Know the bill before you run anything.
Add what the workload needs.
Questions procurement asks.
There is no platform fee on deeplit® Cloud. You pay for the GPU hours you run, and the core is what runs on them: model serving, the catalog, users, API keys, audit log, SSL, and monitoring. Modules are licensed separately.
Buying GPUs and self-hosting runs about €170k to €390k in year one, where hardware is a fifth of it and engineers are the rest. Building a private deployment in your customer's cloud is about €60k to €120k of engineering. Letting the deal slip costs about €50k to €250k, and the next buyer asks the same question.
A GPU does bounded work in an hour, so cost has a ceiling a token meter does not. Heavy users cost what light users cost, and finance gets one number to forecast. Your dashboard counts tokens; your invoice never does.
Private is priced on your users, your load, and your hardware, and every deployment is its own case. A short call settles all three, with the modules you license. Cloud needs none of that, which is why you can start it yourself.
You provide a GPU server you own, in your building or colocation, plus deployment access. Everything above that is ours to build and hand over, and running it needs no ML expertise on your side.
When traffic is spiky or occasional. Flat wins on predictability and sustained use, so light bursty work can be cheaper on a public AI API. We will say so.
No. deeplit® Cloud is funded up front, so you only run what you have paid for. An instance bills while it runs and stops when you stop it.