Unverified50% confidenceFactExact time
MoE uses a gating network to dynamically route each input token, activating only the most relevant few experts, thereby breaking the linear relationship between parameter scale and inference cost.
1
Sources
50%
Confidence
Long-term
Relevance
7/24/2026
First Seen
Sources
开源模型能替代Claude吗？GLM 5.2 vs DeepSeek实测对比
bilibili程序员-智能译站7/10/2026
Related Claims
VerifiedThe MoE architecture divides a model's internals into multiple expert sub-networks, with a gating network dynamically selecting a small number of experts to participate in computation during each inference, so that the actual number of activated parameters is far smaller than the total parameter count.84% similarUnverifiedMoE模型在处理每个token时仅由路由器动态选择少数专家子网络参与计算，其余专家保持休眠82% similarUnverifiedMoE uses a routing mechanism to let each input token dynamically select experts for processing, achieving an efficiency balance between a large total number of parameters and a small number of activated parameters.82% similarUnverifiedThe MoE architecture does not activate all parameters during inference; instead, a router dynamically selects a small number of expert sub-networks to process each token, with each token typically activating only K=2 or K=8 experts.81% similarVerifiedThe MoE architecture uses a gating network to dynamically select the K most relevant experts (typically Top-K, K=2) for each input token, activating only approximately 10%–30% of total parameters during inference.81% similar
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