Running AI on your own hardware: what it takes
Last updated: November 02, 2026 · Author: Private AI Luxembourg editorial team
In short
A private model needs a machine with a suitable graphics unit, power and cooling, and someone who installs updates. If you would rather not keep that in-house, the same model runs in a data centre in the Greater Region – in both cases your data stays within your reach.
The two ways of running it
| Your own server | Data centre in the Greater Region | |
|---|---|---|
| Investment | one-off hardware | monthly service |
| Power and cooling | your task | part of the building |
| Access from outside | over your own line | over managed access |
| Growth | new hardware | book more capacity |
What determines the hardware
Not the processor but the memory of the graphics unit. It decides which model size runs and how many people can work at the same time. Everything else – storage, memory, network – follows from that.
What running it involves
A model is not a purchase but a service: updates, access, logs, a backup of the configuration. Leave that out and after a year you own a machine nobody touches.
The question that settles it
How many people will use it, and how often? For a single department a machine in-house is enough. As soon as several sites and varying load come into play, the data centre is the calmer route.
What you can do now
Decide how many people should work with it at the start. That number determines the hardware – not the other way round.