Mixture of Experts (MoE) Model Architecture ExplAIned Meta’s new open source model Muse Spark Open just dropped, and it uses this foundational architecture called the Mixture of Experts architecture. Pretty much every AI model released today uses it, and it’s founded on this premise: a huge AI model doesn’t have to activate all its parameters for every input. With mixture of experts, or MoE, a router decides which expert networks to activate for each token. Instead of using the entire model every time, it selects specific experts, saving compute and processing time. The total parameter count can be huge, but only a fraction is active at any given time: the parameters of the selected experts, plus shared parameters used for every input. That’s what makes MoEs so powerful: the learning capacity of much larger models, while using only what they need for each input.