Artificial intelligence hardware memory capacity determines which models and context sizes can fit on a system. The deployment must accommodate model weights plus key-value cache, temporary activations and software overhead, not just the model file itself.
More capacity expands model choice and concurrency, but it does not guarantee speed. Memory bandwidth, processor capability, device communication and software support determine how effectively the installed memory can be used.
