Updated daily at 05:00 UTC
Vision-language
Claude Fable 5
- Released
- 9 Jun 2026
- Status
- Legacy
- Context
- 1M
- Max output
- 128K
- Input per 1M tokens
- $10.00
- Output per 1M tokens
- $50.00
- Open weights
- No
- License
- proprietary
- Parameters
- —
- Knowledge cutoff
- Jan 2026
- Reasoning
- Yes
- Modalities
- text, image → text
Category scores
Out of 100, from independent and third-party results only, by method category-2026-09-29.1.
| Category | Score | Rank | Coverage |
|---|---|---|---|
| Knowledge & reasoning | 56.9 | 11 | 4 of 4 |
| Coding & software engineering | 62.4 | 1 | 3 of 5 |
| Vision & multimodal understanding | 8.3 | Not ranked | 1 of 3 |
| Factuality & hallucination | 70.7 | 5 | 1 of 1 |
| Human preference | 54.3 | 17 | 5 of 5 |
Benchmark results
Every result we hold for this model, with who ran it and where it was published.
Knowledge & reasoning
| Benchmark | Metric | Value | Provenance | Setting | Evaluated | Source |
|---|---|---|---|---|---|---|
| Chess Puzzles | Puzzles solved | 41.0% | Independent | max | 9 Jun 2026 | Epoch AI |
| Chess Puzzles | Puzzles solved | 41.0% | Independent | high | 6 Aug 2026 | Epoch AI |
| Chess Puzzles | Puzzles solved | 28.0% | Independent | low | 6 Aug 2026 | Epoch AI |
| DTBench (Decision Theory Benchmark) | Accuracy (capability questions) | 98.4% | Third party | max | — | https://conceptualreasoning.ai/dtbench via Epoch AI |
| DTBench (Decision Theory Benchmark) | Accuracy (capability questions) | 97.3% | Third party | xhigh | — | https://conceptualreasoning.ai/dtbench via Epoch AI |
| DTBench (Decision Theory Benchmark) | Accuracy (capability questions) | 96.5% | Third party | high | — | https://conceptualreasoning.ai/dtbench via Epoch AI |
| DTBench (Decision Theory Benchmark) | Accuracy (capability questions) | 95.7% | Third party | medium | — | https://conceptualreasoning.ai/dtbench via Epoch AI |
| DTBench (Decision Theory Benchmark) | Accuracy (capability questions) | 91.5% | Third party | low | — | https://conceptualreasoning.ai/dtbench via Epoch AI |
| Earthborne Rangers (EBR-bench) | Objectives reached | 39.5% | Independent | max | 17 Jul 2026 | Epoch AI |
| LMCA (Language Model Conceptual Argumentation) | Correlation with expert ratings (Pearson r) | 0.6115 | Third party | high | — | https://conceptualreasoning.ai/lmca via Epoch AI |
| LMCA (Language Model Conceptual Argumentation) | Correlation with expert ratings (Pearson r) | 0.6102 | Third party | xhigh | — | https://conceptualreasoning.ai/lmca via Epoch AI |
| LMCA (Language Model Conceptual Argumentation) | Correlation with expert ratings (Pearson r) | 0.6034 | Third party | max | — | https://conceptualreasoning.ai/lmca via Epoch AI |
| LMCA (Language Model Conceptual Argumentation) | Correlation with expert ratings (Pearson r) | 0.6032 | Third party | medium | — | https://conceptualreasoning.ai/lmca via Epoch AI |
| LMCA (Language Model Conceptual Argumentation) | Correlation with expert ratings (Pearson r) | 0.5959 | Third party | low | — | https://conceptualreasoning.ai/lmca via Epoch AI |
| Mystery Game Puzzles | Puzzles solved | 52.0% | Independent | max | 31 Jul 2026 | Epoch AI |
| SimpleBench | Score (AVG@5) | 81.9% | Third party | max | — | SimpleBench Leaderboard via Epoch AI |
Scientific reasoning
| Benchmark | Metric | Value | Provenance | Setting | Evaluated | Source |
|---|---|---|---|---|---|---|
| GPQA Diamond | Accuracy | 85.9% | Independent | max | 6 Aug 2026 | Epoch AI |
| GPQA Diamond | Accuracy | 83.3% | Independent | high | 6 Aug 2026 | Epoch AI |
| GPQA Diamond | Accuracy | 78.8% | Independent | low | 6 Aug 2026 | Epoch AI |
| Surface Evolver Bench | Mean score (partial credit) | 95.0% | Third party | high | — | https://yhenon.github.io/surface-evolver-llm-eval/ via Epoch AI |
Mathematics
| Benchmark | Metric | Value | Provenance | Setting | Evaluated | Source |
