Three paths, three different commitments
Teams that need AI compute usually end up choosing between renting GPUs from a cloud or specialist provider, placing their own hardware in a colocation facility, or building their own site. These are not three prices for the same thing. They differ in who owns the hardware, who operates it, how quickly you can start, and how hard it is to change course later.
GPU cloud and dedicated rental
Renting is the fastest way to start. You use GPUs that someone else bought and operates, and you pay for what you use or commit to. It keeps capital free and lets you scale in steps. The trade-offs are less control over hardware choices and networking, pricing that can be higher over long horizons, and dependence on the provider's supply. For uncertain or fast-moving workloads, flexibility often outweighs the premium.
Colocation with your own hardware
Colocation means you buy and own the servers and lease space, power and cooling from a facility. You control the stack, the networking and the refresh cycle, and over a long period your cost per unit of compute can be lower. You also take on the purchasing, deployment and operations burden, and you need a facility whose density and cooling match modern GPU racks. Not every colocation hall can host them.
Building your own
Owning the site gives maximum control and can make sense at very large, long-lived scale. It also takes the longest and carries the most risk: land, power interconnection, permitting, construction and equipment lead times all sit on your critical path. Most organizations that think they want to build are better served by leasing at first and revisiting the question once their demand is proven.
The questions that decide it
- How certain is your demand over the next three years?
- How fast do you need capacity online?
- Do you have the team to operate hardware and a facility relationship?
- How much capital do you want tied up in equipment?
- How specific are your needs on networking, density or location?
Hybrid is normal
Many teams mix approaches: rented capacity to start immediately, colocation for the stable core of their workload, and a longer-term plan for scale. The mistake to avoid is committing to the heaviest option before the lighter ones have taught you what you actually need.
Not sure which fits? Talk to an expert and we will help you size the decision.