Claude Fable 5 vs Kimi K3.1 Pro Together
Full profiles: Claude Fable 5 (Anthropic) and Kimi K3.1 Pro Together (Moonshot AI): every benchmark, price and rank.
Updated · Data from 11 sources
As of 9 Nov 2026, Claude Fable 5 is ahead of Kimi K3.1 Pro Together on quality (66.6 vs 60.5 on the BenchLeader Index). Claude Fable 5 leads in every category we measure both in.
Key facts (as of 9 Nov 2026)
- Claude Fable 5 scores 66.6 on the BenchLeader Index and Kimi K3.1 Pro Together scores 60.5 (BenchLeader, 9 Nov 2026).
- Claude Fable 5 costs $20.00 per 1M tokens blended (list price, 9 Nov 2026).
Claude Fable 5 benchmarks Anthropic
Kimi K3.1 Pro Together benchmarks max Moonshot AIAdd a third modelWhich 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 |
|---|---|---|---|
| Reasoning | Claude Fable 5 | 80 vs 67 category score | High |
| Knowledge | Either | 67 vs 68 category score | Either |
| Chat quality (human preference) | – | Only Claude Fable 5 has an Arena rating (68 category score) | Not comparable |
| 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 leads on quality: 66.6 vs 60.5.
- Claude Fable 5 is stronger in agents & tools, coding, human preference, reasoning.
- Kimi K3.1 Pro Together (max) is stronger in knowledge, maths.
At a glance
| Spec | Claude Fable 5 | Kimi K3.1 Pro Together |
|---|---|---|
| Developer | Anthropic | Moonshot AI |
| Released | 9 Jun 2026 | 23 Oct 2026 |
| Context window (tokens) | 1,000,000 | – |
| Compared at | Claude Fable 5 | Kimi K3.1 Pro Together (max) |
| Open weights | No | No |
| Price in / out / cached input per 1M | $10.00 / $50.00 / $1.00 | – |
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 | Kimi K3.1 Pro Together (max) | Leader |
|---|---|---|---|
| Reasoning | 80.1 | 67.1 | Claude Fable 5 |
| Coding | 70.5 | – | not comparable |
| Agents & tools | 63.4 | – | not comparable |
| Maths | – | 65.8 | not comparable |
| Knowledge | 66.8 | 67.6 | level |
| Human preference | 67.7 | – | not 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.
Dashed: that model has no result on the axis it crosses; the line only joins its neighbours.
Not drawn, no result for these models: Instruction following, Long context, Multimodal.
Where sources disagree
Across the 0 benchmarks both have, Claude Fable 5 leads 0, Kimi K3.1 Pro Together leads 0. Every overall index that rates both puts Claude Fable 5 ahead.
| Overall index | Claude Fable 5 | Kimi K3.1 Pro Together (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 66.6 | 60.5 | Claude Fable 5 |
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 | Kimi K3.1 Pro Together (max) |
|---|---|---|
| Blended price per 1M tokens | $20.00 | – |
| Input / output per 1M | $10.00 / $50.00 | – / – |
| Cached input per 1M | $1.00 | – |
| Price per task: chat reply | $0.019 | – |
| Price per task: summarize a 30-page report | $0.150 | – |
| Price per task: code edit | $0.135 | – |
| Price per task: agentic coding session | $0.800 | – |
| Price per task: structured extraction | $0.030 | – |
| Agentic coding session, input mostly cached | $0.395 | – |
| Output speed | 55 tok/s | – |
| Time to first answer | 4.3 s | – |
Each model is compared at its best-ranked reasoning-effort setting. Claude Fable 5 scores 66.6 and takes 4 s to its first answer token; Claude Fable 5 (max) scores 65.3 in 95 s, Claude Fable 5 (high) scores 64.3 in 4 s. Kimi K3.1 Pro Together (max) scores 60.5. 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
115 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 | Kimi K3.1 Pro Together (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 66.6 | 60.5 |
| Agents & tools score | BenchLeader | 63.4 | – |
| Coding score | BenchLeader | 70.5 | – |
| Human preference score | BenchLeader | 67.7 | – |
| Knowledge score | BenchLeader | 66.8 | 67.6 |
| Reasoning score | BenchLeader | 80.1 | 67.1 |
