Unverified50% confidenceFactExact time
The LLM context window is the maximum number of tokens the model can receive in a single call, including the system prompt, conversation history, retrieved memories, tool definitions, and the current input; when the sum of the content approaches the window limit, the model needs to truncate or compress, usually discarding the earliest content first.
1
Sources
50%
Confidence
Long-term
Relevance
10/14/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedThe memory of LLMs depends on the context window, which is the maximum number of tokens the model can process in a single inference.80% similarUnverifiedLLM本质上是无状态的推理引擎,每次调用模型时所有记忆都必须以文本形式塞入上下文窗口77% similarUnverifiedThe autoregressive decoding phase of LLMs is limited by memory bandwidth bottlenecks, as generating each token requires a complete traversal of the activated model weights.71% similarUnverifiedLLM-based information extraction can be quickly adapted to different business scenarios through prompt engineering without retraining the model.71% similarUnverifiedThe context window refers to the total amount of information a model can process simultaneously in a single conversation, usually calculated in tokens; as the number of conversation turns increases, earlier content gradually exceeds the window range, causing the model to "forget" earlier discussion.70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1026323API
curl https://kongchang.com/api/v1/knowledge/claims/1026323MCP
get_claim(id=1026323)