>Chinchilla implicitly assumes that the majority of the total cost of ownership (TCO) for a LLM is the training cost. In practice, this is only the case if you’

>Chinchilla implicitly assumes that the majority of the total cost of ownership (TCO) for a LLM is the training cost. In practice, this is only the case if you’re a researcher at a research lab who doesn’t support products (e.g. FAIR/Google Brain/DeepMind/MSR). For almost everyone else, the amount of resources spent on inference will dwarf the amount of resources spent during training. I'm not so convinced, especially if people are doing multiple training runs for hyperparameter tuning, cleaning data, fixing bugs, etc. I would be very interested in knowing what portion of OpenAI's compute budget is training. I would not be surprised if it was a significant minority.