模型参数

The learnable numbers inside a model, usually measured in billions (B).

Parameter count is the main proxy for model scale: more parameters mean more capacity and usually stronger capability, but also higher training and inference cost. 7B, 70B and 671B denote parameter counts. For MoE models, activated parameters better reflect inference cost.