Mixture of Experts (MoE)
概念
核心技术
Huge capacity, small bills: only a few experts fire per token.
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An MoE model holds many expert sub-networks but routes each token through only a few — DeepSeek-V3 stores 671B parameters yet computes with 37B per token. That decouples capacity from cost and is how open labs reached frontier scale on constrained hardware. The trade: all those parameters still occupy memory, which pushes HBM demand even higher — an architecture choice you can read directly in the memory market.
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记录审阅截至 2026-01-15 — 查看 方法论.