Unverified50% confidenceFactExact time
Conversational large models output natural language tokens, whereas vector models output a fixed-length vector, for example 1536 dimensions or 1024 dimensions.
1
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50%
Confidence
Long-term
Relevance
10/12/2026
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Unverified大语言模型的用量计费通常基于token（词元）消耗，而非简单的对话次数78% similarUnverifiedCurrent mainstream large language models (such as GPT, Claude, etc.) adopt a session-based interaction mode; the context window has expanded from an initial 4K tokens to 128K or even longer, but it remains essentially a single-conversation memory mechanism, and implicitly accumulated knowledge is lost once a new session begins.71% similarUnverifiedText generation in large language models is autoregressive, and the number of output tokens is nearly proportional to response time69% similarUnverifiedBefore working with large models, the largest NLP and speech recognition models Lao Xiao's team built had only 4,000 parameters.68% similarVerifiedIn the conversational architecture of large language models, the System Prompt has the highest priority and can continuously influence the behavioral boundaries of the model throughout the entire session.68% similar
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