Claude Fable 5.2 vs Kimi K3
Full profiles: Claude Fable 5.2 (Anthropic) and Kimi K3 (Moonshot AI): every benchmark, price and rank.
Updated · Data from 11 sources
As of 9 Nov 2026, Claude Fable 5.2 is ahead of Kimi K3 on quality (69.4 vs 62.0 on the BenchLeader Index), but Kimi K3 is 2.7× cheaper at $6.00 vs $16.00 per 1M tokens blended. Choose Claude Fable 5.2 for knowledge (82 vs 60), reasoning (78 vs 60), and coding (80 vs 65) and fast first answers (3.0 s vs 65.8 s), where it also streams ~1.5× faster; choose Kimi K3 for long context (69 vs 66).
Key facts (as of 9 Nov 2026)
- Claude Fable 5.2 scores 69.4 on the BenchLeader Index and Kimi K3 scores 62.0 (BenchLeader, 9 Nov 2026).
- Claude Fable 5.2 costs $16.00 per 1M tokens blended (list price, 9 Nov 2026).
- Kimi K3 costs $6.00 per 1M tokens blended (list price, 9 Nov 2026).
- Claude Fable 5.2 streams ~1.5× faster than Kimi K3 (Artificial Analysis, 7-day median, 9 Nov 2026).
- Of the 17 benchmarks both models have, Claude Fable 5.2 leads 16 (BenchLeader, 9 Nov 2026).
Claude Fable 5.2 benchmarks 
Kimi K3 benchmarks 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 case | Pick | Why | Confidence |
|---|---|---|---|
| Coding | Claude Fable 5.2 | 80 vs 65 category score; SciCode (AA) 67.7% vs 59.5% | High |
| Reasoning | Claude Fable 5.2 | 78 vs 60 category score; HLE-Diamond (AA) 80.2% vs 26.9% | High |
| Knowledge | Claude Fable 5.2 | 82 vs 60 category score; HealthBench Professional (AA) 67.7% vs 53.2% | High |
| Long documents | Kimi K3 | 69 vs 66 category score; AA-LCR v1.1 88.7% vs 83.3% | Medium |
| Chat quality (human preference) | – | Only Kimi K3 has an Arena rating (68 category score) | Not comparable |
| Lowest cost | Kimi K3 | $6.00 vs $16.00 per 1M blended; agentic coding session $0.240 vs $0.640 | – |
| Fastest first answer | Claude Fable 5.2 | 3.0 s (Claude Fable 5.2 (max)) vs 65.8 s (Kimi K3 (max)) to the first answer token | – |
| High volume on a budget | Neither flagship | A 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 62.0.
- Claude Fable 5.2 (max) is stronger in coding, knowledge, reasoning.
- Kimi K3 (max) is stronger in long context, agents & tools, human preference, maths, multimodal.
- Kimi K3 (max) is 2.7× cheaper ($6.00 vs $16.00 per 1M blended).
- Claude Fable 5.2 (max) streams 1.7× faster (72 vs 42 tokens per second).
At a glance
| Spec | Claude Fable 5.2 | Kimi K3 |
|---|---|---|
| Developer | Anthropic | Moonshot AI |
| Released | 9 Nov 2026 | 16 Jul 2026 |
| Context window (tokens) | 1,000,000 | 1,048,576 |
| Compared at | Claude Fable 5.2 (max) | Kimi K3 (max) |
| Open weights | No | Yes |
| Price in / out / cached input per 1M | $8.00 / $40.00 / $0.200 | $3.00 / $15.00 / $0.300 |
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.
| Category | Claude Fable 5.2 (max) | Kimi K3 (max) | Leader |
|---|---|---|---|
| Reasoning | 78.4 | 59.5 | Claude Fable 5.2 |
| Coding | 80.2 | 64.5 | Claude Fable 5.2 |
| Agents & tools | – | 58.7 | not comparable |
| Maths | – | 63.2 | not comparable |
| Knowledge | 81.7 | 60.0 | Claude Fable 5.2 |
| Human preference | – | 68.0 | not comparable |
| Multimodal | – | 63.0 | not comparable |
| Long context | 66.4 | 69.2 | Kimi K3 |
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.
