Claude Fable 5.2 vs Kimi K3.1 Pro Together
Full profiles: Claude Fable 5.2 (Anthropic) and Kimi K3.1 Pro Together (Moonshot AI): every benchmark, price and rank.
Updated · Data from 5 sources
As of 9 Nov 2026, Claude Fable 5.2 is ahead of Kimi K3.1 Pro Together on quality (69.4 vs 60.5 on the BenchLeader Index). Claude Fable 5.2 leads in every category we measure both in.
Key facts (as of 9 Nov 2026)
- Claude Fable 5.2 scores 69.4 on the BenchLeader Index and Kimi K3.1 Pro Together scores 60.5 (BenchLeader, 9 Nov 2026).
- Claude Fable 5.2 costs $16.00 per 1M tokens blended (list price, 9 Nov 2026).
Claude Fable 5.2 benchmarks max 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 5.2 | 78 vs 67 category score | High |
| Knowledge | Claude Fable 5.2 | 82 vs 68 category score | High |
| 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 60.5.
- Claude Fable 5.2 (max) is stronger in coding, knowledge, long context, reasoning.
- Kimi K3.1 Pro Together (max) is stronger in maths.
At a glance
| Spec | Claude Fable 5.2 | Kimi K3.1 Pro Together |
|---|---|---|
| Developer | Anthropic | Moonshot AI |
| Released | 9 Nov 2026 | 23 Oct 2026 |
| Context window (tokens) | 1,000,000 | – |
| Compared at | Claude Fable 5.2 (max) | Kimi K3.1 Pro Together (max) |
| Open weights | No | No |
| Price in / out / cached input per 1M | $8.00 / $40.00 / $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.
| Category | Claude Fable 5.2 (max) | Kimi K3.1 Pro Together (max) | Leader |
|---|---|---|---|
| Reasoning | 78.4 | 67.1 | Claude Fable 5.2 |
| Coding | 80.2 | – | not comparable |
| Maths | – | 65.8 | not comparable |
| Knowledge | 81.7 | 67.6 | Claude Fable 5.2 |
| Long context | 66.4 | – | 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: Agents & tools, Instruction following, Multimodal, Human preference.
Where sources disagree
Across the 0 benchmarks both have, Claude Fable 5.2 leads 0, Kimi K3.1 Pro Together leads 0. Every overall index that rates both puts Claude Fable 5.2 ahead.
| Overall index | Claude Fable 5.2 (max) | Kimi K3.1 Pro Together (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 69.4 | 60.5 | 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 K3.1 Pro Together (max) |
|---|---|---|
| Blended price per 1M tokens | $16.00 | – |
| Input / output per 1M | $8.00 / $40.00 | – / – |
| Cached input per 1M | $0.200 | – |
| Price per task: chat reply | $0.015 | – |
| Price per task: summarize a 30-page report | $0.120 | – |
| Price per task: code edit | $0.108 | – |
| Price per task: agentic coding session | $0.640 | – |
| Price per task: structured extraction | $0.024 | – |
| Agentic coding session, input mostly cached | $0.289 | – |
| Cost per benchmark task (AA Index) | $26.54 | – |
| Output tokens per task (AA Index) | 274k | – |
| Of which reasoning | 193k | – |
| Output speed | 72 tok/s | – |
| Time to first answer | 3.0 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 K3.1 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
55 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 K3.1 Pro Together (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 69.4 | 60.5 |
| Coding score | BenchLeader | 80.2 | – |
| Knowledge score | BenchLeader | 81.7 | 67.6 |
| Long context score | BenchLeader | 66.4 | – |
| Reasoning score | BenchLeader | 78.4 | 67.1 |
| Maths score | BenchLeader | – | 65.8 |
| Blended price $/M | BenchLeader | $16.00 | – |
| Output speed | BenchLeader | 72 tok/s | – |
| Time to first answer | BenchLeader | 3.0 s | – |
| Context window | BenchLeader | 1,000,000 tokens | – |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | – | 94.2% |
| LiveBench 2.0 Reasoning | LiveBench | 88.8%† | – |
