AI Vocabulary · 03 Working with AI
What is Context Window?
The maximum amount of text a model can take in at once. When it is full, something has to go.
The context window is the limit on how much a model can see in one request, measured in tokens. Everything counts: instructions, the whole conversation history, attached files and the answer being written.
Modern windows are large, often hundreds of thousands of tokens, enough for long reports. But two things remain true. Long conversations eventually fill it, and apps then summarise or drop older parts. And even before it is full, quality tends to drop as the context grows, because the important details compete with everything else.
Why it matters for you
If an assistant starts forgetting earlier instructions in a long chat, the conversation has grown too big. Start a fresh chat with a short summary of what matters. It is often faster than arguing with a tired session.
Own it
Bigger windows also mean bigger bills, because you pay for every token sent. Keeping context lean is both a quality and a cost decision.
Where it comes from
There is no single coiner. "Context window" was already used in earlier language research for the span of neighbouring words a model looks at, for example in the 2013 word2vec work (Mikolov et al.). With large language models, it came to mean the whole input a model can read at once. GPT-3's window in 2020 was 2,048 tokens (Brown et al., 2020); today's windows are many times larger.
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