The maximum amount of text an LLM can process in a single request, measured in tokens (roughly, words plus punctuation). A model with a 200,000-token context window can consider about 150,000 English words at once — enough to fit an entire meeting transcript, the participants' calendars, and the team's project documentation in a single call. Larger context windows let meeting copilots ground their suggestions in more material: not just "what was said in the last five minutes" but "what was said five meetings ago and what's in the linked spec." The trade-off is latency and cost: bigger contexts take longer to process and consume more tokens per request. Modern copilots increasingly rely on RAG to avoid stuffing irrelevant context into the window when only a small slice actually matters.