Claude Fable 5.1 vs Claude Haiku 5.5
Compare Claude Fable 5.1 and Claude Haiku 5.5 side-by-side.
Compare Claude Fable 5.1 vs Claude Haiku 5.5 live
Run the same image across every model that supports a task and compare their outputs side-by-side.
These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.
Models in this comparison
Claude Fable 5.1 vs Claude Haiku 5.5 on Vision Evals
Claude Fable 5.1 scores higher on 5 of the six Vision Evals tasks.
The widest gap is Identification, where Claude Fable 5.1 leads 97.9% to 83.3%.
Overall, Claude Fable 5.1 averages 81.3% (#12 of 61) against 77.2% (#20 of 61) for Claude Haiku 5.5.
Claude Haiku 5.5 is cheaper ($0.0005 vs $0.035 per sample), while Claude Fable 5.1 is faster (8.3s vs 13.2s per sample).
Claude Fable 5.1 vs Claude Haiku 5.5 Comparison Table
Evals updated October 8, 2026Pricing updated October 8, 2026
| Property | Claude Fable 5.1 | Claude Haiku 5.5 |
|---|---|---|
| Organization | Anthropic | Anthropic |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Sep 2026 | Oct 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | Unknown | undisclosed |
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $10.00 | $0.100 |
| Output $/1M | $50.00 | $0.500 |
| Vision Tasks | ||
| Captioning | Demo | Supported |
| Chart Question Answering | Supported | Supported |
| Classification | Demo | Supported |
| Document Question Answering | Supported | Supported |
| Image Tagging | Supported | Supported |
| Multi-Label Classification | Supported | Supported |
| Object Detection | Demo | Supported |
| OCR | Demo | Supported |
| Vision Language | Supported | Supported |
| Visual Question Answering | Demo | Supported |
| Model Features | ||
| Foundation Vision | Supported | Supported |
| LLMs with Vision Capabilities | Supported | Supported |
| Multimodal Vision | Supported | Supported |
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 81.3% | 77.2% |
| Avg cost / sample | $0.035 | $0.0005 |
| Avg speed / sample | 8.28s | 13.23s |
| By task | ||
| Object Detection (low) | 61.4% ±0.5, Mean of 3 runs, range 61.0 to 62.0 | 65.8% ±0.6, Mean of 3 runs, range 65.1 to 66.2 |
| Object Detection (high) | 65.0% ±0.4, Mean of 3 runs, range 64.6 to 65.3 | 68.2% ±1.0, Mean of 3 runs, range 67.2 to 69.2 |
| Counting (low) | 69.4% ±2.7, Mean of 3 runs, range 66.2 to 71.6 | 68.9% ±4.7, Mean of 3 runs, range 64.9 to 74.3 |
| Counting (high) | 73.0% ±4.7, Mean of 3 runs, range 67.6 to 77.0 | 73.0% ±1.3, Mean of 3 runs, range 71.6 to 74.3 |
| Identification (low) | 97.9% ±1.6, Mean of 3 runs, range 96.9 to 100.0 | 83.3% ±3.1, Mean of 3 runs, range 81.3 to 87.5 |
| Identification (high) | 96.9% ±3.1, Mean of 3 runs, range 93.8 to 100.0 | 86.5% ±1.6, Mean of 3 runs, range 84.4 to 87.5 |
| OCR (low) | 94.0% ±0.4, Mean of 3 runs, range 93.6 to 94.4 | 90.1% ±1.1, Mean of 3 runs, range 88.8 to 91.0 |
| OCR (high) | 93.6% ±0.2, Mean of 3 runs, range 93.5 to 93.9 | 88.0% ±1.3, Mean of 3 runs, range 87.0 to 89.6 |
| Data Extraction (low) | 93.1% ±0.5, Mean of 3 runs, range 92.8 to 93.8 | 85.9% ±1.5, Mean of 3 runs, range 84.5 to 87.6 |
| Data Extraction (high) | 93.5% ±0.5, Mean of 3 runs, range 92.8 to 93.8 | 87.3% ±0.5, Mean of 3 runs, range 86.6 to 87.6 |
| Reasoning (low) | 72.0% ±1.3, Mean of 3 runs, range 70.9 to 73.5 | 68.9% ±2.0, Mean of 3 runs, range 66.9 to 70.9 |
| Reasoning (high) | 73.1% ±2.0, Mean of 3 runs, range 71.5 to 75.5 | 74.8% ±2.6, Mean of 3 runs, range 72.2 to 77.5 |
Claude Fable 5.1 vs Claude Haiku 5.5: Overview
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.
Claude Haiku 5.5 is a proprietary multimodal language model from Anthropic and the smallest member of the Claude 5.5 family, released on October 7, 2026 after Claude Opus 5.5 and Claude Sonnet 5.5. It accepts text and image input and returns text, with a 1M token context window and up to 128K output tokens per request. It is the first Haiku-class model with an adjustable effort parameter: adaptive thinking is on by default and the model decides how much to reason, steered by effort levels from low to max with medium as the default. Its training data cutoff is June 2026. Pricing starts at $0.10 per million input tokens and $0.50 per million output tokens for prompts up to 100K tokens, which Anthropic reports is about 90% lower than Claude Haiku 4.5 for requests in that range.
Anthropic positions Haiku 5.5 for high-volume, latency-sensitive work such as classification, extraction, routing, summarization, and subagent tasks, and describes it as its fastest model to date at standard speed. On visual and agentic evaluations reported at launch, it scores 46.4% on Chartography, a chart reading benchmark, compared with 6.4% for Haiku 4.5 and 61.6% for Sonnet 5.5, and 72.4% on the offline subset of OSWorld 2.1, a screenshot driven computer use benchmark, compared with 15.7% for Haiku 4.5. It uses the same tokenizer as Claude Opus 4.7 and later models, so the same text counts as roughly 30% more tokens than on Haiku 4.5.
Frequently Asked Questions
On Roboflow's Vision Evals, Claude Fable 5.1 performed better. It scores higher on 5 of the six vision tasks and averages 81.3% (#12 of 61) against 77.2% (#20 of 61) for Claude Haiku 5.5. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
Yes. On the Vision Evals Identification benchmark at low effort, Claude Fable 5.1 leads with 97.9% against 83.3%. This is the widest gap between the two models across the benchmark's tasks.
Claude Haiku 5.5 is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0005 per sample against $0.035. Claude Fable 5.1 is priced at $10.00 per 1M input tokens and $50.00 per 1M output; Claude Haiku 5.5 is priced at $0.10 per 1M input tokens and $0.50 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 13.2s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.