How 125B-Parameter AI Models Work by Activating Only a Fraction at a Time

Large AI models can carry 125 billion parameters yet activate only around 6 billion for each token they process, a design that puzzles many users encountering these specs for the first time. This is made possible by an architecture called Mixture of Experts (MoE), where the model is divided into multiple specialized groups of parameters known as experts. A routing component decides which experts are engaged for any given token, meaning the full parameter count is never used all at once. The approach allows developers to build models with vast total capacity while keeping per-token computation manageable and efficient. As a result, a 125B MoE model can deliver broad capability without the cost of running all 125 billion parameters on every single inference step.