H

Hugging Face

by Hugging Face, Inc.

AI Models & APIsDeveloper ToolsInfrastructure & CloudEnterprise Platform

The AI community building the future.

Freemium · Subscription · Usage-based·Added Jun 21, 2026·Updated Jun 21, 2026
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THE DAILY BRIEF
Hugging Face

by Hugging Face, Inc.

AI Models & APIsDeveloper ToolsInfrastructure & CloudEnterprise Platform

The AI community building the future.

Freemium · Subscription · Usage-based

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.

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
  • Transformers & open-source libraries
  • Spaces
  • Inference Endpoints & Providers
  • Enterprise Hub
  • AutoTrain & fine-tuning

Capabilities

text generation
image generation
video generation
code generation
workflow automation
api access
audio generation
fine tuning
agent orchestration

Use Cases

  • Open-source model discovery and reuse
  • Production model deployment
  • Enterprise AI collaboration

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

Market Analysis

Open-source standardCommunity-drivenModel-agnostic ecosystemGitHub for machine learning

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.

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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

text generation
image generation
video generation
code generation
workflow automation
api access
audio generation
fine tuning
agent orchestration

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

SDK Available
SDK:PythonJavaScriptRust

Deployment

On-Premise

Market & Ratings

Estimated Customers

50,000+ organizations on the platform; 2,000+ paying enterprise customers (as of June 2025), including Intel, Pfizer, Bloomberg and eBay

Market Analysis

Open-source standardCommunity-drivenModel-agnostic ecosystemGitHub for machine learning

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. 1.huggingface.cohuggingface.covendor
  2. 2.huggingface.copricingvendor
  3. 3.en.wikipedia.orgHugging Face
  4. 4.research.contrary.comhugging face
  5. 5.grokipedia.comHugging Face
  6. 6.metacto.comwhat is hugging face a guide to the ai community and its too
  7. 7.huggingface.coindexvendor
  8. 8.cbinsights.comalternatives competitors
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