Conceptually, the training process is like building a massive and highly compressed index of all known results. You can't outright ignore the power usage to build this index, but at the very least once you have it, in theory traversing it could be more efficient than the competing indexes that power google search. Its a data structure that's perfectly tailored to semantic processing.

Though, once the LLM has to engage a hypothetical "google search" or "web search" tool to supplement its own internal knowledge; I think the efficiency obviously goes out the window. I suspect that Google is doing this every time you engage with Gemini on Search AI Mode.