Hey all. I'm exploring the idea of building a desktop PC optimized for running LLMs locally. My two primary use cases are I'd like to be able to add local documents and then talk to my files; I'd also like to use it as a coding assistant. Lower priority use case but something I'm tangentially interested in is image generation using stable diffusion. I don't plan to do any model training, I'll leave that to the pros.

One of the decisions I'm currently working through is whether to create this as a desktop workstation (like a PC build) or as more of a homelab environment (like a "local cloud"). On one hand, I believe a desktop workstation would be easier for me to wrap my head around b/c I've built several gaming PCs, whereas I have no homelab or self hosting experience beyond running a local-only Jellyfin instance on an old laptop. On the other hand, I like the thought a separate, atomic AI hub as like a local cloud if you will, similar to how I think of the NAS as a separate thing. What I like about the separate local cloud thinking is In both cases, the AI hub and/or the NAS can be accessed from any device.

I would like to strike the right balance between budget, power efficiency, and speed. I don't need to set any land speed records, but I would also like to avoid waiting several minutes for responses. I can probably spend up to $2,000 on this project, and I'm located in the US.

My questions for those the community who've gone before me:

• Has anyone build built a desktop workstation and then wished they built it as a server?
• Is there actually much of a difference between a desktop workstation versus a homelab environment when it comes to hardware for AI tasks?
• What other questions I should be asking myself to decide which way to go?

Thanks!