Not drawn, measured for fewer than two of these models: Agents & tools, Maths, Instruction following, Multimodal, Human preference.
ModelIndex
Where sources disagree
Across the 17 benchmarks both have, Claude Fable 5.2 leads 16, Kimi K3 leads 1. Every overall index that rates both puts Claude Fable 5.2 ahead.
| Overall index | Claude Fable 5.2 (max) | Kimi K3 (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 69.4 | 62.0 | Claude Fable 5.2 |
| AA Intelligence Index v5.0 | 64.6 | 17.4† | Claude Fable 5.2 |
| Vals Index | 71.3† | 53.0 | Claude 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.
| Measure | Claude Fable 5.2 (max) | Kimi K3 (max) |
|---|---|---|
| Blended price per 1M tokens | $16.00 | $6.00 |
| Input / output per 1M | $8.00 / $40.00 | $3.00 / $15.00 |
| Cached input per 1M | $0.200 | $0.300 |
| Price per task: chat reply | $0.015 | $0.0057 |
| Price per task: summarize a 30-page report | $0.120 | $0.045 |
| Price per task: code edit | $0.108 | $0.041 |
| Price per task: agentic coding session | $0.640 | $0.240 |
| Price per task: structured extraction | $0.024 | $0.0090 |
| Agentic coding session, input mostly cached | $0.289 | $0.118 |
| Cost per benchmark task (AA Index) | $26.54 | – |
| Output tokens per task (AA Index) | 274k | – |
| Of which reasoning | 193k | – |
| Output speed | 72 tok/s | 42 tok/s |
| Time to first answer | 3.0 s | 65.8 s |
| Time to a complete answer | – | 140.2 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. Kimi K3 (max) scores 62.0 and takes 66 s to its first answer token; Kimi K3 scores 59.5 in 1 s, Kimi K3 (low) scores 53.7 in 12 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
149 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.
| Metric | Publisher | Claude Fable 5.2 (max) | Kimi K3 (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 69.4 | 62.0 |
| Coding score | BenchLeader | 80.2 | 64.5 |
| Knowledge score | BenchLeader | 81.7 | 60.0 |
| Long context score | BenchLeader | 66.4 | 69.2 |
| Reasoning score | BenchLeader | 78.4 | 59.5 |
| Agents & tools score | BenchLeader | – | 58.7 |
| Human preference score | BenchLeader | – | 68.0 |
| Maths score | BenchLeader | – | 63.2 |
| Multimodal score | BenchLeader | – | 63.0 |
| Blended price $/M | BenchLeader | $16.00 | $6.00 |
| Output speed | BenchLeader | 72 tok/s | 42 tok/s |
| Time to first answer | BenchLeader | 3.0 s | 65.8 s |
| Context window | BenchLeader | 1,000,000 tokens | 1,048,576 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | – | 93.1% |
| SimpleBench | SimpleBench | – | 60.7% |
| Arena Hard Prompts | Arena (LMArena) | – | 1515 |
| LiveBench 2.0 Reasoning | LiveBench | 88.8%† | 90.7%† |
| LiveBench 1.0 Reasoning | LiveBench | – | 90.7%† |
| GPQA Diamond (AA) | Artificial Analysis | – | 93.5% |
| Humanity's Last Exam (AA) | Artificial Analysis | 74.3% | 46.9% |
| HLE-Diamond (AA) | Artificial Analysis | 80.2% | 26.9% |
| GPQA Diamond (Vals) | Vals AI | – | 92.9%† |
| ARC-AGI-1 | ARC Prize | 97.5% | 94.5% |
| ARC-AGI-2 | ARC Prize | 92.5% | 60.4% |
| ARC-AGI-3 | ARC Prize | 94.9% | – |
| CritPt | Artificial Analysis | 35.4% | 23.4% |
