Yes, the inefficiency here is the sheer number of models that are served. Instead of every worker having SDXL and loading LoRAs, the worker is very rapidly switching between one of ~230 models... _and_ loading LoRAs, if the worker allows it! From discussions I've seen, there is a lot of encouragement to use LoRAs (and textual inversions) instead of a unique model, but there's still a lot of demand among clients for unique base models. Additionally, being a volunteer system, a lot of the workers are, well, strange. You have people contributing high-end GPUs, and then other people are trying their best to (abuse?) use Colab and Kaggle within whatever their TOS allows, so the capacity of the workers varies quite a bit.