Claude Fable 5.1 vs GLM 5.2
Full profiles: Claude Fable 5.1 (Anthropic) and GLM 5.2 (Zhipu AI): every benchmark, price and rank.
Updated · Data from 9 sources
As of 29 Oct 2026, Claude Fable 5.1 is ahead of GLM 5.2 on quality (67.0 vs 60.2 on the BenchLeader Index), but GLM 5.2 is 9.3× cheaper at $2.15 vs $20.00 per 1M tokens blended. Choose Claude Fable 5.1 for knowledge (73 vs 44), maths (73 vs 57), and coding (71 vs 62); choose GLM 5.2 for fast first answers (24.1 s vs 179.6 s) and agents & tools (63 vs 61), where it also streams faster.
Key facts (as of 29 Oct 2026)
- Claude Fable 5.1 scores 67.0 on the BenchLeader Index and GLM 5.2 scores 60.2 (BenchLeader, 29 Oct 2026).
- Claude Fable 5.1 costs $20.00 per 1M tokens blended (list price, 29 Oct 2026).
- GLM 5.2 costs $2.15 per 1M tokens blended (list price, 29 Oct 2026).
- GLM 5.2 streams faster than Claude Fable 5.1 (Artificial Analysis, 7-day median, 29 Oct 2026).
- Of the 31 benchmarks both models have, Claude Fable 5.1 leads 31 (BenchLeader, 29 Oct 2026).
- On Arena WebDev, Claude Fable 5.1 is rated 1745 and GLM 5.2 1606 (LMArena, as published by 29 Oct 2026).
Claude Fable 5.1 benchmarks max Anthropic
GLM 5.2 benchmarks max Zhipu AIOpen in the comparison toolWhich 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 5.1 | 71 vs 62 category score; Arena WebDev 1745 vs 1606 | High |
| Agents & tool use | GLM 5.2 | 63 vs 61 category score; τ³-Banking (AA) 34.6% vs 47.2% | Medium |
| Maths | Claude Fable 5.1 | 73 vs 57 category score; FrontierMath Tiers 1–3 90.2% vs 59.2% | High |
| Reasoning | Claude Fable 5.1 | 71 vs 66 category score; Arena Hard Prompts 1523 vs 1496 | Medium |
| Knowledge | Claude Fable 5.1 | 73 vs 44 category score; SimpleQA Verified 70.8% vs 34.2% | High |
| Long documents | Claude Fable 5.1 | 68 vs 64 category score; AA-LCR v1.1 85.3% vs 78.3% | Medium |
| Chat quality (human preference) | Claude Fable 5.1 | 70 vs 67 on Arena votes | Medium |
| Lowest cost | GLM 5.2 | $2.15 vs $20.00 per 1M blended; agentic coding session $0.102 vs $0.800 | – |
| Fastest first answer | GLM 5.2 | 24.1 s (GLM 5.2 (max)) vs 179.6 s (Claude Fable 5.1 (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 5.1 (max) leads on quality: 67.0 vs 60.2.
- Claude Fable 5.1 (max) is stronger in coding, human preference, knowledge, long context, maths, multimodal, reasoning.
- GLM 5.2 (max) is stronger in agents & tools, instruction following.
- GLM 5.2 (max) is 9.3× cheaper ($2.15 vs $20.00 per 1M blended).
- GLM 5.2 (max) streams 1.4× faster (94 vs 66 tokens per second).
At a glance
| Spec | Claude Fable 5.1 | GLM 5.2 |
|---|---|---|
| Developer | Anthropic | Zhipu AI |
| Released | 1 Sept 2026 | 16 Jun 2026 |
| Context window (tokens) | 1,000,000 | 1,000,000 |
| Compared at | Claude Fable 5.1 (max) | GLM 5.2 (max) |
| Open weights | No | Yes |
| Price in / out / cached input per 1M | $10.00 / $50.00 / $0.250 | $1.40 / $4.40 / $0.299 |
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 5.1 (max) | GLM 5.2 (max) | Leader |
|---|---|---|---|
| Reasoning | 70.8 | 65.9 | Claude Fable 5.1 |
| Coding | 70.7 | 62.1 | Claude Fable 5.1 |
| Agents & tools | 60.5 | 62.8 | GLM 5.2 |
| Maths | 72.6 | 57.2 | Claude Fable 5.1 |
| Knowledge | 72.9 | 43.6 | Claude Fable 5.1 |
| Instruction following | – | 71.7 | not comparable |
| Human preference | 69.9 | 66.5 | Claude Fable 5.1 |
| Multimodal | 67.1 | – | not comparable |
| Long context | 67.6 | 64.0 | Claude Fable 5.1 |
Where sources disagree
Across the 31 benchmarks both have, Claude Fable 5.1 leads 31, GLM 5.2 leads 0. Every overall index that rates both puts Claude Fable 5.1 ahead.
