The weights are preprocessed into integer quants combined with scaling factors in various configurations (4, 5, 8-bits and recently more exotic 2, 3 and 6-bit quants). At runtime, we use efficient SIMD implementations to perform the matrix multiplication at integer level, carefully optimizing for both compute and memory bandwidth. Similar strategies are applied when running GPU inference - using custom kernels for fast Matrix x Vector multiplications
Yes, but to my knowledge it doesn't do any of the complicated optimization stuff that SOTA quantisation methods use. It basically is just doing a bunch of rounding.