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Hugging Face
AI / Machine Learning

Hugging Face Company Overview

Hugging Face logo

Hugging Face

● Active
AI / Machine Learning · New York, New York · Est. 2016
AIOpen SourceMachine LearningDeveloper ToolsEnterprise↗ Website
$4.5B
Valuation
$70M
Revenue
500
Employees
2016
Founded

Hugging Face is an AI platform company that operates the world's largest open-source model and dataset hub, providing developers and enterprises with tools to build, train, fine-tune, and deploy machine learning models. Its platform hosts over 900,000 models and 200,000 datasets, serving millions of developers globally alongside enterprise customers including Google, Amazon, Microsoft, and the U.S. government.

Recent Press
5 items
Acquisition·2026-01-14
Hugging Face Acquires Argilla to Expand Data Annotation and RLHF Tooling
Hugging Face acquired Argilla, an open-source data labeling and annotation platform for NLP and LLM datasets, integrating Argilla's tools into the Hub to provide end-to-end dataset creation, annotation, and model training workflows for the open-source AI community.
Press Release·2025-10-28
Hugging Face Surpasses 1 Million Public Models on the Hub
Hugging Face announced that the Hub crossed one million public model repositories, driven by rapid growth in fine-tuned LLMs, LoRA adapters, and multimodal models uploaded by the global open-source AI research community.
Product Launch·2025-08-20
Hugging Face Open LLM Leaderboard v2 Launches with Harder Benchmarks
Hugging Face released the second version of its Open LLM Leaderboard with significantly harder evaluation benchmarks including GPQA, MATH, and IFEval to replace benchmarks that frontier models had saturated, restoring the leaderboard's ability to differentiate capability levels among leading open models.
Partnership·2025-06-03
Hugging Face Partners with AWS to Bring Open Models to Amazon SageMaker and Bedrock
Hugging Face deepened its partnership with Amazon Web Services to make Hub models directly deployable on Amazon SageMaker and available through Amazon Bedrock, enabling enterprise AWS customers to access open-source models with the governance and infrastructure they already operate.
Product Launch·2025-04-15
Hugging Face Launches Enterprise Hub Tier for Private Model Governance and SSO
Hugging Face released an Enterprise Hub tier providing organizations with private model repositories, SSO integration, advanced audit logging, and dedicated support, targeting regulated industries and large enterprises requiring controlled AI model governance.
Company History
9 milestones
Clément Delangue, Julien Chaumond, and Thomas Wolf founded Hugging Face in New York City as a conversational AI chatbot app for teenagers, before pivoting to become an open-source NLP platform after releasing the Transformers library.

Hugging Face Organization Structure & Team

Org Chart
500 employees · Click a leader to explore their team
480 across 12 departments
Chief Executive Officer
Clément Delangue
Julien Chaumond — Departments
· 480 people across 12 depts

Hugging Face Financials, Revenue & Market Share

Annual Revenue
$70M
+75% vs prior year
YoY Growth
+75%
From $8M to $70M
Revenue / Employee
$140K
Annual revenue per full-time employee
Revenue Growth
2021
2022
2023
2024
2025
$8M
$20M
$35M
$40M
$70M
Market Share
Open-Source ML Platform & Model Hub
62%
share
Hugging Face
62%
GitHub (Models)
12%
Replicate
10%
Weights & Biases
8%
Others
8%
$280B
TAM
$35B
SAM
$70M
SOM
Revenue Streams
Enterprise Hub & API55%
Inference Endpoints30%
Expert Acceleration Program15%
Business Units
Open Source Platform60%
Hugging Face Hub, Transformers library, Datasets, and Evaluate — the open-source ecosystem that drives community adoption, developer mindshare, and downstream enterprise conversion to paid Hub and infrastructure products.
Enterprise Infrastructure40%
Enterprise Hub subscriptions, Inference Endpoints, and Expert Acceleration Program services that monetize the open-source platform by providing governance, deployment infrastructure, and expert support to paying enterprise and government customers.