| Overall index | Claude Fable 5.1 (max) | GLM 5.2 (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 67.0 | 60.2 | Claude Fable 5.1 |
| Arena Text | 1503 | 1475 | Claude Fable 5.1 |
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; suite cost is what Artificial Analysis paid to run its whole Intelligence Index.
| Measure | Claude Fable 5.1 (max) | GLM 5.2 (max) |
|---|---|---|
| Blended price per 1M tokens | $20.00 | $2.15 |
| Input / output per 1M | $10.00 / $50.00 | $1.40 / $4.40 |
| Cached input per 1M | $0.250 | $0.299 |
| Price per task: chat reply | $0.019 | $0.0019 |
| Price per task: summarize a 30-page report | $0.150 | $0.019 |
| Price per task: code edit | $0.135 | $0.015 |
| Price per task: agentic coding session | $0.800 | $0.102 |
| Price per task: structured extraction | $0.030 | $0.0037 |
| Cost to run a full benchmark suite | $12.99 | – |
| Output speed | 66 tok/s | 94 tok/s |
| Time to first answer | 179.6 s | 24.1 s |
| Time to a complete answer | 187.2 s | 29.5 s |
Each model is compared at its best-ranked reasoning-effort setting. Claude Fable 5.1 (max) scores 67.0 and takes 180 s to its first answer token; Claude Fable 5.1 scores 66.4 in 3 s, Claude Fable 5.1 (xhigh) scores 64.9 in 58 s. GLM 5.2 (max) scores 60.2 and takes 24 s to its first answer token; GLM 5.2 scores 51.6 in 1 s, GLM 5.2 (no reasoning) scores 46.0 in 1 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
155 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 5.1 (max) | GLM 5.2 (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 67.0 | 60.2 |
| Agents & tools score | BenchLeader | 60.5 | 62.8 |
| Coding score | BenchLeader | 70.7 | 62.1 |
| Human preference score | BenchLeader | 69.9 | 66.5 |
| Knowledge score | BenchLeader | 72.9 | 43.6 |
| Long context score | BenchLeader | 67.6 | 64.0 |
| Maths score | BenchLeader | 72.6 | 57.2 |
| Multimodal score | BenchLeader | 67.1 | – |
| Reasoning score | BenchLeader | 70.8 | 65.9 |
| Instruction following score | BenchLeader | – | 71.7 |
| Blended price $/M | BenchLeader | $20.00 | $2.15 |
| Output speed | BenchLeader | 66 tok/s | 94 tok/s |
| Time to first answer | BenchLeader | 179.6 s | 24.1 s |
| Context window | BenchLeader | 1,000,000 tokens | 1,000,000 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | – | 91.9% |
| Humanity's Last Exam | Scale AI / CAIS | 46.5%† | – |
| SimpleBench | SimpleBench | – | 58.8%† |
| Arena Hard Prompts | Arena (LMArena) | 1523 | 1496 |
| LiveBench 2.0 Reasoning | LiveBench | 91.7%† | – |
| LiveBench 1.0 Reasoning | LiveBench | 91.7% | 78.6%† |
| GPQA Diamond (AA) | Artificial Analysis | 93.7% | 89.5% |
| Humanity's Last Exam (AA) | Artificial Analysis | 59.1% | 41.1% |
| HLE-Diamond (AA) | Artificial Analysis | 60.1% | – |
| GPQA Diamond (Vals) | Vals AI | 93.4%† | 85.6%† |
| Kagi LLM Benchmark | Kagi LLM Benchmark | – | 62.6%† |
| ARC-AGI-1 | ARC Prize | 97.5% | 77.0%† |
| ARC-AGI-2 | ARC Prize | 90.0% | 22.8%† |
| CritPt | Artificial Analysis | 29.7% | 20.9% |
| CritPt v2 hard subset (AA) | Artificial Analysis | 51.0% | – |
| MysteryMechanism | Vals AI | 47.8%† | – |
| Chess Puzzles | Epoch AI Benchmarking Hub | 48.0% | 22.0% |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 58.0% | 18.0%† |
| LMCA | Epoch AI Benchmarking Hub | 65.5%† | 45.8% |
| DTBench | Epoch AI Benchmarking Hub | 97.6%† | 93.6% |
| Coding | |||
| SWE-bench Verified (Epoch) | Epoch AI Benchmarking Hub | – | 78.7% |
| SciCode | SciCode | 63.1% | 51.2% |
| WeirdML | WeirdML | 92.9% | 70.1% |
| FrontierCode | Cognition | 50.9%† | 24.5%† |
| GSO-Bench | GSO-Bench | 88.2%† | – |
