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Claude Fable 5 vs Grok 4.6

Compare Claude Fable 5 and Grok 4.6 side-by-side. See how these vision models stack up in Image Captioning, Classification, OCR, Open Prompt, and Object Detection.

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AnthropicClaude Fable 5
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GrokGrok 4.6
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Models in this comparison

Claude Fable 5 vs Grok 4.6 on Vision Evals

Claude Fable 5 scores higher on 5 of the six Vision Evals tasks.

The widest gap is Object Detection, where Claude Fable 5 leads 56.4% to 20.2%.

Overall, Claude Fable 5 averages 78.8% (#8 of 31) against 67.8% (#17 of 31) for Grok 4.6.

Grok 4.6 is both cheaper ($0.0069 vs $0.034 per sample) and faster (7.4s vs 8.7s per sample).

Claude Fable 5Grok 4.6

Claude Fable 5 vs Grok 4.6 Comparison Table

Evals updated August 20, 2026Pricing updated August 25, 2026

PropertyClaude Fable 5Grok 4.6
OrganizationAnthropicSpaceXAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJun 2026Aug 2026
Context Window1.0M500K
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$10.00$2.00
Output $/1M$50.00$6.00
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
78.8%
67.8%
Avg cost / sample$0.034$0.0069
Avg speed / sample8.71s7.39s
By task
Object Detection
56.4%
$0.059
20.2%
$0.0068
Counting
63.5%
$0.017
70.3%
$0.0074
Identification
100.0%
$0.014
78.1%
$0.0048
OCR
94.0%
$0.039
92.0%
$0.0086
Data Extraction
92.8%
$0.015
84.5%
$0.0042
Reasoning (low)
66.2%
$0.018
61.6%
$0.0087
Reasoning (high)
66.2%
$0.024
61.6%
$0.027

Claude Fable 5 vs Grok 4.6: Overview

Claude Fable 5

Claude Fable 5 is Anthropic's first generally available Mythos-class large language model, released on June 9, 2026. It is built for long-horizon, asynchronous, and agentic tasks that prior Claude generations could not sustain, including multi-day autonomous coding sessions, complex knowledge work, and document-heavy analysis. The model supports a 1 million token context window with up to 128,000 output tokens per request and uses adaptive thinking as its sole reasoning mode, where the effort level is adjustable but raw chain-of-thought is never returned. Vision capabilities allow the model to parse diagrams, charts, and tables embedded in files and PDFs, and to use visual feedback to evaluate its own coding outputs against design goals. On benchmarks such as SWE-Bench Pro, the model scores 80.3% compared to 69.2% for Claude Opus 4.8, and it leads on CursorBench 3.1 for autonomous coding workflows.

Claude Fable 5 shares the same underlying model weights as Claude Mythos 5, but is deployed with safety classifiers that automatically reroute queries in high-risk domains — including cybersecurity, biology, and chemistry — to Claude Opus 4.8. These classifiers trigger in fewer than 5% of sessions on average. As a designated Covered Model, all traffic is subject to mandatory 30-day data retention to support safety monitoring. The model is available via the Claude API, Amazon Bedrock, Vertex AI, and Microsoft Foundry. Anthropic has not publicly disclosed parameter count, architecture details, or training data composition for this model.

Grok 4.6

Grok 4.6 is a proprietary reasoning model from xAI aimed at long-running agentic workflows, coding, and knowledge work. It accepts text and image input and returns text, with a 500,000 token context window and a knowledge cutoff of February 1, 2026. The model exposes an adjustable reasoning budget with low, medium, high, and xhigh settings, where high is the default, and it supports function calling, structured outputs, web and X search, and code execution as documented tool behaviors. Its visual capability covers interpreting images supplied alongside text prompts, which places it in the visual question answering and document understanding family, and it can also return object detection boxes as text coordinates when prompted.

xAI characterizes Grok 4.6 as the result of an extended post-training run over the Grok 4.5 lineage rather than a new pretrained base. The described recipe combines curated model-generated reasoning and technical data, engineering data, a revised optimizer, regenerated supervised fine-tuning trajectories, and reinforcement learning across agent environments spanning knowledge work, coding, kernel optimization, web development, and computer-aided design. Parameter count and architecture specifics are not disclosed. Independent measurement from Artificial Analysis places the model at 61 on its Intelligence Index, five points above Grok 4.5.