| CritPt v2 hard subset (AA) | Artificial Analysis | 76.5% | 40.5% |
| MysteryMechanism | Vals AI | 51.8%† | – |
| Chess Puzzles | Epoch AI Benchmarking Hub | – | 36.0% |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | – | 26.0% |
| LMCA | Epoch AI Benchmarking Hub | – | 52.7% |
| DTBench | Epoch AI Benchmarking Hub | – | 91.2% |
| ForecastBench | ForecastBench | – | 64.7% |
| Coding | |||
| SciCode | SciCode | – | 59.5% |
| WeirdML | WeirdML | – | 82.6% |
| FrontierCode | Cognition | – | 44.2%† |
| Arena Coding | Arena (LMArena) | – | 1537 |
| Arena WebDev | Arena (LMArena) | – | 1657 |
Show all 149 benchmarks
| Metric | Publisher | Claude Fable 5.2 (max) | Kimi K3 (max) |
|---|---|---|---|
| Coding | |||
| LiveBench 2.0 Coding | LiveBench | 79.2%† | 53.1%† |
| LiveBench 1.0 Coding | LiveBench | – | 81.5%† |
| SciCode (AA) | Artificial Analysis | 67.7% | 59.5% |
| LiveCodeBench | Vals AI | – | 87.2% |
| IOI | Vals AI | – | 48.9% |
| SWE-bench (Vals) | Vals AI | – | 93.4%† |
| Code Migration | Vals AI | – | 16.1% |
| Code Migration v1.1 | Vals AI | 83.3%† | 28.6% |
| ProgramBench | Vals AI | 19.0%† | 2.0%† |
| SWE-bench Multimodal | Vals AI | 62.3%† | 44.2% |
| Vibe Code Bench 1-100 | Vals AI | – | 18.2% |
| Vibe Code Bench v1.1 | Vals AI | 93.8%† | 85.0% |
| Surface Evolver Bench | Epoch AI Benchmarking Hub | – | 93.0% |
| DeepSWE v1.1 | Epoch AI Benchmarking Hub | – | 68.5% |
| ALE-Bench | Epoch AI Benchmarking Hub | – | 1524.5 |
| FrontierSWE | Epoch AI Benchmarking Hub | – | 25.9% |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 59.6% | 12.6% |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | – | 85.0% |
| Startrise Frontend | Startrise | – | 79.8%† |
| GameBench 2 Overall | DuelLab GameBench 2 | – | 47.2† |
| GameBench 2 by reasoning setting | DuelLab GameBench 2 | – | 43.8 |
| Design Arena Website | Design Arena | – | 1332† |
| FrontierCode 1.1 (AA) | Artificial Analysis | 56.2% | 43.6% |
| FrontierCode 2.0 (AA) | Artificial Analysis | 48.8% | 10.9%† |
| Agents & tools | |||
| APEX-Agents | Mercor | – | 47.8%† |
| Arena Agent | Arena (LMArena) | – | 0.6 |
| LiveBench Long Agentic | LiveBench | 82.9%† | 36.0%† |
| LiveBench Browser | LiveBench | 86.9%† | 75.2%† |
| LiveBench Agentic Coding | LiveBench | – | 62.2%† |
| Terminal-Bench 2.1 (Vals) | Vals AI | – | 80.9%† |
| MCP Atlas | Scale AI SEAL | – | 82.3% |
| HiL-Bench | Scale AI SEAL | – | 42.7%† |
| τ³-bench Banking | τ²-bench | – | 37.1% |
| GDPval-AA v2.1 | Artificial Analysis | 1831 | – |
| τ³-Banking (AA) | Artificial Analysis | – | 46.0% |
| ITBench SRE (AA) | Artificial Analysis | – | 47.7% |
| Analyst Agent (AA) | Artificial Analysis | – | 38.8% |
| APEX-Agents (AA) | Artificial Analysis | – | 41.3% |
| CyberBench | Vals AI | – | 75.2% |
| Finance Agent v2 | Vals AI | – | 53.1% |
| Finance Agent v2.1 | Vals AI | 69.5%† | 60.0% |
| Harvey's Legal Agent Benchmark v1.1 | Vals AI | 5.0%† | 12.9% |
| Harvey's Legal Agent Benchmark v1 | Vals AI | – | 12.9% |
| Legal Research Bench | Vals AI | 46.1%† | 46.1% |
| Tax Agent Bench | Vals AI | 32.1%† | 33.4% |