Show all 155 benchmarks
| Metric | Publisher | Claude Fable 5.1 (max) | GLM 5.2 (max) |
|---|---|---|---|
| Coding | |||
| Arena Coding | Arena (LMArena) | 1538 | 1514 |
| Arena WebDev | Arena (LMArena) | 1745 | 1606 |
| LiveBench 2.0 Coding | LiveBench | 97.7%† | – |
| LiveBench 1.0 Coding | LiveBench | 86.4% | 79.7%† |
| LiveCodeBench | Vals AI | 90.5%† | 69.5%† |
| IOI | Vals AI | 90.8%† | – |
| SWE-bench (Vals) | Vals AI | – | 82.8% |
| Code Migration | Vals AI | 54.6%† | 37.9% |
| ProgramBench | Vals AI | 7.0%† | 0.5% |
| SWE-bench Multimodal | Vals AI | 61.3%† | – |
| Vibe Code Bench 1-100 | Vals AI | 28.0%† | – |
| Vibe Code Bench v1.1 | Vals AI | 90.3%† | 64.0% |
| SWE Atlas: Codebase QnA | Scale AI SEAL | 60.0%† | 48.1%† |
| SWE Atlas: Refactoring | Scale AI SEAL | 56.7%† | 42.4%† |
| SWE Atlas: Test Writing | Scale AI SEAL | 67.0%† | 41.5%† |
| MirrorCode | Epoch AI Benchmarking Hub | 73.3%† | – |
| Surface Evolver Bench | Epoch AI Benchmarking Hub | – | 55.6%† |
| DeepSWE v1.1 | Epoch AI Benchmarking Hub | – | 43.8% |
| CursorBench | Cursor | 51.8% | – |
| ALE-Bench | Epoch AI Benchmarking Hub | 2143.2† | 1010.2 |
| FrontierSWE | Epoch AI Benchmarking Hub | 56.3% | – |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 52.0% | 1.0% |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | 91.4% | 77.9% |
| Startrise Frontend | Startrise | 77.1%† | 72.1%† |
| FrontierCode 1.1 (AA) | Artificial Analysis | 49.0% | – |
| FrontierCode 2.0 (AA) | Artificial Analysis | 31.6% | – |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 57.9% | – |
| Remote Labor Index | Scale AI / CAIS | 17.9%† | – |
| APEX-Agents | Mercor | 68.6%† | 45.2%† |
| Arena Agent | Arena (LMArena) | 13.9 | 1.7 |
| LiveBench Long Agentic | LiveBench | 77.9%† | – |
| LiveBench Browser | LiveBench | 89.8%† | – |
| LiveBench Agentic Coding | LiveBench | 66.1% | 51.8%† |
| Terminal-Bench Hard | Artificial Analysis | – | 50.8% |
| τ²-Bench Telecom (AA) | Artificial Analysis | – | 99.1% |
| Terminal-Bench 2.1 (Vals) | Vals AI | 85.0%† | 67.8% |
| MCP Atlas | Scale AI SEAL | 87.2%† | 77.8%† |
| HiL-Bench | Scale AI SEAL | 61.5%† | 43.7%† |
| τ³-bench Banking | τ²-bench | – | 37.1%† |
| GDPval-AA v2.1, normalised score | Artificial Analysis | 62.7% | – |
| GDPval-AA v2.1 | Artificial Analysis | 1764 | – |
| τ³-Banking (AA) | Artificial Analysis | 47.2% | 34.6% |
| ITBench SRE (AA) | Artificial Analysis | 49.5% | 42.7% |
| Analyst Agent (AA) | Artificial Analysis | 57.5% | – |
| APEX-Agents (AA) | Artificial Analysis | – | 33.7% |
| CUA-bench | Vals AI | 13.2% | – |
| CyberBench | Vals AI | 70.4%† | – |
| Finance Agent v2 | Vals AI | 58.9%† | 49.7%† |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 6.7%† | 7.1% |
| Legal Research Bench | Vals AI | 55.3%† | 31.3% |
| Robo-bench | Vals AI | 5.8% | – |
| SkillsBench | Vals AI | 61.5%† | 45.1% |
| SREBench | Vals AI | 22.9%† | 0.0% |
| Tax Agent Bench | Vals AI | 49.2%† | – |
| Terminal-Bench 4.0 (Vals) | Vals AI | 58.1%† | – |
| Terminal-Bench Science | Vals AI | 40.0%† | – |
| Time Horizon Index: KSP | Vals AI | 63.3%† | – |
| Arena Search | Arena (LMArena) | 1233† | – |
| PostTrainBench | Epoch AI Benchmarking Hub | – | 31.7% |
| GBAEval | Epoch AI Benchmarking Hub | – | 0.0%† |
| Vending-Bench 2 | Andon Labs | 5421.6† | 8313.8† |
| AutomationBench | Artificial Analysis | 59.4% | 28.4% |
| GDP.pdf (AA) | Artificial Analysis | 26.2% | 10.4% |
| Harvey LAB-AA v1.1 | Harvey | 6.4% | – |
| EnterpriseOps-Gym | Artificial Analysis | – | 42.7% |
| AA-Briefcase v1.1 | Artificial Analysis | 1669 | 1227 |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 43.3% | – |
