What NVIDIA GPU specs are most important for Video Enhance AI performance (quickest run times)?(Consider two cases: (1) 480p-1080p and (2) 1080p-8K) (My guess is that different use cases are bottle-necked by different specs. But that’s just a wild guess…)
Ideally, rank the top three specs.
(For example: 1: Number of tensor cores; 2: Video RAM ; 3: Memory interface (bandwidth).)
I’ve been looking for this information, and it does not appear to be available on Topaz forums or 3rd party review sites. I’m well aware of the suggested minimum requirements, but these recommendations don’t include any information as to “why” specific cards are better (or even a frame of reference for theoretically comparing cards).
NVIDIA will be releasing a new line of cards starting next month, Sept. 2020, and many users might be considering upgrading soon. Without knowing what specs affect performance we have no way of making an informed decision about what the best upgrades will be. For example, maybe the RTX 2080’s will perform similarly to the "3080"s (or whatever they will be called). So, it would make more sense to find a good deal on a 2080 than to buy the “newest” model.
Secondarily, maybe, all things being equal, RAM ends up being the bottleneck if your workflow tends to include 4K and 8K upscaling. So, you might be better off prioritizing a model with more RAM (or increased memory bus). But, I don’t really know enough to make an educated guess, at least not enough to warrant spending hundreds of dollars “just to find out”.