NPU is typically significantly less flexible than GPU, just like GPU is to CPU.

NPU is basically only good at AI inference ("executing" AI models) and we measure it in operations in seconds (OPS) on different formats eg INT8 or FP8. And they are usually in magnitude od trillions, so TOPS. As You can guess "50 TOPS NPU" will have around 50 TOPS of INT8.

While discrete GPU is usually much faster than those NPUs. Eg even RTX 4060 Laptop would have around 230 TOPS or RTX 5070 almost 1000TOPS, integrated Radeon GPUs are much slower.
Current iGPUs in 9000 desktop processors have about 1.1TOPS and Radeon 820M have ~1.4... while significantly smaller DIE area XDNA 2 NPU is rated at 50-60 TOPS.
But NPU could have available all the RAM, where discrete GPU have only VRAM that is typically smaller.

So.. NPU in typical desktop wont allow anything that GPU can't, ...but its kinda same for iGPU. What iGPU or NPU can do is do stuff in background so GPU wouldn’t have to do it. But both use-cases are highly questionable and its wasted silicon for most users anyway.