FP16 multipliers are smaller (in terms of silicon footprint), which means that you can fit more of them on a given silicon die, and they use less power than FP3

FP16 multipliers are smaller (in terms of silicon footprint), which means that you can fit more of them on a given silicon die, and they use less power than FP32. The other advantage is that FP16 uses half as much memory, meaning that FP16 operations require half as much memory traffic, which can lead to faster computations. It can also allow you to fit models on your GPU which have twice as many parameters. The reason you don't typically have FP16 on CPUs is that in the CPU world, cache dominates die area and power usage. The floating point ALU component of a CPU is relatively tiny. Still, even in the CPU world, Intel recently added instructions to convert to/from FP16 before operating on it, because they know there is a memory bandwidth advantage in using a smaller floating-point format.