Long context means a model can process a lot of text at once, such as whole books or large codebases.
Example
You upload a 300-page contract and ask for all notice periods.
For pros
Some models now handle hundreds of thousands to millions of tokens. Studies show, however, that information in the middle of long texts is found less reliably (“lost in the middle”). Long context is expensive; for large knowledge collections RAG is often cheaper and more accurate.
