Mixture of Experts: Why Sparse Routing Scales Models Without Scaling Compute
A dense transformer pays for every parameter on every token. Double the model, double the compute, no matter how easy the token is. Mixture of Experts (MoE) breaks that bargain. It keeps a huge pool of parameters available, but activates only a small subset for each token. The result is a model tha…
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- 2026-10-28 05:04 · DEV Community — Machine Learning
Mixture of Experts: Why Sparse Routing Scales Models Without Scaling Compute