What does context window mean?

Key characteristics include its token-based limit, which governs the model's short-term memory for a given interaction. The model processes text within this window using techniques like a "sliding window" to analyze the provided tokens. When input exceeds the window, earlier tokens are typically dropped or truncated, potentially losing information. Therefore, understanding a model's specific context window size is essential for effective prompting and managing long documents or conversations.

Its primary application and value lie in enabling coherent text generation, summarization of lengthy content, document-based Q&A, and maintaining continuity within conversations. Larger context windows generally allow models to handle more complex queries involving extensive background information or multi-turn interactions. Users must structure inputs to stay within this limit or employ methods like retrieval-augmented generation for larger data sources.