Hugging FaceGilles Closset, Fabien Ric, Elias TourneuxAnnouncement
OVHcloud on Hugging Face Inference Providers 🔥
Summary
OVHcloud is now integrated as a supported Inference Provider on the Hugging Face Hub, expanding serverless inference options across model pages and client SDKs. The integration enables access to open-weight models, including gpt-oss, Qwen3, DeepSeek R1, and Llama, using European infrastructure with pay-per-token pricing starting at €0.04 per million tokens. Developers can connect via Python and JavaScript SDKs using either direct custom API keys or automatic routing through Hugging Face tokens. The service supports structured outputs, function calling, multimodal workflows, and embedding models while providing sub-200ms first-token response times. Calls routed through Hugging Face pass through standard provider pricing without markups, and PRO tier subscribers receive monthly inference credits.
Context
Hugging Face expanded its ecosystem of serverless inference providers to give users more access to frontier open-weight AI models through both direct provider accounts and routed Hub workflows.
Approach / What changed
OVHcloud was integrated into the Hugging Face Hub model pages and official Python and JavaScript client SDKs, allowing users to execute inference via custom OVHcloud API keys or routed Hugging Face authentication.
Takeaways
OVHcloud AI Endpoints operate out of European data centers, offering sub-200ms first-token latency, pay-per-token pricing from €0.04 per million tokens, and support for structured outputs and function calling.
Users can run inference in two modes: direct requests using a provider API key billed by OVHcloud, or routed requests authenticated with a Hugging Face token billed directly through Hugging Face without markup.
Hugging Face client SDKs for Python (huggingface_hub >= 1.1.5) and JavaScript (@huggingface/inference) support specifying provider targets directly in the model identifier.
Source and freshness
- Source
- huggingface.co
- Published
- Added to Yomu
- Last updated
Summaries are generated from the original by a language model. Check the original before relying on it.
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