Parameters
The learned weights of a neural network; the "parameter count" (e.g. 70B) is a rough proxy for a model’s size and capacity.
Parameters are the numbers adjusted during training. More parameters generally means more capacity (and more compute/memory to run), though architecture, data quality, and training compute often matter more than raw count. Mixture-of-experts models report both total and active parameters.