Hugging Face
by Hugging Face, Inc.
The AI community building the future.
Hugging Face is the leading open-source platform and community for machine learning, often called 'GitHub for ML.' Its Hub hosts millions of models, datasets and demo apps, and its Enterprise Hub adds security, compliance and managed infrastructure for organizations.
Hugging Face is an American AI company that operates the reference open platform for machine learning, where researchers, companies and developers publish, discover, fine-tune and deploy AI models. At its core is the Hugging Face Hub, a Git-based registry that hosts over 2 million models, more than 500,000 datasets and roughly a million interactive Spaces demos, complemented by widely adopted open-source libraries such as Transformers, Datasets, Diffusers and Tokenizers. Beyond the free community offering, Hugging Face provides commercial products including PRO accounts, Team and Enterprise Hub subscriptions, Inference Endpoints for production model deployment on dedicated GPU and CPU hardware, Inference Providers (an OpenAI-compatible gateway routing to partners like Groq, Together and Fireworks), and AutoTrain for no-code fine-tuning. The Enterprise Hub adds SSO/SAML, audit logs, storage regions, SCIM provisioning, resource groups and dedicated support, and the company partners with vendors such as Dell, AWS, Azure and Nvidia for on-premises and private-cloud deployments. Founded in 2016 by Clément Delangue, Julien Chaumond and Thomas Wolf, Hugging Face has become central infrastructure for the open-weights AI ecosystem, used by more than 50,000 organizations and over 2,000 paying enterprise customers.
At a Glance
- Category
- AI Models & APIs
- Pricing
- Freemium, Subscription, Usage-based
- Target Market
- Data Scientists, ML Engineers, Enterprise Developers, AI Researchers, CTOs, AI/ML Platform Teams
- Founded
- 2016
- Headquarters
- New York City, New York, USA
- Customers
- 50,000+ organizations on the platform; 2,000+ paying enterprise customers (as of June 2025), including Intel, Pfizer, Bloomberg and eBay
Key Features
- ✓Model & Dataset Hub
A Git-based platform hosting over 2 million models and 500,000+ datasets with versioning, model cards and access controls.
- ✓Transformers & open-source libraries
Widely used Python libraries (Transformers, Datasets, Diffusers, Tokenizers) providing state-of-the-art pretrained models for text, vision, audio and multimodal tasks.
- ✓Spaces
Hosted environment for building and sharing interactive ML demo apps, with optional GPU and ZeroGPU compute.
- ✓Inference Endpoints & Providers
Deploy any model to dedicated, autoscaling GPU/CPU infrastructure, or route requests through an OpenAI-compatible gateway to multiple inference providers.
- ✓Enterprise Hub
Adds SSO/SAML, audit logs, storage regions, SCIM provisioning, resource groups and dedicated support for organizations.
- ✓AutoTrain & fine-tuning
No-code and low-code tooling to fine-tune and customize models on private data without managing infrastructure.
Capabilities
Use Cases
- •Open-source model discovery and reuse
Find, download and integrate pretrained open-weight models for NLP, vision, audio and multimodal applications.
- •Production model deployment
Serve fine-tuned models on dedicated, secure and scalable Inference Endpoints without building custom serving infrastructure.
- •Enterprise AI collaboration
Centralize a team's models, datasets and Spaces with governance, access control and compliance via the Enterprise Hub.
Ideal For
Best For
- ✓Discovering, sharing and hosting open-source AI models and datasets
- ✓Fine-tuning and deploying ML models to production infrastructure
- ✓Collaborating on ML projects with enterprise security and governance
Integrations
Deployment
Market & Ratings
50,000+ organizations on the platform; 2,000+ paying enterprise customers (as of June 2025), including Intel, Pfizer, Bloomberg and eBay
Market Analysis
Pros
- ✓Huge, active open-source community and the largest model/dataset hub
- ✓Free tier and open libraries lower the barrier to entry
- ✓Vendor-neutral, model-agnostic ecosystem
- ✓Flexible deployment including on-prem and private cloud via partners
Cons
- ✗Open hub can include unvetted or low-quality community models
- ✗Production GPU inference can become costly at scale
- ✗Enterprise features and support require paid tiers
- ✗Breadth of tooling can be overwhelming for newcomers
Pricing
HF Hub
$0
- ✓Access to models, datasets and Spaces
- ✓Host unlimited public models and datasets
- ✓Community collaboration
- ✓Basic CPU resources
PRO
$9/mo
- ✓10x private storage capacity
- ✓20x included inference credits
- ✓8x ZeroGPU quota with highest queue priority
- ✓Spaces Dev Mode and ZeroGPU hosting
- ✓Dataset Viewer for private datasets
Team
From $20/user/mo
- ✓All PRO features for every member
- ✓SSO and SAML support
- ✓Storage Regions for data location control
- ✓Audit Logs and Resource Groups
- ✓Repository analytics and centralized token control
Enterprise
From $50/user/mo
- ✓All Team features
- ✓Highest storage, bandwidth and API rate limits
- ✓SCIM provisioning
- ✓Managed billing with annual commitments
- ✓Custom contracts, SLAs and dedicated support
The HF Hub is free for public use. Paid tiers are PRO ($9/mo), Team (from $20/user/mo) and Enterprise (from $50/user/mo). Compute is usage-based: Inference Endpoints start around $0.033/hour for CPU and scale up to multi-GPU instances (e.g., NVIDIA A100/H100/H200), and storage is priced per TB. Volume discounts apply at higher storage tiers; custom pricing is available above 500TB.
Sources
This page was written from 8 sources, 5 on domains other than huggingface.co.
- 1.huggingface.co — huggingface.covendor
- 2.huggingface.co — pricingvendor
- 3.en.wikipedia.org — Hugging Face
- 4.research.contrary.com — hugging face
- 5.grokipedia.com — Hugging Face
- 6.metacto.com — what is hugging face a guide to the ai community and its too
- 7.huggingface.co — indexvendor
- 8.cbinsights.com — alternatives competitors
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