| Terminal-Bench 4.0 (Vals) | Vals AI | 65.2%† | 17.2% |
| Terminal-Bench Science | Vals AI | 55.7%† | 1.4% |
| Time Horizon Index: KSP | Vals AI | – | 10.5% |
| PostTrainBench | Epoch AI Benchmarking Hub | – | 32.0%† |
| GBAEval | Epoch AI Benchmarking Hub | – | 48.4%† |
| Vending-Bench 2 | Andon Labs | – | 5165.0† |
| AutomationBench | Artificial Analysis | 76.4% | 58.3% |
| GDP.pdf (AA) | Artificial Analysis | 24.2% | 22.0% |
| Harvey LAB-AA v1.1 | Harvey | 7.2% | 5.3% |
| EnterpriseOps-Gym | Artificial Analysis | – | 45.3% |
| AA-Briefcase v1.1 | Artificial Analysis | 1785 | 1497 |
| GDPx | GDPx by SemiAnalysis | – | 3.7% |
| Design Arena Agentic | Design Arena | – | 1257† |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 73.3% | 8.1% |
| CWE-Bench (AA) | Artificial Analysis | – | 53.3% |
| DeepSec-Bench (AA) | Artificial Analysis | – | 12.4% |
| CyberGym end-to-end (AA) | Artificial Analysis | – | 58.0% |
| FACTS Search | – | 90.3%† | |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | – | 72.2% |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | – | 39.0% |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | – | 97.2% |
| ProofBench | Vals AI | – | 87.0%† |
| LiveBench Mathematics | LiveBench | – | 84.4%† |
| AIME 2026 | MathArena | – | 96.7%† |
| HMMT February 2026 | MathArena | – | 97.0%† |
| MathArena Apex | MathArena | – | 65.6%† |
| Arena Maths | Arena (LMArena) | – | 1502 |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | – | 50.6% |
| LiveBench 2.0 Data Analysis | LiveBench | 81.5%† | 78.7%† |
| LiveBench Research | LiveBench | 94.5%† | 79.8%† |
| LiveBench 1.0 Data Analysis | LiveBench | – | 78.7%† |
| AA-Omniscience v1.1 | Artificial Analysis | 66.8 | -1.7† |
| MMLU-Pro | Vals AI | – | 88.0% |
| LegalBench | Vals AI | – | 86.2% |
| CorpFin | Vals AI | – | 71.6%† |
| TaxEval | Vals AI | – | 75.7%† |
| BioMysteryBench | Vals AI | 83.7%† | 72.6% |
| Excel Modeling Benchmark | Vals AI | – | 66.7% |
| Excel Modeling Benchmark v1.1 | Vals AI | 77.4%† | 71.3% |
| MedCode | Vals AI | – | 49.4% |
| MedScribe | Vals AI | – | 88.0% |
| Public Benefits Bench v1.1 | Vals AI | – | 68.2% |
| GDP.pdf | Epoch AI Benchmarking Hub | – | 19.0% |
| AA-Omniscience v1.1: accuracy | Artificial Analysis | 79.1% | 42.4%† |
| AA-Omniscience v1.1: non-hallucination | Artificial Analysis | 40.7% | 23.4%† |
| HealthBench Professional (AA) | OpenAI | 67.7% | 53.2% |
| Instruction following | |||
| LiveBench Language | LiveBench | – | 85.5%† |
| LiveBench Instruction Following | LiveBench | – | 71.4%† |
| Arena Instruction Following | Arena (LMArena) | – | 1489 |
| Human preference | |||
| Arena Text | Arena (LMArena) | – | 1487 |
| EQ-Bench 4 | EQ-Bench | – | 1319† |
| Arena Creative Writing | Arena (LMArena) | – | 1459 |
| Arena Multi-turn | Arena (LMArena) | – | 1501 |
| Arena Longer Queries | Arena (LMArena) | – | 1500 |
| Multimodal | |||
| LiveBench Design | LiveBench | 85.1%† | 72.5%† |
| MMMU-Pro | Artificial Analysis | – | 80.5% |
| MMMU-Pro (Vals) | Vals AI | – | 88.2%† |
| MortgageTax | Vals AI | – | 66.3%† |
| SAGE | Vals AI | – | 86.8% |