| CWE-Bench (AA) | Artificial Analysis | 50.8% | – |
| DeepSec-Bench (AA) | Artificial Analysis | 23.5% | – |
| CyberGym end-to-end (AA) | Artificial Analysis | 0.8% | – |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 90.2% | 59.2% |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 87.8% | 29.3% |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 100.0% | 86.4% |
| ProofBench | Vals AI | 100.0% | 35.0% |
| LiveBench Mathematics | LiveBench | 97.0% | 89.8%† |
| AIME 2026 | MathArena | – | 90.0%† |
| HMMT February 2026 | MathArena | – | 92.4%† |
| MathArena Apex | MathArena | – | 19.8%† |
| Arena Maths | Arena (LMArena) | 1529 | 1488 |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 70.8% | 34.2% |
| LiveBench 2.0 Data Analysis | LiveBench | 80.3%† | – |
| LiveBench Research | LiveBench | 82.0%† | – |
| LiveBench 1.0 Data Analysis | LiveBench | 80.3% | 73.7%† |
| AA-Omniscience v1.1 | Artificial Analysis | 46.3 | – |
| MMLU-Pro | Vals AI | 92.4%† | 86.7%† |
| LegalBench | Vals AI | 88.5%† | 84.1%† |
| CorpFin | Vals AI | – | 66.1%† |
| TaxEval | Vals AI | 76.0%† | 73.3%† |
| PRBench Finance | Scale AI SEAL | 50.8%† | – |
| PRBench Legal | Scale AI SEAL | 51.6%† | – |
| Excel Modeling Benchmark | Vals AI | 76.7%† | 61.5%† |
| Excel Modeling Benchmark v1.1 | Vals AI | 76.7%† | – |
| MedCode | Vals AI | 53.5%† | 40.8%† |
| MedScribe | Vals AI | 91.3%† | 83.5%† |
| Public Benefits Bench v1.1 | Vals AI | 74.9%† | – |
| DrugDiscoveryBench | Scale AI SEAL | – | 36.2%† |
| EBR-bench | Epoch AI Benchmarking Hub | 57.1% | 9.5% |
| GDP.pdf | Epoch AI Benchmarking Hub | 27.6% | – |
| AA-Omniscience v1.1: accuracy | Artificial Analysis | 68.4% | – |
| AA-Omniscience v1.1: non-hallucination | Artificial Analysis | 30.0% | – |
| HealthBench Professional (AA) | OpenAI | 57.8% | – |
| Instruction following | |||
| LiveBench Language | LiveBench | 89.5% | 76.2%† |
| LiveBench Instruction Following | LiveBench | 73.0% | 62.3%† |
| IFBench | Artificial Analysis | – | 73.3% |
| Arena Instruction Following | Arena (LMArena) | 1501 | 1469 |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1503 | 1475 |
| EQ-Bench 4 | EQ-Bench | – | 1208† |
| Arena Creative Writing | Arena (LMArena) | 1487 | 1453 |
| Arena Multi-turn | Arena (LMArena) | 1488 | 1475 |
| Arena Longer Queries | Arena (LMArena) | 1511 | 1486 |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1320 | – |
| LiveBench Design | LiveBench | 83.4%† | – |
| MMMU-Pro (Vals) | Vals AI | 90.6%† | – |
| MortgageTax | Vals AI | 70.8%† | – |
| Blueprint-Bench 2 | Epoch AI Benchmarking Hub | 41.9%† | – |
| Code2Video-AA | Artificial Analysis | 1325 | – |
| AA-3D | Artificial Analysis | 1135 | – |
| Long context | |||
| AA-LCR v1.1 | Artificial Analysis | 85.3% | 78.3% |
| Arena Document | Arena (LMArena) | 1493 | – |
| MLCR | Artificial Analysis | 15.6% | 12.8% |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 166.5† | 151.9† |
| LiveBench 2.0 | LiveBench | 85.7%† | – |
| LiveBench 1.0 | LiveBench | 83.4% | 73.2%† |
| AA Intelligence Index v5.0 | Artificial Analysis | 49.0 | – |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 53.4 | 33.7 |
| AA Progress Index v1 | Artificial Analysis | 340.8 | 302.5 |
| Vals RSI Index | Vals AI | 36.1% | – |
| AA Cyber Index | Artificial Analysis | 25.0 | – |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | 13.7%† | – |
| Metadata | |||
| AA Openness Index | Artificial Analysis | – | 44.4 |
Data as of 2026-10-29. Best configuration of each model; every score links to its source on the model pages.
