Anthropic’s Claude AI Model Can Now Handle Longer Prompts

Claude Sonnet 4 now supports a 1 million token context window a fivefold increase from the previous limit of 200K tokens To put it in perspective that’s enough space for 750,000 words more than the entire Lord of the Rings trilogy or 75,000+ lines of code in a single prompt

What This Enables

Deep Code Analysis Run full codebases including source files tests and documentation as one unified input ideal for architecture understanding and cross-file improvements Extensive Document Synthesis: Process dozens of lengthy documents like contracts or technical specs within a single request Context-Aware Agent Workflows Build AI agents that retain context across hundreds of tool calls and multi-step tasks

Access & Availability

Available now in public beta for Tier 4 customers and those with custom rate limits via:

Anthropic API Amazon Bedrock Google Cloud’s Vertex AI coming soon

Streamlined Summary & Insight Extraction

Claude especially the Sonnet 4 model excels at ingesting hundreds of pages such as reports research papers or multi-document briefs and producing concise accurate summaries with minimal hallucination . This makes it ideal for Reducing extensive email threads into essential action points Summarizing regulatory filings or academic articles Extracting key insights from large datasets or multi-part reports

End-to-End Code Repository Understanding

With its expanded context window Claude can process entire codebases tests documentation multiple files in a single prompt. This capability supports Cross-file bug detection and refactoring Architectural overview and system mapping Comprehensive code review and documentation generation

Advances in Agentic Workflows & Tool Integration

Claude Sonnet 4 is designed for agentic coding workflows where it applies reasoning uses tools and maintains state across steps all within a unified context . This supports AI agents that operate over extended sessions without losing contextMultistep task execution with memory and error correctionWorkflows that bridge code reports and system integration

Anthropic recommends structuring prompts by placing long-form inputs e.g. large documents datasets at the top of the prompt. Following that with clear instructions at the end has been shown to boost response quality by 30% Anthropic. This is especially beneficial for complex multi-document summarization or instruction-intensive tasks.

Enterprise Applications & Context Retention

• For example entire books e.g., War and Peace.
• Up to 2,500 pages of text roughly equivalent to 100 financial reports
• 75,000–110,000 lines of code in one go

This capability reduces the friction of chunking and enhances Claude’s viability in sectors such as legal pharmaceuticals software development and research services.

Context Utilization Remains Key

While extended context is powerful research shows models often only use 10–20% effectively of extremely large inputs unless specifically fine-tuned or engineered for long-range dependencies . Claude’s strengths lie in effective context utilization especially with Anthropic‘s optimizations for reasoning tool use and memory handling