Unverified50% confidenceFactExact time
LLM models have no memory; every loop iteration requires resending the entire message array from the first message, and all previous content is billed again each round.
1
Sources
50%
Confidence
Long-term
Relevance
10/10/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedLLM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76% similarVerifiedThe memory of LLMs depends on the context window, which is the maximum number of tokens the model can process in a single inference.74% similarUnverifiedDuring each inference, an LLM only processes the token sequence of the current input and does not retain persistent state across sessions (statelessness).74% similarUnverifiedThe current mainstream LLM applications adopt a stateless interaction model, where the model itself does not retain cross-session memory and all context must be temporarily fed in via prompts.73% similarUnverifiedLLMs generate text in an autoregressive manner, producing only one token at a time, requiring N forward inference passes to generate N tokens, with latency scaling linearly with output length.72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/995122API
curl https://kongchang.com/api/v1/knowledge/claims/995122MCP
get_claim(id=995122)