Context Windows

The context window is the total amount of information a model can "see" at once - your input, any previous conversation, and the output it's generating all have to fit within this window. Think of it as the model's working memory. Early GPT models had context windows of about 4,000 tokens (roughly 3,000 words). Current models offer windows of 128,000 tokens or more, and some claim over a million. Bigger windows mean you can paste in entire documents, lengthy conversations or large codebases and ask questions about them. But there are caveats. Models don't necessarily pay equal attention to everything in the window - information in the middle of very long inputs can get less focus than content at the start or end. Larger windows also cost more to process, both in time and money. And "can fit in the window" is not the same as "will be used effectively." For business use, context window size matters when you need the model to work with lengthy documents, maintain conversation history, or cross-reference multiple sources. But don't assume that a bigger number automatically means better results - how well the model uses that context matters just as much.