ATraining a small student model to imitate a larger teacher model
BTraining a large model on the outputs of many smaller models
CRemoving low-importance weights to shrink an already-trained model
DLowering the precision of a model's weights to save on memory
Why this is the answer
Distillation transfers behavior from a big teacher into a compact student that is cheaper to run. Removing weights is pruning; lowering precision is quantization.