Unverified50% confidenceFactExact time
A typical MoE configuration such as Mixtral 8x7B has 8 experts per layer, and each token is routed to only 2 of them, with the parameter count activated in a single pass being about one third of the total (plus shared weights).
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Long-term
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10/13/2026
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VerifiedMixtral 8x7B模型拥有8个专家，每个Token只激活2个，总参数量达到47B，但单次推理的计算量仅相当于一个13B参数的稠密模型72% similarUnverified在MoE模型中每个token只激活少量Expert（通常2-4个，Top-K路由），实际计算量可能仅相当于6-7B的Dense模型72% similarUnverifiedIn the MoE architecture, the Mixtral 8x7B model has a total of 46.7B parameters, but only approximately 12.9B parameters (2 experts) are activated per token, making inference costs close to those of a 13B dense model while achieving performance comparable to the 70B level.67% similarUnverifiedMixtral 8x7B的实际激活参数量仅为总参数量的约1/463% similarUnverifiedThe intelligent routing solution passes 9/12 (75%) tasks and Opus passes 11/12 (92%); of the three failures, two unit test tasks and one QA task were routed to Claude Haiku 5.5, whose responses exceeded the 8,000-token limit.61% similar
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