GPU as a Service, chosen on your numbers rather than a vendor's.
GPUaaS gives you accelerated compute without running the infrastructure: the provider owns the hardware, the facility and the operations, and you consume capacity. It is the right answer for a specific shape of team, and the wrong one for others. We source it buyer-side, which means we are equally happy telling you to buy instead.
Reserved bare-metal capacity from vetted providers, on their direct terms. We read the agreement line by line before you sign it, because the utilisation floor and the exit move more money than the hourly rate ever does.
Capacity without an operations team.
The arithmetic in full: what GPUaaS actually costs against owning, reserved versus on-demand break-even, and the five clauses that beat the rate.
The honest case for GPUaaS is operational rather than financial. If your team should be shipping models rather than managing schedulers, firmware, spares and facility relationships, then paying someone else to run the metal is rational even at a premium. Time to first training run is measured in days rather than the months an owned deployment takes, and the orchestration layer arrives with it.
It also suits demand you cannot forecast. Where the workload genuinely spikes and collapses, consumption pricing means you stop paying when the work stops, which no reserved structure will do for you.
What you give up is the bottom of the cost curve and a degree of control. At sustained high utilisation, GPUaaS costs meaningfully more than reserved bare metal for the same silicon, and you inherit whatever the provider decides about hardware refresh, tenancy and priority.
Two or three that genuinely fit, with the reasoning.
KYC runs before any introduction, and the desk turns work away when a requirement or its end user cannot clear. That discipline is why suppliers quote real numbers into our files.
The wider decision frameworks sit on the comparison pages, and the definitions behind the terminology on the glossary.
We hold no inventory and take no position, so the shortlist is built from what actually suits the workload: fabric quality for distributed training, geography for inference latency, residency for regulated data, and the commercial terms underneath. We know which providers deliver on their published specification and which ones are selling a slide.
Then we price the alternatives beside it. If a reserved bare-metal lease at your utilisation costs materially less than the GPUaaS quote, you will see that comparison rather than a pitch, because our compensation does not depend on which structure you choose.
Real stock, real structures.
Current verified lines with quantities, lead times and indicative pricing are public on the live inventory. The buying structures sit on the procurement desk and the leasing desk, and the decision frameworks are in buy versus lease and cloud versus bare metal.
Where the desk sits in this purchase.
A cleared file gets real numbers. That is the whole mechanism, and it is why the compliance work comes before the price conversation.
The desk sits at the gate on your side, so the contract runs supplier to buyer
Asked first, answered straight.
GPUaaS is managed: the provider runs the hardware, facility and often the orchestration, and you consume capacity through their platform. Bare metal hands you the whole node and the whole fabric with nothing between you and the silicon, at a lower rate and with the operational burden on your side.
Per unit of compute at sustained utilisation, usually yes. The premium buys operations you would otherwise staff for. Whether it is worth it is a question about your team, not your hardware, and it is worth answering deliberately rather than by default.
That is often the right design: a reserved baseline for the work you can forecast, GPUaaS or on-demand for the layer you cannot. The mistake is running a predictable baseline on consumption pricing.
No. We hold no inventory and take no position in the deal. You transact with the provider on their direct terms and our compensation sits on the supply side, disclosed.
Days to a few weeks for standard configurations with a provider that genuinely has capacity, which is materially faster than any owned or racked deployment. Verifying that the capacity is real is the part we do before you commit.
Working through this on a real requirement?
Twenty minutes with the desk, no pitch and no quote at the end of it. Tell us roughly what you need and we will come back within one business day.
Sent. We are on it.
Your enquiry has landed with the desk. Acknowledged within one hour.