Context Window
LLM & Language ModelsThe maximum amount of text an AI model can process in a single conversation — measured in tokens. A larger context window means the AI can 'remember' more.
The context window is one of the most important specs of any language model. It determines how much text the model can see at once — including your prompt, the conversation history, any documents you've uploaded, and the AI's own responses.
Think of it like the AI's working memory. GPT-4o has a 128K token context window (~96,000 words). Claude has 200K tokens (~150,000 words). Google Gemini claims 1 million tokens. When you exceed the context window, the model starts 'forgetting' earlier parts of the conversation.
Context window size matters enormously for practical use. Analyzing a long legal contract? You need a big context window. Having a quick Q&A? 4K tokens is fine. Note that bigger isn't always better — models can struggle with information buried in the middle of very long contexts (the 'lost in the middle' problem).
Real-World Example
Claude's 200K token context window means it can process an entire novel or codebase in a single conversation — a key advantage for document analysis.
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FAQ
What is Context Window?
The maximum amount of text an AI model can process in a single conversation — measured in tokens. A larger context window means the AI can 'remember' more.
How is Context Window used in practice?
Claude's 200K token context window means it can process an entire novel or codebase in a single conversation — a key advantage for document analysis.
What concepts are related to Context Window?
Key related concepts include Token, LLM (Large Language Model), Prompt, RAG (Retrieval-Augmented Generation), Embedding. Understanding these together gives a more complete picture of how Context Window fits into the AI landscape.