> My point, I suppose, is that users of NNs arent interested in the architecture characteristics which affect training -- they're interested in how capable any

> My point, I suppose, is that users of NNs arent interested in the architecture characteristics which affect training -- they're interested in how capable any given model will be. Yes. A more helpful bit of information could be what the model was pre-trained on. Assuming they’re trying to refine it for a more specific task. Size is helpful for “what can I run on my machine” (or how much would it cost to run on a server.) Not all models are created equal, given a byte size, for a given task.