Unverified90% confidenceFactTime unknown
部署MOE模型时必须按总参数量而非激活参数量来估算显存需求，因为所有参数都需要在高速存储中随时可访问
1
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90%
Confidence
Long-term
Relevance
5/31/2026
First Seen
Sources
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Related Claims
UnverifiedIn MoE models, total parameter count primarily determines memory usage, while the number of parameters activated per token primarily determines speed and cost.73% similarUnverifiedThe VRAM usage and inference latency of MoE architectures are calculated based on the number of activated parameters, not the total parameter count.73% similarUnverifiedAll expert parameters of an MoE model need to reside in memory (even when not activated), which is also why ternary quantization is particularly important for MoE.70% similarUnverifiedAll expert parameters of a MoE model must reside in GPU memory simultaneously, and the idle overhead is the primary cost source in engineering deployment of MoE architectures.69% similarUnverifiedModels 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.69% similar
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