Compliance
How to Choose a GPU Cloud Provider in Europe
The GDPR checklist most vendor pages won't answer (2026)
When a regulated European team evaluates a GPU cloud, price and GPU model are the easy part — every vendor lists them. The questions that actually decide whether you can deploy are the ones most provider pages quietly skip: where does my data physically run, what is left of it after the job, and can I prove any of it to my DPO? This is the checklist for exactly that.
The three questions that matter more than price
If a workload touches personal data, your GPU provider becomes your data processor under the GDPR. Before comparing hourly rates, get written answers to these three:
1. Where do my models physically execute?
Not the billing entity, not the marketing “EU region” — the actual datacenter. You need it in writing, because your DPO cannot document what the vendor won't state.
2. What happens to my data after the job?
Is the workload deleted immediately? Are logs retained, and for how long? “We take security seriously” is not an answer; a retention window is.
3. Who are the sub-processors, and where are they?
Under Article 28, you approve the whole chain, not just the vendor at the top. A credible provider names every sub-processor, its role, and its location.
An EU region is not the same as EU sovereignty
This is the trap that catches the most teams. A US-owned hyperscaler with a Frankfurt or Paris region still sits under the US CLOUD Act: a US authority can compel the parent company to produce data regardless of where it is stored. An “EU region” checkbox does not remove that exposure. Sovereignty is about who can be compelled, not just where the disk spins.
For most ML workloads this is a documentation problem before it is a security problem: you can run on a US cloud's EU region for years without incident, but you often cannot prove to a regulator or an enterprise customer that the data never left EU control. If that proof matters to your buyers, it belongs on your evaluation checklist.
The EU GPU cloud evaluation checklist
- Does the provider state, in writing, the exact country and datacenter where workloads run?
- Is there a signed GDPR Article 28 DPA available — not just “on request, eventually”?
- Is the full sub-processor chain disclosed, with role and location for each?
- Is data retention defined with a specific window, and deletion confirmable?
- Is the provider (or its parent) outside the reach of the US CLOUD Act?
- Can you leave without lock-in — standard formats, exportable results, clear exit terms?
- Are the security measures (isolation, encryption, access control) documented, not just claimed?
Red flags to walk away from
No DPA, or a generic one
If the provider cannot give you an Article 28 DPA with real sub-processor disclosure, your DPO has nothing to approve. That is a stop, not a negotiation.
Vague on location
“Global infrastructure” or “EU region” with no named datacenter means you cannot document data residency. If they won't write it down, assume the worst.
A faster way to run the checklist
GhostNexus runs Python/ML workloads on GPUs in Nuremberg, Germany — a European provider, outside US corporate reach. You can generate a GDPR Art.28 DPA yourself in about two minutes, pre-filled with the full sub-processor chain and security measures, so half of the checklist above is answered before you even talk to us. Workload files are deleted after each job, results are yours to export, and there is no lock-in.
This article is general information, not legal advice. GhostNexus does not hold HDS certification; whether a given setup fits your obligations depends on your overall architecture and should be confirmed with your DPO or counsel.
Run your ML on an EU GPU cloud — and prove it
Generate your GDPR Art.28 DPA in two minutes, or see how private EU GPU execution works. A 30-day pilot is €299, with no lock-in and no auto-renewal.