Converting weights to float16 after training will reduce quality/accuracy whereas mixed precision has a negligible effect on quality/accuracy and dramatically i

Converting weights to float16 after training will reduce quality/accuracy whereas mixed precision has a negligible effect on quality/accuracy and dramatically improves performance. If you really just want to save memory, there's plenty of other low hanging fruit. It's just not a priority for most devs since mid tier GPUs start at 10GB whereas a typical model only has 0.5GB weights. Activations and intermediate calculations use way more memory.