[siver_john]

As someone who used various types of GPUs in graduate school. For most simulations, and even machine learning (unless you need the VRAM) you are generally better off going with a consumer card. There is generally about the same number of CUDA cores and the higher clock speeds will generally net you better performance overall.

Simulations where this isn't true is any that need double floating point (which you previously were able to do in the Titan series of consumer-ish cards). And where it is super important for DL is the VRAM it allows you to use much larger models. Plus the added features of being able to string them together and share memory which is an important feature that has been left off consumer cards (honestly in a way that makes sense because SLI has been dumb for some time).