| Maths score | BenchLeader | – | 65.8 |
| Blended price $/M | BenchLeader | $20.00 | – |
| Output speed | BenchLeader | 55 tok/s | – |
| Time to first answer | BenchLeader | 4.3 s | – |
| Context window | BenchLeader | 1,000,000 tokens | – |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 85.9%† | 94.2% |
| SimpleBench | SimpleBench | 81.9%† | – |
| Arena Hard Prompts | Arena (LMArena) | 1529† | – |
| LiveBench 1.0 Reasoning | LiveBench | 89.7%† | – |
| GPQA Diamond (AA) | Artificial Analysis | 92.6%† | – |
| Humanity's Last Exam (AA) | Artificial Analysis | 55.5%† | – |
| GPQA Diamond (Vals) | Vals AI | 93.2% | – |
| EnigmaEval | Scale AI SEAL | 39.3%† | – |
| Kagi LLM Benchmark | Kagi LLM Benchmark | 88.8% | – |
| ARC-AGI-1 | ARC Prize | 98.5%† | – |
| ARC-AGI-2 | ARC Prize | 89.2%† | – |
| CritPt | Artificial Analysis | 28.6%† | – |
| Chess Puzzles | Epoch AI Benchmarking Hub | 47.0%† | 45.0% |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 52.0%† | 42.0% |
| LMCA | Epoch AI Benchmarking Hub | 60.3%† | – |
| DTBench | Epoch AI Benchmarking Hub | 98.4%† | – |
| ForecastBench | ForecastBench | 66.0%† | – |
| BTF-3 | Epoch AI Benchmarking Hub | 13.0%† | – |
| Coding | |||
| SciCode | SciCode | 61.0%† | – |
| WeirdML | WeirdML | 91.9%† | – |
| FrontierCode | Cognition | 53.5% | – |
| GSO-Bench | GSO-Bench | 78.4% | – |
| Arena Coding | Arena (LMArena) | 1551† | – |
| Arena WebDev | Arena (LMArena) | 1625† | – |
| LiveBench 1.0 Coding | LiveBench | 86.0%† | – |
Show all 115 benchmarks
| Metric | Publisher | Claude Fable 5 | Kimi K3.1 Pro Together (max) |
|---|---|---|---|
| Coding | |||
| LiveCodeBench | Vals AI | 89.8% | – |
| SWE-bench (Vals) | Vals AI | 95.0% | – |
| Code Migration | Vals AI | 55.1% | – |
| ProgramBench | Vals AI | 2.0% | – |
| Vibe Code Bench v1.1 | Vals AI | 90.3% | – |
| SWE Atlas: Codebase QnA | Scale AI SEAL | 39.0%† | – |
| SWE Atlas: Refactoring | Scale AI SEAL | 54.8%† | – |
| SWE Atlas: Test Writing | Scale AI SEAL | 55.6%† | – |
| MirrorCode | Epoch AI Benchmarking Hub | 63.9%† | – |
| Surface Evolver Bench | Epoch AI Benchmarking Hub | 95.0%† | – |
| DeepSWE v1.1 | Epoch AI Benchmarking Hub | 69.7%† | – |
| ALE-Bench | Epoch AI Benchmarking Hub | 2041.3† | – |
| FrontierSWE | Epoch AI Benchmarking Hub | 47.0%† | – |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 42.4%† | – |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | 84.6%† | – |
| Startrise Frontend | Startrise | 73.8% | – |
| GameBench 2 Overall | DuelLab GameBench 2 | 65.8 | – |
| GameBench 2 by reasoning setting | DuelLab GameBench 2 | 58.1† | – |
| Design Arena Website | Design Arena | 1292 | – |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 44.9%† | – |
| Remote Labor Index | Scale AI / CAIS | 16.1% | – |
| APEX-Agents | Mercor | 63.6% | – |
| Arena Agent | Arena (LMArena) | 7.7† | – |
| LiveBench Agentic Coding | LiveBench | 62.2%† | – |
| Terminal-Bench Hard | Artificial Analysis | 62.9%† | – |
| τ²-Bench Telecom (AA) | Artificial Analysis | 98.5%† | – |
| Terminal-Bench 2.1 (Vals) | Vals AI | 80.5% | – |
| MCP Atlas | Scale AI SEAL | 83.3% | – |
| HiL-Bench | Scale AI SEAL | 56.3% | – |
| τ³-bench Banking | τ²-bench | 39.7%† | – |
| τ³-Banking (AA) | Artificial Analysis | 38.1%† | – |
| Analyst Agent (AA) | Artificial Analysis | 48.8%† | – |
| Finance Agent v2 | Vals AI | 56.3% | – |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 11.3% | – |
| Legal Research Bench | Vals AI | 49.5% | – |
| Tax Agent Bench | Vals AI | 38.3% | – |
| Terminal-Bench 4.0 (Vals) | Vals AI | 41.4% | – |
| Terminal-Bench Science | Vals AI | 15.7% | – |
| Web Search Index | Vals AI | 46.9% | – |
| Arena Search | Arena (LMArena) | 1229† | – |
| PostTrainBench | Epoch AI Benchmarking Hub | 41.8%† | – |
| GBAEval | Epoch AI Benchmarking Hub | 74.5% | – |
| Vending-Bench 2 | Andon Labs | 4529.9 | – |
