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Claude Fable 5.1 vs Claude Sonnet 5

Compare Claude Fable 5.1 and Claude Sonnet 5 side-by-side. See how these vision models stack up in Object Detection, OCR, Image Captioning, Open Prompt, and Classification.

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AnthropicClaude Fable 5.1
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AnthropicClaude Sonnet 5
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Models in this comparison

Claude Fable 5.1 vs Claude Sonnet 5 on Vision Evals

Claude Fable 5.1 scores higher on all six Vision Evals tasks.

The widest gap is Reasoning, where Claude Fable 5.1 leads 72.0% to 43.0%.

Overall, Claude Fable 5.1 averages 81.3% (#7 of 52) against 66.4% (#31 of 52) for Claude Sonnet 5.

Claude Sonnet 5 is both cheaper ($0.0064 vs $0.035 per sample) and faster (4.8s vs 8.3s per sample).

Claude Fable 5.1Claude Sonnet 5

Claude Fable 5.1 vs Claude Sonnet 5 Comparison Table

Evals updated September 3, 2026Pricing updated September 3, 2026

PropertyClaude Fable 5.1Claude Sonnet 5
OrganizationAnthropicAnthropic
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateSep 2026Jun 2026
Context Window1.0M1.0M
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$10.00$2.00
Output $/1M$50.00$10.00
Vision Tasks
CaptioningDemoDemo
Chart Question Answering
ClassificationDemoDemo
Document Question Answering
Image Tagging
Multi-Label Classification
Object DetectionDemoDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
Overall
81.3%
66.4%
Avg cost / sample$0.035$0.0064
Avg speed / sample8.28s4.84s
By task
Object Detection (low)
61.4%
±0.5, Mean of 3 runs, range 61.0 to 62.0
$0.060
36.1%
$0.011
Object Detection (high)
65.0%
±0.4, Mean of 3 runs, range 64.6 to 65.3
$0.078
Counting (low)
69.4%
±2.7, Mean of 3 runs, range 66.2 to 71.6
$0.019
56.8%
$0.0030
Counting (high)
73.0%
±4.7, Mean of 3 runs, range 67.6 to 77.0
$0.023
Identification (low)
97.9%
±1.6, Mean of 3 runs, range 96.9 to 100.0
$0.013
81.3%
$0.0027
Identification (high)
96.9%
±3.1, Mean of 3 runs, range 93.8 to 100.0
$0.014
OCR (low)
94.0%
±0.4, Mean of 3 runs, range 93.6 to 94.4
$0.039
91.7%
$0.0078
OCR (high)
93.6%
±0.2, Mean of 3 runs, range 93.5 to 93.9
$0.039
Data Extraction (low)
93.1%
±0.5, Mean of 3 runs, range 92.8 to 93.8
$0.016
89.7%
$0.0030
Data Extraction (high)
93.5%
±0.5, Mean of 3 runs, range 92.8 to 93.8
$0.016
Reasoning (low)
72.0%
±1.3, Mean of 3 runs, range 70.9 to 73.5
$0.019
43.0%
$0.0032
Reasoning (high)
73.1%
±2.0, Mean of 3 runs, range 71.5 to 75.5
$0.028
43.0%
$0.0043

Claude Fable 5.1 vs Claude Sonnet 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 Sonnet 5

Claude Sonnet 5 is a mid-tier large language model from Anthropic, released on June 30, 2026, as the latest model in the Sonnet series and a direct successor to Claude Sonnet 4.6. It is a hybrid reasoning model designed primarily for agentic workflows, software coding, and professional tasks. The model features a 1 million token context window, a 128k maximum output token limit, and runs adaptive thinking by default, giving API users fine-grained control over reasoning effort across five levels (low, medium, high, max, and extra-high). It uses an updated tokenizer shared with Opus 4.7 and later models, which produces approximately 30% more tokens for equivalent text compared to earlier Claude models. On benchmarks, Sonnet 5 scores 63.2% on agentic coding and 81.2% on OSWorld, narrowing the gap with Opus 4.8 while remaining at Sonnet-tier pricing.

The model supports text and image input with text output, and accepts tools including browsers and terminals for autonomous multi-step task execution. Anthropic's safety evaluations report that Sonnet 5 shows a lower rate of undesirable behaviors than Sonnet 4.6 and is generally safer in agentic contexts, with improved resistance to prompt injection and reduced sycophancy. Cybersecurity safeguards equivalent to those on Opus 4.7 and 4.8 are active, though Anthropic notes the model was not deliberately trained on cybersecurity tasks. The model is proprietary and API-only, with no open weights.

Frequently Asked Questions

On Roboflow's Vision Evals, Claude Fable 5.1 performed better. It scores higher on all six vision tasks and averages 81.3% (#7 of 52) against 66.4% (#31 of 52) for Claude Sonnet 5. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.

Yes. On the Vision Evals Reasoning benchmark at low effort, Claude Fable 5.1 leads with 72.0% against 43.0%. This is the widest gap between the two models across the benchmark's tasks.

Claude Sonnet 5 is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0064 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 Sonnet 5 is priced at $2.00 per 1M input tokens and $10.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.

Claude Sonnet 5 is faster. Across Roboflow's Vision Evals it averaged 4.8s per inference against 8.3s. 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 object detection and OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.