7 best GPU clouds for self-hosting large models in Europe in 2026 (and where OVHcloud's B300s actually fit)

European GPU clouds are increasingly viable for self-hosting open-weight models, particularly for steady-state inference and smaller fine-tuning workloads requiring EU data residency and jurisdiction, although hyperscalers retain advantages in large-scale, multi-node training capacity and surrounding managed services. The comparison ranks OVHcloud first for sovereign inference due to its French jurisdiction, comparatively low published GPU prices, included egress, and managed Kubernetes support, followed by Scaleway, Nebius, CoreWeave, AWS, Google Cloud, and Azure, with Hetzner presented as a lower-cost but operationally demanding bare-metal alternative. NVIDIA Blackwell Ultra B300 GPUs increase available memory to up to 288 GB per GPU and can reduce the number of GPUs needed for models such as Llama 3.3 70B, but OVHcloud had not yet published B300 pricing, regions, quotas, or interconnect details as of November 7, 2026. The assessment emphasizes that capacity availability, sovereignty, egress charges, and the operational work required to build reliable inference services often matter more than raw GPU specifications. It also argues that self-hosting becomes economically attractive only at sufficiently high GPU utilization, while per-token APIs may be cheaper for intermittent workloads. Teams are advised to maintain portability through Kubernetes, provider-neutral deployment configurations, stable inference APIs, and careful management of GPU drivers, model loading, autoscaling, observability, and data sovereignty across the entire platform stack.

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