Understanding AI Context Windows
Learn about context window limits, how models process long inputs, and strategies for handling large documents. What is a Context Window? The context window is the maximum input length an AI model can process at once. GPT-4o: 128K tokens, Claude 4: 200K tokens, Gemini 2.5 Pro: 1M tokens. Tokens (not words) are the unit — roughly 0.75 words per token. Larger windows enable processing entire books, codebases, or long conversations in one request. Strategies for Long Content Summarize or chunk long documents before sending. Use RAG (Retrieval Augmented Generation) for large knowledge bases. Send relevant sections, not entire documents. For codebases: include file structure and key function signatures, not all files. For conversations: summarize earlier parts periodically. Use sliding window approaches for very long streams. Quality at Context Boundaries Models focus more on content at the beginning and end of the context window (primacy/recency effects). Important instructions should go at the start. Critical data should be near the end. Model performance degrades for details in the middle of long contexts — verify accuracy for mid-context information.