It’s not totally clear what you are asking. The models are trained on something like an NVIDIA A100 which is a super high end machine learning processor, but in

It’s not totally clear what you are asking. The models are trained on something like an NVIDIA A100 which is a super high end machine learning processor, but inference can be run on a home GPU. So this is a “different configuration”. But I think maybe you mean, can they make a model which normally needs a lot of RAM run more slowly on a machine that only has a little RAM? It sounds like there are some tricks to allow the use of smaller amounts of ram by making specific algorithmic tweaks, so if a model normally needs 12GB of VRAM then, depending on the model, it may be possible to modify the algorithm to use 1/2 the RAM for example. But I don’t think it’s the same as other rendering tasks where you can use arbitrarily less compute and just run it longer. Maybe I’m wrong though.