Unverified50% confidenceFactExact time
Switch Transformer and Mixtral 8x7B are typical representatives of the MoE architecture, with a large total parameter count but only a subset of experts activated each time.
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50%
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Long-term
Relevance
10/15/2026
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UnverifiedGoogle 的 Switch Transformer（2021）和 Mistral 的 Mixtral 8x7B（2023）都采用了稀疏 MoE 架构，即每次前向传播只激活少数几个专家77% similarUnverifiedSwitch Transformer and the Mixtral series have widely adopted the MoE architecture.73% similarVerifiedThe MoE architecture replaces the FFN layer of a standard Transformer with N parallel expert sub-networks, and selects the Top-K experts (typically K=2) for computation each time via a gating routing network, achieving sparse activation.68% similarUnverifiedGoogle's Switch Transformer and Mixtral 8x7B are classic representatives of the MoE architecture, and Qwen3, DeepSeek-V3, and others also adopt this architecture.67% similarVerifiedThe MoE architecture replaces the feed-forward network layers of the Transformer with multiple parallel expert sub-networks, dynamically selecting 2–4 experts to activate for each token via a routing network.65% similar
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