Does a bigger context window always produce better results?

No. Models exhibit 'lost-in-the-middle' degradation: facts buried deep in a long context are recalled less accurately than facts at the beginning or end. For best accuracy, retrieve only the most relevant context (via RAG and reranking) rather than dumping entire documents in. Use the large context window for tasks that genuinely require holistic understanding—not as a substitute for good retrieval.

Context Window

Written by Max Zeshut

Founder at Agentmelt · Last updated May 26, 2026

The maximum amount of text (measured in tokens) an AI model can process in a single interaction. Larger context windows let agents reason over longer documents—entire contracts, codebases, or conversation histories. Models now support 100K–1M+ tokens, enabling agents to handle complex tasks without losing context.

Example

A 500-page commercial real estate lease (~80K tokens) fits comfortably within Claude's 200K-token context window. The legal AI agent reviews the entire document in one shot—identifying assignment provisions, change-of-control clauses, and operating expense exclusions—without needing to chunk and reassemble findings the way older systems required.

Frequently asked questions

Does a bigger context window always produce better results?: No. Models exhibit 'lost-in-the-middle' degradation: facts buried deep in a long context are recalled less accurately than facts at the beginning or end. For best accuracy, retrieve only the most relevant context (via RAG and reranking) rather than dumping entire documents in. Use the large context window for tasks that genuinely require holistic understanding—not as a substitute for good retrieval.

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