What is a Context Window?

A context window is the maximum amount of text an AI model can consider at once, covering both your input and its reply. Anything beyond that limit is invisible to the model. It is measured in tokens, which are pieces of words rather than whole words.

The window covers everything in play: the conversation so far, any documents pasted in, and the answer being generated. Sizes are quoted in tokens, roughly three-quarters of a word each in English, and they vary widely: 128,000 tokens is common, and some models advertise a million, which is several long novels. When a chat outgrows the window, the oldest messages fall out first, which is why a long session forgets instructions given at the start. Bigger windows also cost more to run, since the model compares every token against every other, so doubling the text roughly quadruples that work. Models are weaker in the middle of very long inputs too, recalling the start and end far better, a measured effect known as lost in the middle.

A whiteboard in a meeting room. Everything the team needs must fit on it, and when it fills up, someone erases the oldest corner to make space for new notes. The plan sketched in minute one is gone by hour three, not because anyone chose to forget it, but because the board ran out of surface.