Sparse Routing Mechanism
A learned gating network determines which experts activate for each input token, enabling selective parameter activation.
Scalable Capacity
Allows models to grow to extreme parameter counts while keeping inference practical by activating only relevant subnetworks.
Expert Specialization
Individual experts are optimized for narrow behavioral domains rather than general-purpose processing.
Efficiency Gains
Inference cost remains low despite massive parameter increases; for example, a model with 40× more parameters only increases inference time by about 2%.
Variants
Includes Basic MoE, Sparse MoE for large language models, and Shared Expert Sparse MoE combining specialized and global processing streams.