OVHcloud on Hugging Face Inference Providers 🔥

We're thrilled to share that OVHcloud is now a supported Inference Provider on the Hugging Face Hub! OVHcloud joins our growing ecosystem, enhancing the breadth and capabilities of serverless inference directly on the Hub's model pages. Inference Providers are also seamlessly integrated into our client SDKs (for both JS and Python), making it super easy to use a wide variety of models with your preferred providers.

This launch makes it easier than ever to access popular open-weight models like gpt-oss, Qwen3, DeepSeek R1, and Llama — right from Hugging Face. You can browse OVHcloud's org on the Hub at https://huggingface.co/ovhcloud and try trending supported models at https://huggingface.co/models?inference_provider=ovhcloud&sort=trending.

OVHcloud AI Endpoints are a fully managed, serverless service that provides access to frontier AI models from leading research labs via simple API calls. The service offers competitive pay-per-token pricing starting at €0.04 per million tokens.

The service runs on secure infrastructure located in European data centers, ensuring data sovereignty and low latency for European users. The platform supports advanced features including structured outputs, function calling, and multimodal capabilities for both text and image processing.

Built for production use, OVHcloud's inference infrastructure delivers sub-200ms response times for first tokens, making it ideal for interactive applications and agentic workflows. The service supports both text generation and embedding models. You can learn more about OVHcloud's platform and infrastructure at https://www.ovhcloud.com/en/public-cloud/ai-endpoints/catalog/.

See the list of supported models here.

How it works

In the website UI

In your user account settings, you are able to:

• Set your own API keys for the providers you've signed up with. If no custom key is set, your requests will be routed through HF.
• Order providers by preference. This applies to the widget and code snippets in the model pages.