Claude Fable 5
Anthropic · released Jun 9, 2026
Claude Fable 5 is a Mythos-class model from Anthropic, built for autonomous knowledge work and coding. It supports text, image, and file inputs with text output, with reasoning support and...
Specification
- Context window
- 1M
- Max output
- 128K
- Knowledge cutoff
- Not stated
- Parameters
- Undisclosed
- Licence
- Proprietary
- Serving providers
- 4
- Moderated
- Yes
- Uptime
- 100.0%
Intelligence
62.1
100th percentile
Coding
76.5
Coding Index
Agentic
56.6
Agentic Index
Output speed
54 t/s
Median across providers
Latency
3.84s
Time to first token
Cost per task
$4.50
Estimated
Benchmarks
Where the score comes from
The Intelligence Index is a composite. These are the underlying evaluations this model was actually measured on.
Evaluation scores
Percentage correct · higher is better
- τ²-bench (Telecom)98.5%
- GPQA Diamond92.6%
- AA-LCR (long context)76.7%
- IFBench63.5%
- Terminal-Bench Hard62.9%
- SciCode60.2%
- Humanity's Last Exam55.5%
An evaluation missing from this list was not run for this model — it is not a zero.
View as table
| Evaluation | Score |
|---|---|
| τ²-bench (Telecom) | 98.5% |
| GPQA Diamond | 92.6% |
| AA-LCR (long context) | 76.7% |
| IFBench | 63.5% |
| Terminal-Bench Hard | 62.9% |
| SciCode | 60.2% |
| Humanity's Last Exam | 55.5% |
Against its peers
Intelligence Index · this model highlighted, nearest peers in grey
- Claude Opus 5Anthropic63.1
- Claude Fable 5Anthropic62.1
- GPT-5.6 SolOpenAI60.9
- Kimi K3Moonshot AI59.7
- Qwen3.8 MaxQwen58.1
- Claude Opus 4.8Anthropic57.3
- Muse Spark 1.2Meta56.8
- GPT-5.6 TerraOpenAI56.6
Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.
View as table
| Model | Intelligence |
|---|---|
| Claude Opus 5 | 63.1 |
| Claude Fable 5 | 62.1 |
| GPT-5.6 Sol | 60.9 |
| Kimi K3 | 59.7 |
| Qwen3.8 Max | 58.1 |
| Claude Opus 4.8 | 57.3 |
| Muse Spark 1.2 | 56.8 |
| GPT-5.6 Terra | 56.6 |
Percentile among all indexed models
Pricing
What it costs to run
List prices per million tokens, plus what one representative task works out to.
List price
- Input / 1M tokens
- $10
- Output / 1M tokens
- $50
- Cached input / 1M
- $1
- Blended 3:1
- $20
One task, estimated
$4.50
- Input tokens
- 50,000
- Output tokens
- 80,000
- Profile
- Reasoning
Estimated from list pricing: 50K input tokens plus 80K output tokens for reasoning models (25K for non-reasoning).
Serving providers
Speed and latency figures are medians across these providers, so a widely-served model reports a blend rather than any single endpoint.
Arena
Head-to-head generation quality
Elo from pairwise judgements, broken out by the kind of thing the model was asked to build.
- Overall Elo
- 1,397
- Win rate
- 65.4%
- Strongest at
- Game development
- Tournaments
- 1,157
Elo by category
Dot position on a 1,250–1,400 scale · Elo has no meaningful zero
- 1,397
- 1,376
- 1,355
- 1,352
- 1,344
- 1,327
- 1,295
- 1,254
Agent categories (full-stack apps, mobile apps) are only scored for models tested in agent harnesses.
View as table
| Category | Elo | Win rate |
|---|---|---|
| Game development | 1397 | 65.4% |
| 3D scenes | 1376 | 62.9% |
| UI components | 1355 | 59.1% |
| SVG | 1352 | 66.1% |
| Data visualisation | 1344 | 59.3% |
| Websites | 1327 | 59.8% |
| Full-stack apps | 1295 | 63.7% |
| Mobile apps | 1254 | 57.5% |