What changed
- GLM 5.2 (max): cached input price moved from $0.26/M to $0.30/M (15% up).
- Claude Fable 5.1 (max): BenchLeader Index 67.9 → 67.1.
- GLM 5.2 (max): BenchLeader Index 61.3 → 60.2.
- Claude Fable 5.1 (max): 5 new results (AA Intelligence Index v5.0, AA Progress Index v1, HLE-Diamond (AA)…); 3 score revisions; cost per task moved from $7.63/M to $13.04/M (71% up).
- GLM 5.2 (max): 1 new result (AA Progress Index v1); cached input price moved from $0.30/M to $0.26/M (13% down).
- GLM 5.2 (max): BenchLeader Index 61.8 → 61.3.
- GLM 5.2 (max): cached input price moved from $0.26/M to $0.30/M (15% up).
- GLM 5.2 (max): cost per task moved from $1.47/M to $1.28/M (13% down); cached input price moved from $0.30/M to $0.26/M (13% down).
- GLM 5.2 (max): 1 new result (AA-Briefcase v1.1); cached input price moved from $0.26/M to $0.30/M (15% up).
- GLM 5.2 (max): cached input price moved from $0.30/M to $0.26/M (13% down).
Related comparisons
- Claude Fable 5.1 vs Claude Opus 5.5
- Claude Fable 5.1 vs GPT-6 Astra
- Claude Fable 5.1 vs GPT-6.1 Sol
- GLM 5.2 vs Claude Opus 5.5
- GLM 5.2 vs GPT-6 Astra
- GLM 5.2 vs GPT-6.1 Sol
- Claude Opus 5 vs GLM 5.2
- Claude Fable 5.1 vs GLM-5
Rankings: Best LLM overall · Best LLM for coding · Best LLM for agents · Best cheap LLMs
Claude Fable 5.1 vs GLM 5.2: questions
- Is Claude Fable 5.1 better than GLM 5.2?
- Claude Fable 5.1 (max) leads on quality: 67.0 vs 60.2. The BenchLeader Index combines every independent quality benchmark; Claude Fable 5.1 (max) is ahead overall as of 29 Oct 2026, but check the category scores for your use.
- Claude Fable 5.1 vs GLM 5.2: which is cheaper, and will that change?
- GLM 5.2 is cheaper today: $2.15 against $20.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
- Is Claude Fable 5.1 or GLM 5.2 better for coding?
- Claude Fable 5.1 scores higher in coding (71 vs 62 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1745 for Claude Fable 5.1 against 1606 for GLM 5.2.
- Which is faster, Claude Fable 5.1 or GLM 5.2?
- GLM 5.2 streams faster (94 vs 66 output tokens per second, Artificial Analysis 7-day median).
- Is Claude Fable 5.1 or GLM 5.2 better for agents and tool use?
- GLM 5.2 scores higher in agentic tasks (63 vs 61 on the category index, where 50 is average). On τ³-Banking (AA), the top shared agents & tools benchmark, it is 47.2% for Claude Fable 5.1 against 34.6% for GLM 5.2.
More questions (4)
- Which is better for long documents?
- Claude Fable 5.1 scores higher on long-context benchmarks (68 vs 64). Both accept 1,000,000 tokens of context.
- Which has lower latency?
- GLM 5.2 answers first: 24.1 s against 179.6 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 5.1 vs GLM 5.2?
- Across the 31 benchmarks both have, Claude Fable 5.1 leads 31, GLM 5.2 leads 0. Every overall index that rates both puts Claude Fable 5.1 ahead.
- When was Claude Fable 5.1 released?
- Claude Fable 5.1 was released on 1 Sept 2026.