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Claude Fable 5.1 vs Gemini 3.8 Flash

Compare Claude Fable 5.1 and Gemini 3.8 Flash 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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GoogleGemini 3.8 Flash
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Models in this comparison

Claude Fable 5.1 vs Gemini 3.8 Flash on Vision Evals

Gemini 3.8 Flash scores higher on 3 of the five Vision Evals tasks.

The widest gap is Counting, where Gemini 3.8 Flash leads 78.8% to 69.4%.

Overall, Claude Fable 5.1 averages 74.7% (#14 of 63) against 79.8% (#7 of 63) for Gemini 3.8 Flash.

Gemini 3.8 Flash is cheaper ($0.0045 vs $0.039 per sample), while Claude Fable 5.1 is faster (8.3s vs 12.8s per sample).

Claude Fable 5.1Gemini 3.8 Flash

Claude Fable 5.1 vs Gemini 3.8 Flash Comparison Table

Evals updated October 13, 2026Pricing updated October 17, 2026

PropertyClaude Fable 5.1Gemini 3.8 Flash
OrganizationAnthropicGoogle
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateSep 2026Sep 2026
Context Window1.0M1.0M
ParametersUnknownUnknown
LicenseProprietaryProprietary
Commercial usecommercial use per vendor termscommercial use per vendor terms
Pricing per 1M tokens
Input $/1M$10.00$0.825
Output $/1M$50.00$4.13
Vision Tasks
CaptioningDemoDemo
Chart Question AnsweringSupportedSupported
ClassificationDemoDemo
Document Question AnsweringSupportedSupported
Image TaggingSupportedSupported
Multi-Label ClassificationSupportedSupported
Object DetectionDemoDemo
OCRDemoDemo
Vision LanguageSupportedSupported
Visual Question AnsweringDemoDemo
Model Features
Foundation VisionSupportedSupported
LLMs with Vision CapabilitiesSupportedSupported
Multimodal VisionSupportedSupported
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
Overall
74.7%
79.8%
Avg cost / sample$0.039$0.0045
Avg speed / sample8.35s12.76s
By task
Object Detection (low)
61.4%
±0.5, Mean of 3 runs, range 61.0 to 62.0
$0.060
68.1%
±0.8, Mean of 3 runs, range 67.3 to 69.0
$0.0045
Object Detection (high)
65.0%
±0.4, Mean of 3 runs, range 64.6 to 65.3
$0.078
74.8%
±1.1, Mean of 3 runs, range 73.4 to 75.6
$0.023
Counting (low)
69.4%
±2.7, Mean of 3 runs, range 66.2 to 71.6
$0.019
78.8%
±2.7, Mean of 3 runs, range 75.7 to 81.1
$0.0040
Counting (high)
73.0%
±4.7, Mean of 3 runs, range 67.6 to 77.0
$0.023
79.3%
±1.4, Mean of 3 runs, range 78.4 to 81.1
$0.027
Identification (low)
97.9%
±1.6, Mean of 3 runs, range 96.9 to 100.0
$0.013
97.9%
±1.6, Mean of 3 runs, range 96.9 to 100.0
$0.0016
Identification (high)
96.9%
±3.1, Mean of 3 runs, range 93.8 to 100.0
$0.014
96.9%
±0.0, Mean of 3 runs, range 96.9 to 96.9
$0.0037
OCR (low)
72.9%
$0.039
72.8%
$0.0049
by category
Single value
64.3%
Transcription
84.7%
Structured JSON
89.2%
Text localization
46.5%
Single value
73.5%
Transcription
91.3%
Structured JSON
86.1%
Text localization
26.4%
OCR (high)
75.3%
$0.051
78.7%
$0.039
by category
Single value
69.1%
Transcription
95.2%
Structured JSON
89.5%
Text localization
43.4%
Single value
70.9%
Transcription
94.1%
Structured JSON
90.9%
Text localization
58.6%
Reasoning (low)
72.0%
±1.3, Mean of 3 runs, range 70.9 to 73.5
$0.019
81.2%
±0.3, Mean of 3 runs, range 80.8 to 81.5
$0.0038
Reasoning (high)
73.1%
±2.0, Mean of 3 runs, range 71.5 to 75.5
$0.028
84.5%
±1.0, Mean of 3 runs, range 83.4 to 85.4
$0.023

Claude Fable 5.1 vs Gemini 3.8 Flash: 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.

Gemini 3.8 Flash

Gemini 3.8 Flash is a natively multimodal reasoning model in Google's Gemini 3 series, positioned as the speed and cost oriented Flash tier while targeting long-horizon software engineering, autonomous agents, and enterprise workflows. It accepts text, images, video, audio, and PDF documents in a single request and returns text, with an input limit of 1,048,576 tokens and an output limit of 65,536 tokens. Thinking is configurable at low, medium, and high levels, and the model supports function calling, code execution, structured outputs, context caching, search and Maps grounding, file search, and computer use in preview. Image generation, audio generation, and the Live API are not supported.

On vision oriented evaluations the model reports 86.2% on CharXiv Reasoning for chart and figure synthesis and 87.8% on LVBench for long video understanding in agentic mode, alongside 90.8% on Terminal-Bench 2.1 and 61.6% on SWE-Bench Pro for coding. Following Gemini API conventions, it can localize objects by emitting bounding boxes as [ymin, xmin, ymax, xmax] integers normalized to a 0 to 1000 range, which supports prompt driven detection and grounding in addition to captioning, document parsing, and visual question answering. The knowledge cutoff is March 2026, though coverage in some domains reflects the January 2025 cutoff shared across the Gemini 3 family.

Frequently Asked Questions

On Roboflow's Vision Evals, Gemini 3.8 Flash performed better. It scores higher on 3 of the five vision tasks and averages 79.8% (#7 of 63) against 74.7% (#14 of 63) for Claude Fable 5.1. 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, Gemini 3.8 Flash leads with 78.8% against 69.4%. This is the widest gap between the two models across the benchmark's tasks.

Gemini 3.8 Flash is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0045 per sample against $0.039. Claude Fable 5.1 is priced at $10.00 per 1M input tokens and $50.00 per 1M output; Gemini 3.8 Flash is priced at $0.83 per 1M input tokens and $4.13 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 12.8s. 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.