Verified75% confidenceFactTime unknown
Large models are essentially stateless; during each inference, the model can only see the token sequence in the current input and has no persistent memory storage.
5
Sources
75%
Confidence
Long-term
Relevance
5/31/2026
First Seen
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Related Claims
Unverified大模型是无状态的，每次API调用对模型来说都是一次全新的推理过程，完全依赖messages列表来回忆之前发生的事情79% similarVerifiedThe inference stage of large models is memory-bound (limited by memory bandwidth); generating each token requires reading the entire model weights from VRAM, resulting in extremely low computational intensity.78% similarUnverifiedEven if a model can retrieve relevant memory context, it does not necessarily truly constrain its own behavior during generation based on that context (writing to memory does not equal following memory)76% similarUnverified传统大模型天然是无状态的，每次推理都是独立的前向传播过程，没有持久化的外部记忆，也没有与环境交互的接口76% similarUnverified大语言模型是无状态的文本预测系统，每次推理调用仅接收当前输入的Token序列，不存储跨请求的持久化状态75% similar
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