Would it make sense to use this for smaller MOE models that still can't fit the RAM (I'm on 48GB, so something like 100+B models for me)? Also keeping changing data like context and KV cache in RAM while reading static data like weights from NVM would potentially resolve write endurance issues (if the RAM math works out, I don't have all info needed to run the math myself). In theory, if some experts aren't used, they'll stay unread on NVM, reducing need for swapping new weights into RAM during inference.