Hugging Face Internal Tools & Processes

Internal Tools
12 departments
Engineering140 people · 3 roles
Standards & Certifications
10 standards
Compliance frameworks, security audits, and quality certifications this company maintains.
Security
SOC 2 Type II
Certified
Hugging Face maintains SOC 2 Type II certification covering its Hub infrastructure and Inference Endpoints services, providing enterprise customers assurance over the security, availability, and confidentiality controls protecting their private model repositories and API traffic.
Security
ISO 27001
In Progress
Hugging Face is pursuing ISO 27001 certification for its Enterprise Hub and Inference Endpoints infrastructure to meet the information security management requirements of regulated enterprise customers in financial services, healthcare, and government sectors.
Privacy
GDPR
Compliant
Hugging Face complies with GDPR for its European user base and enterprise customers, implementing data processing agreements, data residency controls, and model card transparency requirements for models hosted on the Hub that process personal data.
Privacy
CCPA
Compliant
Hugging Face adheres to CCPA requirements for California residents using the Hub platform, providing data access and deletion rights and ensuring that model training data uploaded by California-based users is handled in compliance with California privacy law.
Regulatory
EU AI Act
In Progress
Hugging Face is adapting its Hub platform and model card standards to align with EU AI Act transparency and documentation requirements, particularly for high-risk AI models hosted on the platform, ensuring model providers can generate conformity assessment documentation.
Regulatory
NIST AI RMF
Compliant
Hugging Face aligns its model card standard and Hub governance features to the NIST AI Risk Management Framework, providing structured documentation fields for model intended use, limitations, bias evaluations, and safety considerations required by federal AI policy.
Privacy
HIPAA
Compliant
Hugging Face supports HIPAA-compliant deployments through private Inference Endpoints with VPC isolation and BAA agreements for healthcare enterprise customers who deploy medical NLP and clinical AI models using Hugging Face infrastructure.
Regulatory
FedRAMP Moderate
In Progress
Hugging Face is pursuing FedRAMP Moderate authorization for its Enterprise Hub and Inference Endpoints to serve U.S. federal government customers who require FedRAMP-authorized cloud services for hosting and deploying AI models in government environments.
Accessibility
WCAG 2.1 AA
Compliant
Hugging Face maintains WCAG 2.1 AA accessibility compliance across its Hub web platform, ensuring that the model discovery interface, dataset viewer, Spaces, and documentation are accessible to users with disabilities in the global developer community.
Regulatory
Open Rail License
Compliant
Hugging Face developed and enforces the OpenRAIL (Open Responsible AI License) framework for models hosted on the Hub, providing a responsible use license that allows open sharing and modification of AI models while restricting harmful applications defined in acceptable use policies.

Hugging Face Interview Preparation

Interview Prep
Role-specific interview questions and keywords. Select a department, then click any role to prepare.
Engineering· 3 roles

Hugging Face Products & Competitors

Product Suite
4 products · select one to explore
AI / Machine Learning
Developer Tools
Hugging Face Hub
The AI community building the future

Hugging Face Hub is the world's largest open-source repository for machine learning models, datasets, and demo applications, hosting over 900,000 models across NLP, computer vision, audio, and multimodal domains. Researchers, developers, and enterprises use it to discover, share, version, and deploy pre-trained models and datasets through a Git-based collaboration platform with integrated model cards and evaluation leaderboards.

Use Cases
Discovering and downloading pre-trained transformer models for fine-tuning on domain-specific NLP classification tasksHosting and versioning organization-private model repositories with access-controlled sharing across research and engineering teamsPublishing model cards with evaluation benchmarks and bias disclosures to meet responsible AI documentation requirements
No image
Key Customers
GOOG
Google
MSFT
Microsoft
META
Meta
Competitive Intelligence
VSGitHub
THEM

GitHub is a code hosting and version control platform that supports machine learning projects through Git repository management, Actions CI/CD, and Codespaces, and has begun adding AI-specific features like GitHub Models for model discovery.

EDGE

Hugging Face Hub is purpose-built for ML artifacts including model cards, dataset viewers, and inference widgets — features GitHub's general-purpose repository model does not natively support

VSWeights & Biases
THEM

Weights & Biases is an MLOps platform for experiment tracking, model versioning, and performance visualization that helps ML teams log, compare, and share model training runs and artifacts.

EDGE

Hugging Face Hub provides a public-facing model sharing and discovery layer that complements training tracking tools, with built-in community engagement and open-source model discoverability at a scale W&B does not offer

VSReplicate
THEM

Replicate is a cloud platform for running and deploying open-source machine learning models via API, offering a model library and serverless inference for developers who want to use models without managing infrastructure.

EDGE

Hugging Face Hub offers deeper model ecosystem integration including Spaces demos, dataset hosting, and community fine-tuning workflows that go beyond Replicate's API-first deployment focus

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