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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 5.1Claude Haiku 5.5

Claude Fable 5.1 vs Claude Haiku 5.5 Comparison Table

Evals updated October 8, 2026Pricing updated October 8, 2026

PropertyClaude Fable 5.1Claude Haiku 5.5
OrganizationAnthropicAnthropic
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateSep 2026Oct 2026
Context Window1.0M1.0M
ParametersUnknownundisclosed
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$10.00$0.100
Output $/1M$50.00$0.500
Vision Tasks
CaptioningDemoSupported
Chart Question AnsweringSupportedSupported
ClassificationDemoSupported
Document Question AnsweringSupportedSupported
Image TaggingSupportedSupported
Multi-Label ClassificationSupportedSupported
Object DetectionDemoSupported
OCRDemoSupported
Vision LanguageSupportedSupported
Visual Question AnsweringDemoSupported
Model Features
Foundation VisionSupportedSupported
LLMs with Vision CapabilitiesSupportedSupported
Multimodal VisionSupportedSupported
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 / sample8.28s13.23s
By task
Object Detection (low)
61.4%
±0.5, Mean of 3 runs, range 61.0 to 62.0
$0.060
65.8%
±0.6, Mean of 3 runs, range 65.1 to 66.2
$0.0006
Object Detection (high)
65.0%
±0.4, Mean of 3 runs, range 64.6 to 65.3
$0.078
68.2%
±1.0, Mean of 3 runs, range 67.2 to 69.2
$0.0010
Counting (low)
69.4%
±2.7, Mean of 3 runs, range 66.2 to 71.6
$0.019
68.9%
±4.7, Mean of 3 runs, range 64.9 to 74.3
$0.0003
Counting (high)
73.0%
±4.7, Mean of 3 runs, range 67.6 to 77.0
$0.023
73.0%
±1.3, Mean of 3 runs, range 71.6 to 74.3
$0.0004
Identification (low)
97.9%
±1.6, Mean of 3 runs, range 96.9 to 100.0
$0.013
83.3%
±3.1, Mean of 3 runs, range 81.3 to 87.5
$0.0002
Identification (high)
96.9%
±3.1, Mean of 3 runs, range 93.8 to 100.0
$0.014
86.5%
±1.6, Mean of 3 runs, range 84.4 to 87.5
$0.0003
OCR (low)
94.0%
±0.4, Mean of 3 runs, range 93.6 to 94.4
$0.039
90.1%
±1.1, Mean of 3 runs, range 88.8 to 91.0
$0.0006
OCR (high)
93.6%
±0.2, Mean of 3 runs, range 93.5 to 93.9
$0.039
88.0%
±1.3, Mean of 3 runs, range 87.0 to 89.6
$0.0009
Data Extraction (low)
93.1%
±0.5, Mean of 3 runs, range 92.8 to 93.8
$0.016
85.9%
±1.5, Mean of 3 runs, range 84.5 to 87.6
$0.0002
Data Extraction (high)
93.5%
±0.5, Mean of 3 runs, range 92.8 to 93.8
$0.016
87.3%
±0.5, Mean of 3 runs, range 86.6 to 87.6
$0.0002
Reasoning (low)
72.0%
±1.3, Mean of 3 runs, range 70.9 to 73.5
$0.019
68.9%
±2.0, Mean of 3 runs, range 66.9 to 70.9
$0.0004
Reasoning (high)
73.1%
±2.0, Mean of 3 runs, range 71.5 to 75.5
$0.028
74.8%
±2.6, Mean of 3 runs, range 72.2 to 77.5
$0.0006

Claude Fable 5.1 vs Claude Haiku 5.5: Overview

Claude Fable 5.1

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

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.