Context Window Calculator

A context window is the maximum amount of text an AI model can process in a single request. It includes your prompt, conversation history, documents you've attached, and the model's response. Context windows are measured in tokens — approximately 4 characters or 0.75 words per token in English.

As of 2026, several models advertise 1,000,000-token contexts—including Gemini 2.5 Flash / Gemini 3 Flash and Claude Sonnet 4.6 / Opus 4.6. OpenAI gpt-5.4 uses a 272,000-token context on the standard tier, while GPT-4o remains at 128,000 tokens.

Claude Sonnet 4.6 can use up to 1,000,000 tokens in one request on supported tiers—enough for very large books or codebases. Older 200K-class models fit roughly 600 pages of English text; CJK text uses more tokens per character so page counts are lower.

When you exceed an LLM's context window, one of two things happens: (1) the API returns an error requiring you to shorten your input, or (2) older parts of the conversation are silently truncated. Production systems typically handle this with summarization, sliding window approaches, or RAG (retrieval-augmented generation).

RAG (Retrieval-Augmented Generation) is a technique where only the most relevant chunks of a large document are retrieved and placed into the context window, rather than the entire document. This allows LLMs to effectively 'read' documents much larger than their context limit, while also reducing cost.