Yeah, my thinking was definitely biased to my environment. I selfhost llama.cpp so even if Hivekeep doesn’t require significant resources, whatever LLMs it runs will use my hardware.

agents are activated serially per message, not all firing at once, and the persistent memory is exactly what keeps each context small

It sounds like I need to try it!

This looks interesting, especially the persistent memory. I want to try it out but it seems likely to me that multiple simultaneous agents would require significant hardware. Even if they were serially activated, reloading contexts with each switch would take time. I have a pretty beefy GPU and experience significant (almost ridiculous) slowdown when opencode runs 2 subagents simultaneously.

But perhaps the memory storage/lookup keeps contexts very small?

Anyway, I can’t find any mention in the repo or docs what the suggested minimum hardware is.