Anthropic Super-Frontier Available in FlowHunt

Claude Fable 5

Claude Fable 5 is the highest-rated AI model in this leaderboard, above all standard frontier models, developed by Anthropic and released in June 2026. It is a proprietary closed-weight model, available through the Anthropic API. The 1M-token context window is large enough to hold entire codebases, lengthy technical documents, or extended agentic sessions without truncation.

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Claude Fable 5 was released on June 9, 2026 as the first model in Anthropic’s new Mythos-class tier — a capability level above the existing Opus line. The name ‘Fable’ continues Anthropic’s literary naming convention (Opus, Sonnet, Haiku) while marking a significant architectural departure. Fable 5 is the production deployment of Anthropic’s internal Mythos 5 research model, with enterprise-grade safety and reliability constraints applied.
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Benchmarks

Each score appears once, with its rank among tracked models and who measured it.

Compared with Super-Frontier peers on the same scale
  • Claude Fable 5this model
  • GPT-6 Astrathis model leads on 1 of 6
  • Claude Fable 5.1this model leads on 1 of 7
Verified independent evaluator, counted in the ranking Self-reported published by Anthropic, shown but not ranked
Overall

AA Intelligence Index

Independent composite of agent, coding, knowledge and science tests by Artificial Analysis (v4).

Source ↗

Claude Fable 5 49.6 GPT-6 Astra 52.7 Claude Fable 5.1 53.4
#7of 45 Verified
Coding

DeepSWE

113 long-horizon software tasks written from scratch, graded by hidden tests.

Source ↗Also: Self-reported 69.7% (quoted in Opus 5 system card Table 8.1.A)

Claude Fable 5 69.9% GPT-6 Astra 74.1% Claude Fable 5.1 67.4%
#5of 17 Verified

SWE-bench Pro

Real issues across several languages and large codebases.

Claude Fable 5 80.3% GPT-6 Astra No score Claude Fable 5.1 81.2%
Not ranked Self-reported

SWE-bench Verified

500 verified GitHub issues. Saturated at the frontier.

Claude Fable 5 95.0% GPT-6 Astra No score Claude Fable 5.1 No score
Not ranked Self-reported
Agents

Terminal-Bench 4.0

Multi-step professional tasks done by an agent in a command-line terminal.

Source ↗Also: Self-reported 42.0% (TB 4.0 (Mythos 5: 45))

Claude Fable 5 42.4% GPT-6 Astra 59.1% Claude Fable 5.1 52.0%
#7of 36 Verified
Reasoning

Humanity's Last Exam

Expert-written questions across 100+ subjects, no tools.

Source ↗Also: Self-reported 57.8% (no tools, restated in Fable 5.1 card)

Claude Fable 5 55.5% GPT-6 Astra 54.7% Claude Fable 5.1 59.1%
#3of 44 Verified

GPQA Diamond

Graduate-level science questions that search cannot answer.

Source ↗Also: Verified 93.2% (Vals AI own implementation)

Claude Fable 5 92.6% GPT-6 Astra 96.1% Claude Fable 5.1 93.7%
#13of 37 Verified

ARC-AGI-2

Novel visual puzzles that cannot be memorised.

Source ↗

Claude Fable 5 89.2% GPT-6 Astra 95.0% Claude Fable 5.1 90.0%
#7of 27 Verified

What to Use Claude Fable 5 For

Software Engineering

The benchmark uses 500 human-validated real GitHub issues: the model reads the repo, understands the failing test, and produces a passing patch. At this level it autonomously closes complex tickets, performs multi-file refactors, and acts as an agentic coding assistant in real development workflows.

Long-Document & Codebase Analysis

With a 1M-token context window, Claude Fable 5 can ingest entire software repositories, long legal contracts, book-length research reports, or extensive conversation histories in a single prompt — enabling deep document Q&A, cross-file codebase reasoning, and comprehensive summarisation without chunking heuristics or RAG pipelines.

Strengths and limitations

Strengths

  • Exceptional real-world coding
  • Very long documents and large codebases (1M context)

Limitations

  • Closed-weight — cannot be self-hosted or fine-tuned on private data

Use it in FlowHunt

Use Claude Fable 5 in any flow, next to your own tools and knowledge sources.

  1. 1Open a flow, or create one from a template
  2. 2Add an AI Agent or Generator component
  3. 3Pick Claude Fable 5 in the model selector

Related AI Models

About Anthropic San Francisco, CA · Founded 2021 · anthropic.com

Anthropic is an AI safety company founded in 2021 by former OpenAI researchers Dario Amodei and Daniela Amodei, along with a group of colleagues who had led OpenAI's safety and policy teams. The company's stated mission is the responsible development of AI for the long-term benefit of humanity, and its research agenda is defined by that commitment: Constitutional AI (CAI), a technique for training models to be helpful, harmless, and honest through self-critique; mechanistic interpretability, which aims to reverse-engineer what individual neurons and circuits inside large networks actually compute; and scaling science, which tries to predict how model behaviour changes with compute and data. Anthropic publishes this research openly and has become one of the most cited AI safety labs in academic literature. Claude is Anthropic's public model family, named for Claude Shannon, the founder of information theory, and runs from Claude 1 to the Claude 5.5 generation and Claude Fable 5.1. Anthropic operates a commercial API and consumer-facing Claude.ai product, and maintains deep cloud partnerships with AWS (Amazon Bedrock) and Google Cloud (Vertex AI).

anthropic.com ↗

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Frequently asked questions

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