Colocation means placing organization-owned servers in a data center operated by a specialist provider. The provider generally supplies physical space, electrical power, cooling, building access controls and network connectivity options. The customer remains responsible for the servers, operating systems and applications unless extra managed services are purchased.
For AI infrastructure, colocation can avoid the cost of constructing a facility while allowing control over GPUs and other components. Pricing may depend on rack space, power capacity, contracted usage, cross-connects and support services. High-density GPU systems can require power and cooling arrangements beyond an ordinary server rack.
The cost is not only the monthly facility bill. Hardware purchases, shipping, repairs, network transport, staffing and replacement parts still matter. Long contracts, limited local capacity and hands-on maintenance can reduce flexibility compared with renting cloud instances for a short experiment.
When comparing colocation with public cloud, calculate total cost over the intended hardware life. Confirm service levels, power density, remote-hands support, security responsibilities and what happens when a GPU fails or the application outgrows the reserved rack.