A context window is the amount of text, tokens, or other input information that a model can consider at one time. A larger context window can support longer documents and conversations, but it does not guarantee perfect recall or reasoning over all included information.
The number of tokens a model can process in a given prompt. The larger the context window, the more information the model can use to provide coherent and consistent responses to the prompt.
The number of tokens that a foundational model can process in a given prompt. A larger context window lets the model access and process more information, which leads to more coherent, relevant, and comprehensive responses.
A side-by-side comparison of Context Window and Token. Understand how the terms differ, when each applies, and what the distinction means for AI governance, system design, or assurance evidence.
A side-by-side comparison of Prompt and Context Window. Understand how the terms differ, when each applies, and what the distinction means for AI governance, system design, or assurance evidence.
A side-by-side comparison of Content Chunking and Context Window. Understand how preparing source material into sections differs from the amount of information a model can consider at once.