Everyone posts about their home-lab GPU setup. Almost nobody posts about the operational reality of running one. A few notes from my own, in the spirit of transparency.
Heat is the constraint. A single workstation GPU under load produces meaningful heat in a residential room. Two of them can make a small room uncomfortable in summer. I ended up segregating the compute into a separate space with its own HVAC. This is the hidden cost nobody mentions in the build posts.
Power is the other constraint. The GPU draws power. So does everything adjacent to it. My lab is on a dedicated 20A circuit, which is enough for current use but would need upgrading if I added another GPU. Home electrical is not built for always-on compute loads.
Remote access is essential. I quickly learned that I did not want to be physically in the lab room when it was running. VPN into a bastion, SSH into the compute node, run experiments remotely. The lab is infrastructure; I do not want to sit next to it.
Cloud still wins for bursty work. I own the lab because I do a lot of steady-state experimentation. If my workload were a few 10-hour training runs per month, I would rent spot instances and save money. The home lab is worth it because I am running things most of the time, not because it is cheaper per hour.
Would I do it again? Yes. The iteration speed of running experiments on hardware I own, whenever I want, with no billing anxiety — that is worth the operational cost. But the operational cost is real, and the build-post aesthetic systematically understates it.
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