Verified65% confidenceTradeoffExact time
Fine-tuning MoE models typically requires loading all parameters and their corresponding optimizer states, placing far greater demands on hardware resources than dense models with equivalent activated parameter counts.
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65%
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8/24/2026
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Unverified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79% 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.79% similarUnverifiedMoE models can handle more concurrent requests on the same hardware, or serve larger model capacity within the same latency budget.78% similarUnverifiedA dense model refers to the traditional architecture in which all parameters participate in computation during each inference, as opposed to sparse architectures such as MoE.78% similarUnverifiedMoE模型在推理延迟和计算成本上往往优于同参数规模的Dense模型，但代价是需要更大显存加载全部专家权重78% similar
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