What Is a Context Window and Why Does It Matter for AI Models

A context window is the total number of tokens — covering the prompt, conversation history, and model response — that a large language model can process at one time. Every AI model has a fixed token limit for this working memory, and once it is exceeded, older parts of a conversation effectively become invisible to the model. This creates the illusion that the model has 'forgotten' earlier details, though the information was simply pushed out of the window. To work around these limits, systems like retrieval-augmented generation (RAG) fetch only the most relevant documents and insert them into the prompt rather than loading everything at once. While newer models offer much larger context windows, bigger does not always mean better, as processing more tokens increases cost, latency, and can reduce how evenly the model attends to information across the full context.