| AutomationBench | Artificial Analysis | 54.1%† | – |
| GDP.pdf (AA) | Artificial Analysis | 24.0%† | – |
| EnterpriseOps-Gym | Artificial Analysis | 51.1%† | – |
| AA-Briefcase v1.1 | Artificial Analysis | 1535† | – |
| Design Arena Agentic | Design Arena | 1268 | – |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 87.0%† | 78.3% |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 90.2%† | 65.8% |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 99.7%† | 100.0% |
| ProofBench | Vals AI | 95.0%† | – |
| LiveBench Mathematics | LiveBench | 96.0%† | – |
| Arena Maths | Arena (LMArena) | 1521† | – |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 70.7%† | 62.2% |
| LiveBench 1.0 Data Analysis | LiveBench | 80.5%† | – |
| MMLU-Pro | Vals AI | 91.5% | – |
| LegalBench | Vals AI | 88.6% | – |
| CorpFin | Vals AI | 71.8% | – |
| TaxEval | Vals AI | 76.9% | – |
| PRBench Finance | Scale AI SEAL | 53.9% | – |
| PRBench Legal | Scale AI SEAL | 52.6% | – |
| Excel Modeling Benchmark | Vals AI | 73.7% | – |
| MedCode | Vals AI | 56.1% | – |
| MedScribe | Vals AI | 88.5% | – |
| Public Benefits Bench v1.1 | Vals AI | 70.4% | – |
| EBR-bench | Epoch AI Benchmarking Hub | 39.5%† | – |
| GDP.pdf | Epoch AI Benchmarking Hub | 30.0% | – |
| Instruction following | |||
| LiveBench Language | LiveBench | 90.7%† | – |
| LiveBench Instruction Following | LiveBench | 75.8%† | – |
| IFBench | Artificial Analysis | 63.5%† | – |
| Arena Instruction Following | Arena (LMArena) | 1509† | – |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1504† | – |
| EQ-Bench 4 | EQ-Bench | 1313 | – |
| Arena Creative Writing | Arena (LMArena) | 1501† | – |
| Arena Multi-turn | Arena (LMArena) | 1517† | – |
| Arena Longer Queries | Arena (LMArena) | 1522† | – |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1326† | – |
| MMMU-Pro (Vals) | Vals AI | 89.3% | – |
| MortgageTax | Vals AI | 68.9% | – |
| Blueprint-Bench 2 | Epoch AI Benchmarking Hub | 38.6% | – |
| Long context | |||
| AA-LCR v1.1 | Artificial Analysis | 82.3%† | – |
| Arena Document | Arena (LMArena) | 1500† | – |
| MLCR | Artificial Analysis | 20.6%† | – |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 164.2 | – |
| LiveBench 1.0 | LiveBench | 83.0%† | – |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 49.6† | – |
| AA Progress Index v1 | Artificial Analysis | 329.3† | – |
| Vals RSI Index | Vals AI | 24.3%† | – |
| Vals Multimodal Index | Vals AI | 74.2% | – |
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 Together (max): first results.
- Claude Fable 5: 1 score revision.
- Claude Fable 5: 1 score revision.
- Claude Fable 5: BenchLeader Index 67.3 → 66.5.
- Claude Fable 5: 1 score revision.
- Claude Fable 5: 1 new result (Harvey's Legal Agent Benchmark v1).
- Claude Fable 5: 1 score revision.
- Claude Fable 5: 8 new results (LiveBench 2.0, LiveBench Long Agentic, LiveBench 2.0 Reasoning…).
- Claude Fable 5: 1 new result (Startrise Frontend); 1 score revision.
- Claude Fable 5: BenchLeader Index 67.8 → 67.3.
Related comparisons
- Claude Fable 5 vs Claude Fable 5.2
- Claude Fable 5 vs Claude Opus 5.5
- Claude Fable 5 vs Gemini 4 Carbon
- Kimi K3.1 Pro Together vs Claude Fable 5.2
- Kimi K3.1 Pro Together vs Claude Opus 5.5
- Kimi K3.1 Pro Together vs Gemini 4 Carbon
- Kimi K3.1 Pro Together vs GPT-6 Astra
- Claude Opus 4.8 vs Kimi K3.1 Pro Together
Rankings: Best LLM overall · Best LLM for coding · Best LLM for agents · Best cheap LLMs
Claude Fable 5 vs Kimi K3.1 Pro Together: questions
- Is Claude Fable 5 better than Kimi K3.1 Pro Together?
- Claude Fable 5 leads on quality: 66.6 vs 60.5. The BenchLeader Index combines every independent quality benchmark; Claude Fable 5 is ahead overall as of 9 Nov 2026, but check the category scores for your use.
- When was Kimi K3.1 Pro Together released?
- Kimi K3.1 Pro Together was released on 23 Oct 2026.