> distributed LLM inference
This seems extremely inefficient considering data transfer between model layers if the model is distributed. I found this project called Petals that claim up to 4 tok/s for a 180B model although its repository hasn't been updated in two years.
For token generation, yes: because current-gen LLMs are autoregressive you need to add the inter-node latency for every since token.
For prompt processing it would work though, and it could for diffusion LLMs as well.