Hugging Face
The world's leading open-source AI community, hosting over 2 million models, datasets and Spaces applications, providing inference services, cloud computing power and team enterprise editions, supporting the entire process of model selection, trial, fine-tuning and deployment.
Updated: 2026-10-26
What is Hugging Face?
Hugging Face calls itself "the AI community building the future". Its official positioning is a platform for the machine learning community to collaborate on models, datasets and applications, with a mission to advance the democratization of AI through open source and open science. The site currently hosts over 2 million models and runs a large number of Spaces applications and public datasets. According to the official, more than 50,000 organizations are already using it. For developers, whether it is model selection, dataset search or team collaboration, this is an indispensable first stop in the current open source AI ecosystem. The community-driven feature also makes the launch speed of new models and new libraries significantly faster than traditional channels.
Who is it for?
- Developers and researchers who are looking for open-source models and datasets for model selection and experimentation, as well as teams that need to quickly build demos, compare model performance, and host their own models; engineers who want to showcase their works in the community and build personal technical influence, and students who want to keep up with the cutting edge of research are also suitable for frequent visits.
Key features
7Model Hub
Over 2 million models cover various modalities and tasks such as text, images, speech, and video, supporting online trial, inference, and download. You can directly compare multiple candidates when selecting models, and hot lists and trends can also help judge community focus.
Datasets
Retrieval, loading and collaboration of public datasets facilitate training and evaluation, and supporting tools make data preparation more convenient.
Spaces
Run and share machine learning Demo applications directly in the browser, the lightest way to showcase and experience models, with just a few lines of configuration you can turn a model into an interactive page.
Inference Providers
Unify calls to multiple inference service providers, making it easier to integrate models into applications and eliminating the operational burden of building and maintaining in-house services.
Compute
Provides hosted training and inference resources to speed up development and deployment, suitable for teams requiring elastic computing power.
Team & Enterprise
Provides permission management, compliance support and collaboration capabilities for organizations. The official states that more than 50,000 organizations are using the platform.
Open-source toolchains
Libraries such as Transformers and Diffusers are deeply integrated with the platform, boasting abundant community resources and comprehensive tutorials and examples.
How to use Hugging Face
- Pay attention to distinguishing between model weights and licenses โ different versions of the same model may have very different licensing terms, so be sure to verify each item one by one before commercial use.
- The discussion sections on popular model pages often contain practical tips to avoid pitfalls, which are often more useful than README files.
- you can run the Demos in Spaces first to decide whether to integrate them.
- Before hosting your own model, it is recommended to first check the platform's storage and bandwidth rules clearly.
Things to know
Traffic & popularity
Data month Sep 2026
Hugging Face receives about 26.2M visits per month and ranks #1,474 worldwide.
Monthly visits
12 monthsTraffic sources
- Direct42.9%
- Search32.6%
- Social10.7%
- Referrals9.4%
- AI assistants3.4%
- Other1.0%
Top countries
- United States19.1%
- China10.8%
- India9.0%
- Germany4.9%
- Russia4.7%
Estimated from third-party traffic data.
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