Unverified50% confidenceFactExact time
Activated parameters refer to the scale of parameters that actually participate in floating-point operations when the model processes a single token, usually equal to the parameters of the selected experts plus the parameters of the shared layers and attention parts.
1
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50%
Confidence
Long-term
Relevance
10/15/2026
First Seen
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Related Claims
UnverifiedIn dense models, all parameters participate in computation for every token, and the amount of computation is strictly tied to the parameter scale.79% similarUnverifiedActive parameters describe the portion involved in computation per token, not the model's download size or the memory required to load it.76% similarUnverifiedTotal parameter count reflects the upper limit of a model's knowledge capacity and expressive power, while activated parameter count determines the computational cost and latency during inference.73% similarVerifiedModels with extremely large parameter scales typically adopt the MoE (Mixture of Experts) architecture, which activates only a portion of parameters per inference rather than computing the full set.73% similarUnverified模型参数需要同时服务于记住具体事实和泛化推理规则两个相互竞争的目标，会争夺参数空间72% similar
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