (AA)Artificial Analysis–94.7%
Maths
ProofBenchVals AI–91.0%
Knowledge
LiveBench 2.0 Data AnalysisLiveBench81.5%†79.1%
LiveBench ResearchLiveBench94.5%†82.1%
AA-Omniscience v1.1Artificial Analysis66.829.9
BioMysteryBenchVals AI83.7%†75.6%†
Excel Modeling Benchmark v1.1Vals AI77.4%†70.0%†
AA-Omniscience v1.1: accuracyArtificial Analysis79.1%48.9%
AA-Omniscience v1.1: non-hallucinationArtificial Analysis40.7%62.7%
HealthBench Professional (AA)OpenAI67.7%–
Multimodal
LiveBench DesignLiveBench85.1%†73.7%
MMMU-ProArtificial Analysis–83.9%
AA-3DArtificial Analysis12711112
Long context
AA-LCR v1.1Artificial Analysis83.3%86.3%
MLCRArtificial Analysis–38.3%
Composite
LiveBench 2.0LiveBench84.9%†68.7%
AA Intelligence Index v5.0Artificial Analysis64.646.5
AA Intelligence Index v4.3.2Artificial Analysis–55.1
AA Progress Index v1Artificial Analysis–340.7
Vals IndexVals AI71.3†62.5†
Vals Finance IndexVals AI63.6%†56.0%†
Vals Science IndexVals AI63.7%†44.4%†
AA Cyber IndexArtificial Analysis–64.1
Metadata
AA Openness IndexArtificial Analysis–33.3

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

  • Kimi K3.1 Pro: BenchLeader Index 61.8 → 61.2.
  • Kimi K3.1 Pro: 5 score revisions.
  • Kimi K3.1 Pro: BenchLeader Index 61.3 → 61.8.
  • Kimi K3.1 Pro: 1 new result (GameBench 2 Overall); 1 score revision.
  • Kimi K3.1 Pro: 1 score revision.
  • Kimi K3.1 Pro: BenchLeader Index 59.3 → 61.3.
  • Kimi K3.1 Pro: 3 new results (SciCode, ProofBench, Startrise Frontend).
  • Kimi K3.1 Pro: BenchLeader Index 61.8 → 59.3.
  • Kimi K3.1 Pro: 5 new results (AA Intelligence Index v5.0, AA Progress Index v1, HLE-Diamond (AA)…); 2 score revisions; Kimi K3.1 Pro cost per task moved from $2.11/M to $3.68/M (74% up).
  • Kimi K3.1 Pro: BenchLeader Index 62.3 → 61.8.

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

Claude Fable 5.2 vs Kimi K3.1 Pro: questions

Is Claude Fable 5.2 better than Kimi K3.1 Pro?
Claude Fable 5.2 (max) leads on quality: 69.4 vs 61.2. 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 Kimi K3.1 Pro: which is cheaper, and will that change?
Kimi K3.1 Pro is cheaper today: $4.00 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 Kimi K3.1 Pro better for coding?
Claude Fable 5.2 scores higher in coding (80 vs 60 on the category index, where 50 is average). On FrontierCode 2.0 (AA), the top shared coding benchmark, it is 48.8% for Claude Fable 5.2 against 25.4% for Kimi K3.1 Pro.
Which is faster, Claude Fable 5.2 or Kimi K3.1 Pro?
Claude Fable 5.2 streams ~2× faster (72 vs 32 output tokens per second, Artificial Analysis 7-day median).
Which is better for long documents?
Kimi K3.1 Pro scores higher on long-context benchmarks (68 vs 66). Both take about 1M tokens: Claude Fable 5.2 1,000,000, Kimi K3.1 Pro 1,048,576.
More questions (3)
Which has lower latency?
Claude Fable 5.2 answers first: 3.0 s against 167.4 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 Kimi K3.1 Pro?
Across the 18 benchmarks both have, Claude Fable 5.2 leads 13, Kimi K3.1 Pro leads 5. 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.