| Blueprint-Bench 2 | Epoch AI Benchmarking Hub | – | 29.5%† |
| Code2Video-AA | Artificial Analysis | – | 1041 |
| AA-3D | Artificial Analysis | 1271 | 984 |
| Long context | |||
| AA-LCR v1.1 | Artificial Analysis | 83.3% | 88.7% |
| MLCR | Artificial Analysis | – | 21.7% |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | – | 158.5† |
| LiveBench 2.0 | LiveBench | 84.9%† | 65.0%† |
| LiveBench 1.0 | LiveBench | – | 79.2%† |
| AA Intelligence Index v5.0 | Artificial Analysis | 64.6 | 17.4† |
| AA Intelligence Index v4.3.2 | Artificial Analysis | – | 43.6 |
| AA Progress Index v1 | Artificial Analysis | – | 319.9 |
| Vals Index | Vals AI | 71.3† | 53.0 |
| Vals Finance Index | Vals AI | 63.6%† | 58.0% |
| Vals RSI Index | Vals AI | – | 20.9% |
| Vals Science Index | Vals AI | 63.7%† | – |
| Vals Multimodal Index | Vals AI | – | 73.4%† |
| Vals Router Index | Vals AI | – | 53.0%† |
| AA Cyber Index | Artificial Analysis | – | 41.3 |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | – | 26.6% |
| Metadata | |||
| AA Openness Index | Artificial Analysis | – | 38.9 |
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 (max): 2 score revisions.
- Kimi K3 (max): 1 new result (MirrorCode).
- Kimi K3 (max): 1 score revision.
- Kimi K3 (max): BenchLeader Index 63.1 → 62.1.
- Kimi K3 (max): 3 new results (AA Progress Index v1, HLE-Diamond (AA), CritPt v2 hard subset (AA)); 1 score revision.
- Kimi K3 (max): 7 new results (Code Migration v1.1, Excel Modeling Benchmark v1.1, Finance Agent v2.1…).
- Kimi K3 (max): 1 new result (Terminal-Bench-Science 0.1 (AA)); 1 score revision.
- Kimi K3 (max): 3 score revisions.
- Kimi K3 (max): 1 score revision.
- Kimi K3 (max): 1 new result (τ³-bench Banking).
Related comparisons
- Claude Fable 5.2 vs Claude Opus 5.5
- Claude Fable 5.2 vs Gemini 4 Carbon
- Claude Fable 5.2 vs GPT-6 Astra
- Kimi K3 vs Claude Opus 5.5
- Kimi K3 vs Gemini 4 Carbon
- Kimi K3 vs GPT-6 Astra
- Claude Sonnet 5.5 vs Kimi K3
- Claude Fable 5.2 vs Kimi K2.6
Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
Claude Fable 5.2 vs Kimi K3: questions
- Is Claude Fable 5.2 better than Kimi K3?
- Claude Fable 5.2 (max) leads on quality: 69.4 vs 62.0. 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 Kimi K3: which is cheaper, and will that change?
- Kimi K3 is cheaper today: $6.00 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 better for coding?
- Claude Fable 5.2 scores higher in coding (80 vs 65 on the category index, where 50 is average).
- Which is faster, Claude Fable 5.2 or Kimi K3?
- Claude Fable 5.2 streams ~1.5× faster (72 vs 42 output tokens per second, Artificial Analysis 7-day median).
- Which is better for long documents?
- Kimi K3 scores higher on long-context benchmarks (69 vs 66). Both take about 1M tokens: Claude Fable 5.2 1,000,000, Kimi K3 1,048,576.
More questions (3)
- Which has lower latency?
- Claude Fable 5.2 answers first: 3.0 s against 65.8 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?
- Across the 17 benchmarks both have, Claude Fable 5.2 leads 16, Kimi K3 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.