|---|---|---|---|---|---|---|
| FrontierMath Tier 4 | Accuracy | 90.2% | Independent | max | 9 Jun 2026 | Epoch AI |
| FrontierMath Tiers 1-3 | Accuracy | 87.0% | Independent | max | 9 Jun 2026 | Epoch AI |
| OTIS Mock AIME 2024-2025 | Accuracy | 100.0% | Independent | high | 6 Aug 2026 | Epoch AI |
| OTIS Mock AIME 2024-2025 | Accuracy | 99.7% | Independent | max | 10 Jun 2026 | Epoch AI |
| OTIS Mock AIME 2024-2025 | Accuracy | 97.8% | Independent | low | 6 Aug 2026 | Epoch AI |
Coding & software engineering
| Benchmark | Metric | Value | Provenance | Setting | Evaluated | Source |
|---|---|---|---|---|---|---|
| DeepSWE | Pass@1 | 69.9% | Third party | xhigh | — | https://deepswe.datacurve.ai/ via Epoch AI |
| DeepSWE | Pass@1 | 69.7% | Third party | max | — | https://deepswe.datacurve.ai/ via Epoch AI |
| DeepSWE | Pass@1 | 68.6% | Third party | high | — | https://deepswe.datacurve.ai/ via Epoch AI |
| DeepSWE | Pass@1 | 65.4% | Third party | medium | — | https://deepswe.datacurve.ai/ via Epoch AI |
| DeepSWE | Pass@1 | 59.6% | Third party | low | — | https://deepswe.datacurve.ai/ via Epoch AI |
| FrontierCode | Main score (Mean@5) | 53.5% | Third party | unknown | — | https://cognition.com/frontiercode via Epoch AI |
| MirrorCode | Score | 63.9% | Independent | high | 10 Aug 2026 | Epoch AI |
| PostTrainBench | Average score | 41.8% | Source not stated | max | — | Epoch AI via Epoch AI |
| WeirdML (v2) | Average accuracy | 91.9% | Third party | max | — | https://htihle.github.io/weirdml.html via Epoch AI |
| WeirdML (v2) | Average accuracy | 87.8% | Third party | high | — | WeirdML Leaderboard via Epoch AI |
Professional knowledge work
| Benchmark | Metric | Value | Provenance | Setting | Evaluated | Source |
|---|---|---|---|---|---|---|
| APEX-Agents | Pass@1 (all rubric criteria met) | 63.6% | Source not stated | — | — | Epoch AI via Epoch AI |
Vision & multimodal understanding
| Benchmark | Metric | Value | Provenance | Setting | Evaluated | Source |
|---|---|---|---|---|---|---|
| Furniture Assembly | Score | 35.8% | Independent | max | 10 Sep 2026 | Epoch AI |
Factuality & hallucination
| Benchmark | Metric | Value | Provenance | Setting | Evaluated | Source |
|---|---|---|---|---|---|---|
| SimpleQA Verified | Accuracy (% correct) | 70.7% | Independent | xhigh | 10 Aug 2026 | Epoch AI |
Human preference
| Benchmark | Metric | Value | Provenance | Setting | Evaluated | Source |
|---|---|---|---|---|---|---|
| Code Arena: WebDev (arena.ai) | Arena score (Elo scale) | 1627 | Independent | high | 25 Sep 2026 | Arena |
| Code Arena: WebDev (arena.ai) | Votes | 13086 | Independent | high | 25 Sep 2026 | Arena |
| Document Arena (arena.ai) | Arena score (Elo scale) | 1499 | Independent | — | 13 Sep 2026 | Arena |
| Document Arena (arena.ai) | Votes | 8497 | Independent | — | 13 Sep 2026 | Arena |
| Search Arena (arena.ai) | Arena score (Elo scale) | 1229 | Independent | — | 24 Aug 2026 | Arena |
| Search Arena (arena.ai) | Votes | 41795 | Independent | — | 24 Aug 2026 | Arena |
| Text Arena (arena.ai) | Arena score (Elo scale) | 1504 | Independent | high | 25 Sep 2026 | Arena |
| Text Arena (arena.ai) | Votes | 36462 | Independent | high | 25 Sep 2026 | Arena |
| Vision Arena (arena.ai) | Arena score (Elo scale) | 1310 | Independent | high | 28 Sep 2026 | Arena |
| Vision Arena (arena.ai) | Votes | 13483 | Independent | high | 28 Sep 2026 | Arena |
Other Claude Fable versions
- Claude Fable 5.11 Sep 2026
Sources
- https://platform.claude.com/docs/en/models/fable-5/overview
- https://platform.claude.com/docs/en/models/fable-5/introducing-claude-fable-5-and-claude-mythos-5
- https://www.anthropic.com/news/claude-fable-5-mythos-5
- https://www.anthropic.com/news/redeploying-fable-5
- https://platform.claude.com/docs/en/about-claude/model-deprecations