Context Window

The maximum amount of text (measured in tokens) a language model can consider at once — its prompt plus everything it has generated so far.

The context window sets the Cost of Retrieval an agent pays: the cheaper it is to fit your content in-window (markdown twins, concise structured data), the more of it an agent can afford to read.

term
Context Window
category
knowledge-memory
short_def
The maximum amount of text (measured in tokens) a language model can consider at once — its prompt plus everything it has generated so far.
long_def
The context window is the model's working memory: everything the model can 'see' for a single response — system prompt, retrieved documents, conversation history and tools — must fit inside it. Larger windows let an agent hold more context, but cost and latency rise with how much of the window is used.
see_also
token-economics tokenization context-engineering
etymology_origin
— verify-against-primary-at-build ↗ https://en.wikipedia.org/wiki/Large_language_model — 'context window' is standard LLM terminology; no single coiner
related_to
token-economics tokenization context-engineering prompt-caching
contrast_with
Unlike a database that stores unlimited data, the context window is a fixed per-request budget — anything beyond it must be retrieved, summarized or dropped.
example
A model with a 1M-token context window can read a large codebase in one request; a 200K window forces an agent to retrieve only the relevant files.
source
https://en.wikipedia.org/wiki/Large_language_model
status
active
why_it_matters
The context window sets the Cost of Retrieval an agent pays: the cheaper it is to fit your content in-window (markdown twins, concise structured data), the more of it an agent can afford to read.
sameAs
https://en.wikipedia.org/wiki/Large_language_model
bridge_entity
context-engineering
last_verified
2026-07-06
md_twin
/glossary/context-window.md

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