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Claude Fable 5

Explore benchmark scores, genre strengths, weaknesses, and recent examples for Claude Fable 5 on Orivel.

Model Overview

Provider: Anthropic · claude-fable-5 NEW

Released

2026-06-09

Context

1M tokens

Input

$10.00 / 1M

Output

$50.00 / 1M

Claude Fable 5 is Anthropic's most capable widely released model, generally available from June 9, 2026. It is the public release of the Mythos model family, positioned for the most demanding reasoning, long-horizon agentic work, vision, and scientific research.

In Anthropic's own testing, Fable 5 posts state-of-the-art results on nearly all measured benchmarks and beats not only the previous Anthropic flagship Opus 4.8 but also GPT-5.5 and Gemini 3.1 Pro. It ships with safety safeguards: in high-risk areas (cybersecurity, biology, chemistry) it blocks the response and falls back to Claude Opus 4.8 — these safeguards trigger in under 5% of sessions on average.

The model uses always-on adaptive thinking, the Opus 4.7-generation tokenizer, a 1M-token context window, and up to 128k tokens of output. Pricing is $10 input / $50 output per 1M tokens — double Opus 4.8 — reflecting its frontier tier. Knowledge cutoff is January 2026.

What changed

  • Released June 9, 2026 as Anthropic's most capable widely released model (public release of the Mythos family)
  • State-of-the-art on nearly all measured benchmarks; beats Opus 4.8, GPT-5.5, and Gemini 3.1 Pro in Anthropic's testing
  • Exceptional at software engineering, knowledge work, vision, and scientific research
  • Safety safeguards: blocks high-risk (cyber/bio/chem) responses and falls back to Opus 4.8; triggers in <5% of sessions on average
  • Always-on adaptive thinking; Opus 4.7-generation tokenizer
  • 1M-token context window; up to 128k output tokens
  • Pricing: $10 input / $50 output per 1M tokens — double Opus 4.8 (frontier tier)
  • Available across the Claude API, Amazon Bedrock, Vertex AI, and Microsoft Foundry
  • Knowledge cutoff: January 2026
Official announcement

Overall Performance

Overall Rank

#1

Overall win rate

100%

Average Score

86

Wins

3

Sample Count

3

Win Rate by Model

Compare by Genre

Strength by Evaluation Criteria

Average score by criterion (out of 10)

Coverage

92 3 samples

Diversity

90 3 samples

Faithfulness

90 3 samples

Usefulness

89 3 samples

Specificity

88 3 samples

Structure

88 3 samples

Clarity

87 6 samples

Originality

84 3 samples

Compression

83 3 samples

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