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Context windows in LLMs: the limit that decides what a model can remember

An Analytics Vidhya explainer updated today breaks down how an LLM’s context window caps the text it can use in a single response and why older messages can drop out.

Analytics Vidhya refreshed a quick explainer (Jan 19, 2026) on why LLMs can “forget” earlier parts of a long chat: the context window.

Key points:

  • What it is: The context window is the maximum amount of text a model can read and use while generating a response.
  • What it includes: Your current prompt plus the most recent conversation history (think short‑term memory).
  • What happens when you exceed it: Older messages may drop out of the usable input, so earlier details can be ignored mid-thread.
  • Why it matters: Context length is a practical differentiator between modern LLMs.
  • Where you notice the limit: Code work (analysis/debugging), summarizing long text, long-document Q&A, and maintaining continuity in extended conversations.