Hmm, 24%-42% performance increase (14/16TFlops vs 11.3TFlops) for 70-90% price increase... And prices were already inflated by crypto that is now collapsing. Not sure who is the target market for this tech honestly. Still only 11GB RAM, even if 50% faster, making it a nonsense purchase for Deep Learning enthusiasts (state-of-art models are already larger). Unless somebody invented RTX-based coin of course, then this…
Whether it's substantially better for deep learning depends on whether they chose to neuter fp16 like they did in all other consumer GPUs. The main bottleneck is not actually the size of the model per se (sizes of the models have been mostly going _down_ as of late), it's the size of the batch during training. Both batch size and model size determine the size of the main memory hog: activations that you need to keep…
You won't get double throughput compared to fp32, but you shouldn't fall back to some terribly slow path either.