Claude Fable 5 vs Claude Fable 5.1
Compare Claude Fable 5 and Claude Fable 5.1 side-by-side. See how these vision models stack up in Image Captioning, Classification, OCR, Open Prompt, and Object Detection.
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Models in this comparison
Claude Fable 5 vs Claude Fable 5.1 on Vision Evals
Claude Fable 5.1 scores higher on 4 of the six Vision Evals tasks.
The widest gap is Counting, where Claude Fable 5.1 leads 69.4% to 63.5%.
Overall, Claude Fable 5 averages 78.7% (#10 of 36) against 81.3% (#7 of 36) for Claude Fable 5.1.
Claude Fable 5 is cheaper ($0.034 vs $0.035 per sample), while Claude Fable 5.1 is faster (8.3s vs 8.7s per sample).
Claude Fable 5 vs Claude Fable 5.1 Comparison Table
Evals updated September 2, 2026Pricing updated September 2, 2026
| Property | Claude Fable 5 | Claude Fable 5.1 |
|---|---|---|
| Organization | Anthropic | Anthropic |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Jun 2026 | Sep 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $10.00 | $10.00 |
| Output $/1M | $50.00 | $50.00 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Chart Question Answering | ||
| Classification | Demo | Demo |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 78.7% | 81.3% |
| Avg cost / sample | $0.034 | $0.035 |
| Avg speed / sample | 8.71s | 8.28s |
| By task | ||
| Object Detection (low) | 56.4% | 61.4% ±0.5, Mean of 3 runs, range 61.0 to 62.0 |
| Object Detection (high) | – | 65.0% ±0.4, Mean of 3 runs, range 64.6 to 65.3 |
| Counting (low) | 63.5% | 69.4% ±2.7, Mean of 3 runs, range 66.2 to 71.6 |
| Counting (high) | – | 73.0% ±4.7, Mean of 3 runs, range 67.6 to 77.0 |
| Identification (low) | 100.0% | 97.9% ±1.6, Mean of 3 runs, range 96.9 to 100.0 |
| Identification (high) | – | 96.9% ±3.1, Mean of 3 runs, range 93.8 to 100.0 |
| OCR (low) | 94.0% | 94.0% ±0.4, Mean of 3 runs, range 93.6 to 94.4 |
| OCR (high) | – | 93.6% ±0.2, Mean of 3 runs, range 93.5 to 93.9 |
| Data Extraction (low) | 91.8% | 93.1% ±0.5, Mean of 3 runs, range 92.8 to 93.8 |
| Data Extraction (high) | – | 93.5% ±0.5, Mean of 3 runs, range 92.8 to 93.8 |
| Reasoning (low) | 66.2% | 72.0% ±1.3, Mean of 3 runs, range 70.9 to 73.5 |
| Reasoning (high) | 66.2% | 73.1% ±2.0, Mean of 3 runs, range 71.5 to 75.5 |
Claude Fable 5 vs Claude Fable 5.1: Overview
Claude Fable 5 is Anthropic's first generally available Mythos-class large language model, released on June 9, 2026. It is built for long-horizon, asynchronous, and agentic tasks that prior Claude generations could not sustain, including multi-day autonomous coding sessions, complex knowledge work, and document-heavy analysis. The model supports a 1 million token context window with up to 128,000 output tokens per request and uses adaptive thinking as its sole reasoning mode, where the effort level is adjustable but raw chain-of-thought is never returned. Vision capabilities allow the model to parse diagrams, charts, and tables embedded in files and PDFs, and to use visual feedback to evaluate its own coding outputs against design goals. On benchmarks such as SWE-Bench Pro, the model scores 80.3% compared to 69.2% for Claude Opus 4.8, and it leads on CursorBench 3.1 for autonomous coding workflows.
Claude Fable 5 shares the same underlying model weights as Claude Mythos 5, but is deployed with safety classifiers that automatically reroute queries in high-risk domains — including cybersecurity, biology, and chemistry — to Claude Opus 4.8. These classifiers trigger in fewer than 5% of sessions on average. As a designated Covered Model, all traffic is subject to mandatory 30-day data retention to support safety monitoring. The model is available via the Claude API, Amazon Bedrock, Vertex AI, and Microsoft Foundry. Anthropic has not publicly disclosed parameter count, architecture details, or training data composition for this model.
Claude Fable 5.1 is a proprietary multimodal model from Anthropic in the Mythos-class tier of the Claude 5 family, positioned above Claude Opus for demanding reasoning and long-horizon agentic work. It accepts text and images as input and returns text, with a one million token context window and a maximum output of 128 thousand tokens. Adaptive thinking is always on, and an effort parameter controls how much reasoning the model applies to a given request. Anthropic reports a reliable knowledge and training data cutoff of June 2026. Claude Fable 5.1 and Claude Mythos 5.1 share the same underlying model; the difference between them is the set of safety classifiers applied to dual-use cybersecurity and biology requests.
On the vision side, Anthropic documents improvements in reading dense charts, financial filings, and tables nested inside PDF documents, which extends the model toward document understanding, chart question answering, and spreadsheet and slide work. Reported evaluations cover agentic scientific research on Terminal-Bench-Science 0.1, agentic coding on Terminal-Bench 4.0, computer use on OSWorld 2.0, and multidisciplinary reasoning on Humanity's Last Exam. Model weights are not published.
Frequently Asked Questions
On Roboflow's Vision Evals, Claude Fable 5.1 performed better. It scores higher on 4 of the six vision tasks and averages 81.3% (#7 of 36) against 78.7% (#10 of 36) for Claude Fable 5. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
No. On the Vision Evals Counting benchmark at low effort, Claude Fable 5.1 leads with 69.4% against 63.5%. This is the widest gap between the two models across the benchmark's tasks.
Claude Fable 5 is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.034 per sample against $0.035. Claude Fable 5 is priced at $10.00 per 1M input tokens and $50.00 per 1M output; Claude Fable 5.1 is priced at $10.00 per 1M input tokens and $50.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Claude Fable 5.1 is faster. Across Roboflow's Vision Evals it averaged 8.3s per inference against 8.7s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.
Yes. The comparison demo on this page runs both models on the same image side by side for image captioning and image classification in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.