惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

云风的 BLOG
云风的 BLOG
The GitHub Blog
The GitHub Blog
A
About on SuperTechFans
P
Proofpoint News Feed
G
Google Developers Blog
Stack Overflow Blog
Stack Overflow Blog
IT之家
IT之家
Microsoft Security Blog
Microsoft Security Blog
F
Fortinet All Blogs
人人都是产品经理
人人都是产品经理
博客园 - 叶小钗
C
Check Point Blog
Microsoft Azure Blog
Microsoft Azure Blog
aimingoo的专栏
aimingoo的专栏
月光博客
月光博客
美团技术团队
D
Docker
博客园 - Franky
Y
Y Combinator Blog
大猫的无限游戏
大猫的无限游戏
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
博客园 - 【当耐特】
罗磊的独立博客
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报

Hugging Face - Blog

Waypoint-1.5: Higher-Fidelity Interactive Worlds for Everyday GPUs ALTK‑Evolve: On‑the‑Job Learning for AI Agents Safetensors is Joining the PyTorch Foundation Holo3: Breaking the Computer Use Frontier Any Custom Frontend with Gradio's Backend A New Framework for Evaluating Voice Agents (EVA) Bringing Robotics AI to Embedded Platforms: Dataset Recording, VLA Fine‑Tuning, and On‑Device Optimizations One-Shot Any Web App with Gradio's gr.HTML CUGA on Hugging Face: Democratizing Configurable AI Agents New in llama.cpp: Model Management Building Deep Research: How we Achieved State of the Art OVHcloud on Hugging Face Inference Providers 🔥 20x Faster TRL Fine-tuning with RapidFire AI Building for an Open Future - our new partnership with Google Cloud Aligning to What? Rethinking Agent Generalization in MiniMax M2 Building a Healthcare Robot from Simulation to Deployment with NVIDIA Isaac Sentence Transformers is joining Hugging Face! Unlock the power of images with AI Sheets Supercharge your OCR Pipelines with Open Models Google Cloud C4 Brings a 70% TCO improvement on GPT OSS with Intel and Hugging Face Get your VLM running in 3 simple steps on Intel CPUs Nemotron-Personas-India: Synthesized Data for Sovereign AI Introducing RTEB: A New Standard for Retrieval Evaluation Accelerating Qwen3-8B Agent on Intel® Core™ Ultra with Depth-Pruned Draft Models VibeGame: Exploring Vibe Coding Games Nemotron-Personas-Japan: ソブリン AI のための合成データセット Swift Transformers Reaches 1.0 – and Looks to the Future Smol2Operator: Post-Training GUI Agents for Computer Use SyGra: The One-Stop Framework for Building Data for LLMs and SLMs Gaia2 and ARE: Empowering the community to study agents
Scaleway on Hugging Face Inference Providers 🔥
Guillaume Noale, Franck Pagny, Fred Bardolle, Guillaume Calmette · 2025-09-19 · via Hugging Face - Blog

Back to Articles

banner image

We're thrilled to share that Scaleway is now a supported Inference Provider on the Hugging Face Hub! Scaleway 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 Gemma 3 — right from Hugging Face. You can browse Scaleway's org on the Hub at https://huggingface.co/scaleway and try trending supported models at https://huggingface.co/models?inference_provider=scaleway&sort=trending.

Scaleway Generative APIs is 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 €0.20 per million tokens.

The service runs on secure infrastructure located in European data centers (Paris, France), 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, Scaleway'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 Scaleway's platform and infrastructure at https://www.scaleway.com/en/generative-apis/.

Read more about how to use Scaleway as an Inference Provider in its dedicated documentation page.

See the list of supported models here.

How it works

In the website UI

  1. 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.

Inference Providers

  1. As mentioned, there are two modes when calling Inference Providers:
  • Custom key (calls go directly to the inference provider, using your own API key of the corresponding inference provider)
  • Routed by HF (in that case, you don't need a token from the provider, and the charges are applied directly to your HF account rather than the provider's account)

Inference Providers

  1. Model pages showcase third-party inference providers (the ones that are compatible with the current model, sorted by user preference)

Inference Providers

From the client SDKs

from Python, using huggingface_hub

The following example shows how to use OpenAI's gpt-oss-120b using Scaleway as the inference provider. You can use a Hugging Face token for automatic routing through Hugging Face, or your own Scaleway API key if you have one.

Note: this requires using a recent version of huggingface_hub (>= 0.34.6).

import os
from huggingface_hub import InferenceClient

client = InferenceClient(
    provider="scaleway",
    api_key=os.environ["HF_TOKEN"],
)

messages = [
    {
        "role": "user",
        "content": "Write a poem in the style of Shakespeare"
    }
]

completion = client.chat.completions.create(
    model="openai/gpt-oss-120b",
    messages=messages,
)

print(completion.choices[0].message)

from JS using @huggingface/inference

import { InferenceClient } from "@huggingface/inference";

const client = new InferenceClient(process.env.HF_TOKEN);

const chatCompletion = await client.chatCompletion({
  model: "openai/gpt-oss-120b",
  messages: [
    {
      role: "user",
      content: "Write a poem in the style of Shakespeare",
    },
  ],
  provider: "scaleway",
});

console.log(chatCompletion.choices[0].message);

Billing

Here is how billing works:

For direct requests, i.e. when you use the key from an inference provider, you are billed by the corresponding provider. For instance, if you use a Scaleway API key you're billed on your Scaleway account.

For routed requests, i.e. when you authenticate via the Hugging Face Hub, you'll only pay the standard provider API rates. There's no additional markup from us; we just pass through the provider costs directly. (In the future, we may establish revenue-sharing agreements with our provider partners.)

Important Note ‼️ PRO users get $2 worth of Inference credits every month. You can use them across providers. 🔥

Subscribe to the Hugging Face PRO plan to get access to Inference credits, ZeroGPU, Spaces Dev Mode, 20x higher limits, and more.

We also provide free inference with a small quota for our signed-in free users, but please upgrade to PRO if you can!

Feedback and next steps

We would love to get your feedback! Share your thoughts and/or comments here: https://huggingface.co/spaces/huggingface/HuggingDiscussions/discussions/49