Analyze Massive Document Sets Using 1M Token Context Window
Process massive datasets instantly using the 1M token context window.
Upload large batches of documents or entire code repositories directly into Claude Fable 5 to perform deep analysis without segmenting the data.
The Scenario
You have a massive collection of documents, such as 20 different research papers or a whole legacy codebase, and you need to find specific information or synthesize a summary across all of them.
Before & after
Researching across dozens of PDFs or massive log files required manual searching, ctrl+f, and taking notes to connect dots. This could take 3–5 hours for a comprehensive review.
By passing the entire 1M token context (roughly 750,000 words) into Claude Fable 5, you can ask specific questions or extract data instantly. This takes about 2–4 minutes to process and respond.
The Prompt
I am uploading [DESCRIBE_FILES, E.G., 20 RESEARCH PAPERS / LARGE CODEBASE]. Using your 1M token context window, please analyze all uploaded materials and [SPECIFIC_TASK, E.G., IDENTIFY CONTRADICTIONS BETWEEN PAPERS / FIND THE LOGIC ERROR IN THE AUTHENTICATION FLOW].
The new 1M token context window allows you to upload entire codebases, multiple books, or thousands of lines of logs to Claude Fable 5 and Mythos 5. This eliminates the need for RAG (Retrieval-Augmented Generation) for many medium-sized datasets.
Source
Claude Platform - Claude API Docs"Both models support a 1M token context window by default, 128k max output tokens, and always-on adaptive thinking."