I'm speaking from my daily experience. Sometimes i don't want to close my laptop before going to bed because there are still 1-2 tasks ongoing in my AI kanban board, so I just leave my laptop open (lock but not suspend it) so that the agents keep working for a while. I don't even have things all that automated.

I anticipate that once I have some more complex agentic scaffolds set up to do things like automatically explore promising directions for the project, then leaving the AI system on overnight becomes a necessity.

I would point out that a beefy desktop is probably faster at compiling code than a typical cloud instance simply due to more CPU performance. So maybe up to 10-ish concurrent agents it's faster to use a local desktop than a cloud instance, and then you start to get into the territory where multiple agents are compiling code at the same time, and the cloud setup starts to win. (That's assuming the codebase takes a while to compile and pegs your CPU at 100% while doing so. If the codebase is faster to compile or uses fewer threads, then the breakeven agent count is even higher.)

Other than that, I agree with what you said. I don't know what the tradeoffs for local on-premises and cloud agents are in terms of other areas like convenience, but I do think that scalability in the cloud is a big advantage.