MYTHOS MYTHOS MYTHOS

2026-06-09 · Source: Matthew Berman · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Advanced, extended

Summary

Anthropic has publicly released its new "Mythos" class models, Claude Fable 5 and Mythos 5, previously described as "too dangerous" for general release. Fable 5, a 10 trillion parameter model, is the general-use version with safeguards, while Mythos 5 is for the security community without guardrails. Benchmarks show Fable 5 achieving 80% on Aenta coding SWEBench Pro, 29.3% on Frontier Code Diamond, and 1932 on GDP val, significantly outperforming Claude Opus 4.8 and GBT 5.5. The model demonstrates exceptional capabilities in software engineering, knowledge work, vision, and scientific research, particularly excelling at complex, long-duration tasks, such as migrating a 50 million-line Ruby codebase in a day. Priced at \$10 per million input and \$50 per million output tokens, it offers unparalleled autonomous work. User experience notes its verbosity, high information density, tendency to ask clarifying questions, and perceived slowness.

Key takeaway

For AI Engineers and ML teams tackling complex, long-horizon software engineering or knowledge work, Anthropic's Fable 5 presents a transformative solution. Its unparalleled autonomous capabilities can compress months of engineering effort into days, making its \$50 per million output token cost a bargain for critical projects. You should strategically route your most difficult problems to Fable 5, leveraging its workflows and loops for agentic execution, while reserving less expensive models for simpler tasks to optimize your budget. Be prepared for verbose outputs and initial processing slowness.

Key insights

Anthropic's Fable 5/Mythos 5 introduces a new AI class, demonstrating unprecedented autonomous capability for complex tasks despite high cost.

Principles

• Model routing is crucial for cost efficiency.
• Information density increases model intelligence.
• No apparent limit to tokens improving output quality.

Method

Utilize model routing to assign difficult problems to Fable 5, reserving less capable models for simpler tasks. Employ workflows and loops for parallel agentic execution to maximize autonomous capability.

In practice

• Start Fable 5 on lowest thinking effort setting.
• Use "Here.Now" for agent publishing and storage.
• Update prompts to simplify Fable 5's verbose output.

Topics

• Claude Fable 5
• Large Language Models
• Agentic AI
• Software Engineering
• AI Benchmarks
• Model Pricing

Best for: CTO, AI Architect, MLOps Engineer, AI Scientist, Machine Learning Engineer, AI Engineer

Related on AIssential

• MYTHOS is LIVE!!!! — Fable is a 10 trillion-parameter model excelling in complex, long-horizon tasks, but with notable verbosity and a unique interaction flow.
• Anthropic's new Claude Fable 5 is the same base model as Mythos but with guardrails attached — Fable 5 offers Mythos-class AI power with integrated safety guardrails for broader, secure general use.
• Anthropic hands the public Mythos-class AI — Anthropic's Fable 5 sets new AI performance benchmarks, while agents like Perplexity Computer empower users for complex, creative work.
• Why Everyone Is Freaking Out About Fable 5 (Mythos) — Fable 5 delivers unprecedented "one-shot" capability for complex coding and agentic tasks, balanced by high cost and strict censorship.
• Anthropic finally released Claude Fable 5, a public Mythos-class model. — Anthropic's Claude Fable 5 introduces a guarded public release model, balancing advanced capabilities with controlled access for sensitive AI research.
• Claude Fable 5 review: what the new Mythos model gets right (and very wrong) — Claude Fable 5 offers advanced intelligence for complex tasks and vision, but its verbose output and high cost necessitate strategic application.

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Editorial summary, takeaway, and curation by AIssential. Original article published by Matthew Berman.