GetSovereignGPU Cloud: Sovereign GPU Providers & Regions
GPU cloud is the compute layer of sovereign AI. For training and inference to remain in-country, the GPUs must be in-country. This page maps GPU capacity to regions and providers in the directory.
GPU cloud — definition
Bare-metal and virtualised GPU infrastructure (NVIDIA H100/H200 and equivalents) offered as a service, with the accelerator location determining whether AI workloads are resident in the jurisdiction.
GPU capacity by provider
| Provider | GPU line | In-region availability | Notes | Profile |
|---|---|---|---|---|
| Oracle Cloud | OCI Superclusters (up to 131k GPUs) | 🇦🇺 🇮🇳 🇩🇪 🇫🇷 🇬🇧 regions | Largest hyperscaler GPU clusters; Dedicated Region for sovereign | Read → |
| AWS | EC2 p5 (H100), p6 (H200) | 🇦🇺 🇮🇳 🇩🇪 🇫🇷 🇬🇧 regions | Deepest instance catalogue | Read → |
| Microsoft Azure | ND-series (H100/H200) | 🇦🇺 🇮🇳 🇩🇪 🇫🇷 🇬🇧 regions | Azure OpenAI inference in-region | Read → |
| OVHcloud | NVIDIA H100 instances | 🇫🇷 🇩🇪 (EU data centres) | EU-owned GPU capacity; EU AI Act-aligned | Read → |
GPU instance availability varies by region and capacity cycle; verify current SKUs before procurement.
Procurement checklist
- Are the GPUs physically located in the required jurisdiction?
- Can training and inference run in-region, or only inference?
- What happens to weights, checkpoints and logs at contract end?
- Is GPU capacity reserved and guaranteed, or burst/spot?
- Does the provider's AI policy train on customer data by default?