Anthropic Launches Claude Fable 5.1 & Mythos 5.1: Features & Pricing

 

Anthropic has introduced Claude Fable 5.1 and Claude Mythos 5.1, marking another significant step in the evolution of its frontier AI models. While both models are built on the same underlying architecture, they are designed for different audiences through distinct safety controls. Claude Fable 5.1 is broadly available for developers, enterprises, and paid Claude users, whereas Claude Mythos 5.1 is reserved for vetted organizations working on advanced cybersecurity and life sciences projects. Beyond performance improvements, Anthropic has focused on making long-running AI workloads more efficient by significantly lowering prompt cache-read costs.

The biggest upgrades in Claude Fable 5.1 revolve around extended coding sessions, autonomous agentic workflows, and complex knowledge tasks. The model can work across entire codebases, perform code reviews, generate and verify tests, identify root causes instead of temporary fixes, and interpret charts, tables, and diagrams within documents. Anthropic also reports notable benchmark improvements over Fable 5, particularly in software engineering and automation tasks, while enterprise customers gain access to enhanced security controls and flexible data governance options.

According to Anthropic, the standard pricing for Claude Fable 5.1 remains unchanged at $10 per million input tokens and $50 per million output tokens. However, cache-read pricing has been reduced by 75%, dropping from $1 to just $0.25 per million tokens. Anthropic estimates this could lower overall costs by around 25% for typical workloads and by as much as 45% for highly agentic applications. Meanwhile, Claude Mythos 5.1 continues to offer the same core intelligence but with more permissive safeguards for approved users handling sensitive scientific and cybersecurity research.

Ultimately, the launch of Claude Fable 5.1 and Mythos 5.1 highlights how frontier AI competition is shifting beyond raw benchmark scores. Anthropic is placing equal emphasis on affordability, long-duration reliability, enterprise governance, and responsible access controls. By combining stronger autonomous capabilities with lower operational costs and specialized deployment options, the company is positioning its latest AI models to better support both mainstream enterprise adoption and highly regulated research environments.