I don’t really get why anyone would be buying ai compute unless A) to your goal is to rent out the compute B) no vendor can rent you enough compute when you need it C) you have an exotic funding arrangement that makes compute capex cheap and opex expensive. Unless you can keep your compute at 70% average utilization for 5 years - you will never save money purchasing your hardware compared to renting it.
$3,000 is well under many "oopsie billsies" from cloud providers.
And that's outside of the whole "I own it" side of the conversation, where things like latency, control, flexibility, & privacy are all compelling reasons to be willing to spend slightly more.
I still run quite a number of LLM services locally on hardware I bought mid-covid (right around 3k for a dual RTX3090 + 124gb system ram machine).
It's not that much more than you'd spend if you're building a gaming machine anyways, and the nifty thing about hardware I own is that it usually doesn't stop working at the 5 year mark. I have desktops from pre-2008 still running in my basement. 5 year amortization might have the cloud win, but the cloud stops winning long before most hardware dies. Just be careful about watts.
Personally - I don't think pi clusters really make much sense. I love them individually for certain things, and with a management plane like k8s, they're useful little devices to have around. But I definitely wouldn't plan to get good performance from 10 of them in a box. Much better off spending roughly the same money for a single large machine unless you're intentionally trying to learn.