Anthropic Claude Fable 5.1, released in September 2026, succeeds Fable 5 as the most capable tier of the Claude family, positioned for the most demanding reasoning and long-horizon agentic work. Against Fable 5 it raises the completion rate on long-running agentic coding tasks from the low forties to over 55 percent, roughly doubles its score on scientific research terminal tasks, and improves knowledge work including documents, spreadsheets, and slides, while staying on task better across very long conversations. Its knowledge cutoff moves to June 2026. Supports very long context for whole-codebase or multi-document analysis, plus a reasoning-effort dropdown (five levels, default high), an option to show the thinking process, web search, and image and document upload; extended thinking is always on and cannot be switched off. Same premium per-token pricing as Fable 5, but cached context re-read in continuous conversations is far cheaper, which makes long sessions more economical. Reserve it for the hardest work such as large refactors, complex architecture design, and deep cross-document research; use Opus 5 or Sonnet 5 for daily work. If you need to search the web for information, please turn on the "Web Search" switch. Prompt example 1: (Upload the project's design and module docs as docx) Analyze module dependencies, find overly coupled parts, and propose a phased refactoring plan with risks per phase. Prompt example 2: Plan a 12-week research project comparing three ways to reduce the urban heat island effect, listing literature topics, data sources, methods, and weekly milestones. Prompt example 3: Design an annual sales analysis spreadsheet for a mid-size online store with sheets, columns, and formulas, then outline a 10-slide presentation for management. Prompt example 4: Build a Markdown-to-HTML converter from scratch in TypeScript supporting headings, lists, tables, and code blocks: break the work into steps, complete them in order, and include test cases. Prompt example 5: Design an RNA-seq analysis pipeline from raw read quality control through alignment, differential expression, and functional enrichment, explaining tool choices and output files at each step. Prompt example 6: Derive a finite-difference scheme for the 2D heat equation and its stability condition, then simulate in Python a square metal plate heated at the center for 60 seconds and plot the heat map. Prompt example 7: (Upload a 40-slide technical product spec pptx) Rewrite it as a 12-slide deck for the sales team, each slide with a title, three key points, and speaker notes in customer-friendly terms. Prompt example 8: Analyze how population aging affects staffing at small and mid-size businesses, and propose short, mid, and long-term strategies with resources needed, expected impact, and metrics for each. Prompt example 9: (Upload five vendors' system proposals as PDF) Build an evaluation matrix scoring features, timeline, maintenance, and risk, justify each score, and recommend the best two. Prompt example 10: Design an algorithm to build a monthly three-shift roster for 30 nurses that honors leave requests, allows at most five days in a row, and spreads night shifts evenly, with its time complexity. Maximum context window (input and output combined): about 1,000,000 tokens. Maximum output per reply: about 64,000 tokens (model reasoning, if any, counts toward this limit). Maximum total upload size per request: 512MB (all files and message content combined). Accepted document formats: pdf, docx, xlsx, pptx, txt, csv (file content is provided to the model as extracted text). Accepted image formats: gif, jpeg, jpg, png, webp. Animated GIF images are analyzed using only the first frame. Maximum number of images: 600. When uploading more than 20 images, each side must be at most 2,000 pixels. Maximum size per image: 10MB (base64-encoded). Maximum total image size per message: 20MB (text and history share the same request size limit; uploads close to the limit may still be rejected). Image dimensions: 200 to 8,000 pixels per side. Output content formats: Text/Image Pricing: Very high Continuous conversation: Supported AI can make mistakes. Please verify important information.