A single high-end GPU already pulls 300–450W under load. Put two or three of them in one chassis for AI training or render farming, and the power supply stops being an afterthought — it becomes the component most likely to bottleneck or crash the whole build if it's undersized.
GPU-maker "recommended PSU" figures assume a single card and a modest rest-of-system. They don't scale linearly once you add a second or third GPU, because the CPU, storage array, and fans are drawing their own separate load on top. The right way to size a PSU is to add up every component's actual rated draw, not the smallest GPU-vendor number times the GPU count.
| Component | Typical draw (multi-GPU build) |
|---|---|
| 2–3× high-end GPU | 600–1,350W combined |
| High-core-count CPU | 150–280W |
| NVMe/SSD array + fans/pump | 40–80W |
| Motherboard + RAM | 60–100W |
A workstation that runs multi-hour training jobs or render queues draws near-peak power for long stretches, not in short bursts like a typical desktop. A few points of PSU efficiency compounds into a real difference in heat output and electricity cost over months of near-continuous use — worth the premium on a build that's actually going to run like this.
Every ProStation AI/ML workstation and render build is PSU-sized against the real component list, not a rounded-up guess — including connector count and continuous-load headroom. Configure your build or talk to us via a free consulting call if you're planning a multi-GPU rig.