Cloud GPUs are convenient - and expensive. For sustained AI workloads, colocating hardware you own is often dramatically cheaper.
Renting a high-end GPU in the cloud can cost several dollars per hour. Run it around the clock for a year and you have often paid many times the cost of the hardware itself. Cloud pricing is built for burst and convenience, not for compute that runs 24/7.
If your GPUs sit mostly idle, cloud can make sense. But the moment you have steady training or inference running near full-time, the math flips hard toward owning the hardware and paying only for power and space.
With colocation you pay for two things: power (your kW multiplied by your electricity rate) and space and cooling (a monthly rate per kW). For a busy GPU fleet, that total is typically a small fraction of the equivalent cloud bill.
Use our colocation vs. cloud calculator to estimate your own savings, then ask us for an exact quote.