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Claude Fable 5.1 vs Qwen3.8 Max

Compare Claude Fable 5.1 and Qwen3.8 Max 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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QwenQwen3.8 Max
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Models in this comparison

Claude Fable 5.1 vs Qwen3.8 Max on Vision Evals

Qwen3.8 Max scores higher on 4 of the five Vision Evals tasks.

The widest gap is Object Detection, where Qwen3.8 Max leads 76.7% to 61.4%.

Overall, Claude Fable 5.1 averages 74.7% (#14 of 63) against 79.3% (#8 of 63) for Qwen3.8 Max.

Qwen3.8 Max is cheaper ($0.0080 vs $0.039 per sample), while Claude Fable 5.1 is faster (8.3s vs 18.9s per sample).

Claude Fable 5.1Qwen3.8 Max

Claude Fable 5.1 vs Qwen3.8 Max Comparison Table

Evals updated October 13, 2026Pricing updated October 23, 2026

PropertyClaude Fable 5.1Qwen3.8 Max
OrganizationAnthropicQwen
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateSep 2026Aug 2026
Context Window1.0M984K
ParametersUnknown2.4T total, ~95B active
LicenseProprietaryApache 2.0
Commercial usecommercial use per vendor termsfree for commercial use
Pricing per 1M tokens
Input $/1M$10.00No published price
Output $/1M$50.00No published price
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%
79.3%
Avg cost / sample$0.039$0.0080
Avg speed / sample8.35s18.95s
By task
Object Detection (low)
61.4%
±0.5, Mean of 3 runs, range 61.0 to 62.0
$0.060
76.7%
±0.3, Mean of 3 runs, range 76.5 to 77.1
$0.012
Object Detection (high)
65.0%
±0.4, Mean of 3 runs, range 64.6 to 65.3
$0.078
78.4%
±0.4, Mean of 3 runs, range 78.1 to 78.9
$0.030
Counting (low)
69.4%
±2.7, Mean of 3 runs, range 66.2 to 71.6
$0.019
81.1%
±2.0, Mean of 3 runs, range 78.4 to 82.4
$0.0046
Counting (high)
73.0%
±4.7, Mean of 3 runs, range 67.6 to 77.0
$0.023
81.1%
±0.0, Mean of 3 runs, range 81.1 to 81.1
$0.0091
Identification (low)
97.9%
±1.6, Mean of 3 runs, range 96.9 to 100.0
$0.013
88.5%
±1.6, Mean of 3 runs, range 87.5 to 90.6
$0.0027
Identification (high)
96.9%
±3.1, Mean of 3 runs, range 93.8 to 100.0
$0.014
89.6%
±1.6, Mean of 3 runs, range 87.5 to 90.6
$0.0037
OCR (low)
72.9%
$0.039
74.0%
$0.0077
by category
Single value
64.3%
Transcription
84.7%
Structured JSON
89.2%
Text localization
46.5%
Single value
63.9%
Transcription
95.2%
Structured JSON
85.4%
Text localization
59.0%
OCR (high)
75.3%
$0.051
71.8%
$0.028
by category
Single value
69.1%
Transcription
95.2%
Structured JSON
89.5%
Text localization
43.4%
Single value
61.7%
Transcription
94.8%
Structured JSON
81.6%
Text localization
59.6%
Reasoning (low)
72.0%
±1.3, Mean of 3 runs, range 70.9 to 73.5
$0.019
75.9%
±2.0, Mean of 3 runs, range 73.5 to 77.5
$0.0048
Reasoning (high)
73.1%
±2.0, Mean of 3 runs, range 71.5 to 75.5
$0.028
80.3%
±2.0, Mean of 3 runs, range 78.2 to 82.1
$0.011

Claude Fable 5.1 vs Qwen3.8 Max: 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.

Qwen3.8 Max

Qwen3.8 Max is the flagship tier of Alibaba's Qwen3.8 family, a sparse mixture-of-experts multimodal model with roughly 2.4 trillion total parameters of which about 95 billion activate per token, which keeps serving cost and latency well below what the total parameter count would imply. It builds on the architectural foundation established by Qwen3.5 and accepts text, images, video, and documents as input while producing text output. Reported context handling reaches close to one million tokens, with a maximum generation length of 131,072 tokens, so the model is aimed at long-horizon agentic work such as repository-scale coding, multi-step research, data analysis, and office document workflows.

For vision work the model performs image and video understanding, document and chart interpretation, text recognition inside images, and grounded visual question answering, and Alibaba reports gains concentrated in multimodal and agentic evaluation categories rather than general reasoning. Published figures include 86.6 on Terminal-Bench 2.1, 67.7 on SWE-bench Pro, 93.0 on PaperBench, 82.8 on IFBench, and 92.6 on GPQA Diamond. It is the first model in the Max tier of the Qwen line for which the team states weights will be released publicly, alongside a smaller Qwen3.8 27B checkpoint. No training or safety model card has been published.