| Humanity's Last Exam (AA) | Artificial Analysis | 74.3% | – |
| HLE-Diamond (AA) | Artificial Analysis | 80.2% | – |
| ARC-AGI-1 | ARC Prize | 97.5% | – |
| ARC-AGI-2 | ARC Prize | 92.5% | – |
| ARC-AGI-3 | ARC Prize | 94.9% | – |
| CritPt | Artificial Analysis | 35.4% | – |
| CritPt v2 hard subset (AA) | Artificial Analysis | 76.5% | – |
| MysteryMechanism | Vals AI | 51.8%† | – |
| Chess Puzzles | Epoch AI Benchmarking Hub | – | 45.0% |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | – | 42.0% |
| Coding | |||
| LiveBench 2.0 Coding | LiveBench | 79.2%† | – |
| SciCode (AA) | Artificial Analysis | 67.7% | – |
| Code Migration v1.1 | Vals AI | 83.3%† | – |
| ProgramBench | Vals AI | 19.0%† | – |
| SWE-bench Multimodal | Vals AI | 62.3%† | – |
| Vibe Code Bench v1.1 | Vals AI | 93.8%† | – |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 59.6% | – |
| FrontierCode 1.1 (AA) | Artificial Analysis | 56.2% | – |
| FrontierCode 2.0 (AA) | Artificial Analysis | 48.8% | – |
| Agents & tools | |||
| LiveBench Long Agentic | LiveBench | 82.9%† | – |
| LiveBench Browser | LiveBench | 86.9%† | – |
| GDPval-AA v2.1 | Artificial Analysis | 1831 | – |
| Finance Agent v2.1 | Vals AI | 69.5%† | – |
Show all 55 benchmarks
| Metric | Publisher | Claude Fable 5.2 (max) | Kimi K3.1 Pro Together (max) |
|---|---|---|---|
| Agents & tools | |||
| Harvey's Legal Agent Benchmark v1.1 | Vals AI | 5.0%† | – |
| Legal Research Bench | Vals AI | 46.1%† | – |
| Tax Agent Bench | Vals AI | 32.1%† | – |
| Terminal-Bench 4.0 (Vals) | Vals AI | 65.2%† | – |
| Terminal-Bench Science | Vals AI | 55.7%† | – |
| AutomationBench | Artificial Analysis | 76.4% | – |
| GDP.pdf (AA) | Artificial Analysis | 24.2% | – |
| Harvey LAB-AA v1.1 | Harvey | 7.2% | – |
| AA-Briefcase v1.1 | Artificial Analysis | 1785 | – |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 73.3% | – |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | – | 78.3% |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | – | 65.8% |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | – | 100.0% |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | – | 62.2% |
| LiveBench 2.0 Data Analysis | LiveBench | 81.5%† | – |
| LiveBench Research | LiveBench | 94.5%† | – |
| AA-Omniscience v1.1 | Artificial Analysis | 66.8 | – |
| BioMysteryBench | Vals AI | 83.7%† | – |
| Excel Modeling Benchmark v1.1 | Vals AI | 77.4%† | – |
| AA-Omniscience v1.1: accuracy | Artificial Analysis | 79.1% | – |
| AA-Omniscience v1.1: non-hallucination | Artificial Analysis | 40.7% | – |
| HealthBench Professional (AA) | OpenAI | 67.7% | – |
| Multimodal | |||
| LiveBench Design | LiveBench | 85.1%† | – |
| AA-3D | Artificial Analysis | 1271 | – |
| Long context | |||
| AA-LCR v1.1 | Artificial Analysis | 83.3% | – |
| Composite | |||
| LiveBench 2.0 | LiveBench | 84.9%† | – |
| AA Intelligence Index v5.0 | Artificial Analysis | 64.6 | – |
| Vals Index | Vals AI | 71.3† | – |
| Vals Finance Index | Vals AI | 63.6%† | – |
| Vals Science Index | Vals AI | 63.7%† | – |
Data as of 2026-11-09. Best configuration of each model; every score links to its source on the model pages.
What changed
- Kimi K3.1 Pro Together (max): first results.
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- Claude Fable 5.2 vs Kimi K3
Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
Claude Fable 5.2 vs Kimi K3.1 Pro Together: questions
- Is Claude Fable 5.2 better than Kimi K3.1 Pro Together?
- Claude Fable 5.2 (max) leads on quality: 69.4 vs 60.5. 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.
- When was Claude Fable 5.2 released?
- Claude Fable 5.2 was released on 9 Nov 2026.