Context Window
The maximum number of tokens a model can consider in a single request.
The context window is the total number of tokens a model can process in one request, covering both the input prompt and the generated output. In Amazon Bedrock, each foundation model exposes a different maximum context length, so model choice means matching that window to the task, such as summarizing long legal documents. The exam nuance is that input and output share the window: a very long prompt leaves fewer tokens for the response. This differs from RAG, which extends effective memory by retrieving relevant chunks before the call rather than enlarging the window itself.
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