Verified65% confidenceFactExact time
The context window determines how much content the model can remember within a single conversation.
3
Sources
65%
Confidence
Long-term
Relevance
9/16/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe context window mechanism causes models in multi-turn conversations to feed the entire conversation history into the context, causing token consumption to grow rapidly as the conversation lengthens.79% similarVerifiedThe so-called conversational memory is essentially the application layer concatenating historical messages into the prompt before submitting it to the model, with state management handled by the client or an intermediate layer.77% similarUnverifiedIn multi-turn conversations, the System message sets the behavioral tone and constraints, the user message represents user input, and the assistant message is the model's historical replies.74% similarVerifiedLong conversations package and resend the entire context history to the model, which is counted toward the token usage of each request; the longer the conversation, the more tokens a single request consumes.74% similarUnverifiedThe actual number of tokens consumed by a single user request includes the entire input context (including conversation history, system prompts, tool definitions, etc.) as well as the response content generated by the model.73% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/927579API
curl https://kongchang.com/api/v1/knowledge/claims/927579MCP
get_claim(id=927579)