Hugging Face

What Hugging Face does

Hugging Face, founded in 2016 and headquartered in Brooklyn, NY, operates the leading open-source collaboration platform for machine learning. The company hosts over 2 million public models, 500,000+ datasets, and 1 million+ applications (Spaces) on its Hub, serving a community of approximately 16 million developers and over 50,000 organizations. Originally founded as a chatbot app, the company pivoted to become a central repository and deployment platform for AI models, functioning similarly to how GitHub serves software development. More than 30% of Fortune 500 companies are reported customers, including Meta (2.35K models hosted), Google (1.13K), Microsoft (522), Amazon, Intel, Grammarly, and Writer.

The platform is built on a comprehensive open-source stack including the Transformers library (161,925+ models), Diffusers, Safetensors, TRL (Transformer Reinforcement Learning), PEFT (parameter-efficient fine-tuning), smolagents, Datasets, and Tokenizers. Core products include the Hugging Face Hub for model sharing and discovery, Inference Endpoints for managed model deployment with support for vLLM, SGLang, llama.cpp, TGI, and TEI inference engines, and Hugging Face Enterprise for organizational deployments. Recent additions include Hugging Face Buckets (private storage replacing AWS S3 for some customers), LeRobot for open-source robotics, Reachy Mini desktop robot hardware acquired through the Pollen Robotics acquisition, and ML Intern for autonomous ML research agents.

Revenue is generated through a hybrid model combining freemium public hosting with three primary monetization streams: enterprise subscriptions (Team and Enterprise tiers starting at $20/user/month with SSO, audit logs, and dedicated support), usage-based compute (Inference Endpoints starting at $0.60/hour for GPU instances), and paid inference through a network of inference providers offering access to 45,000+ models via a unified API. Distribution combines self-serve developer adoption with strategic enterprise partnerships, including OEM integrations with Qualcomm, Dell, and Intel. Reported revenue reached approximately $130 million in 2024, reflecting 367% year-over-year growth. The company has raised approximately $395 million in total funding from investors including Sequoia Capital, Coatue, Salesforce Ventures, and major technology strategics, and is reported to be preparing for an IPO.

Name

Hugging Face

Legal name

Hugging Face, Inc.

Website

https://huggingface.co

Company type

Private

Founded year

2016

Operating status

Operating

Headcount range

101–250 employees

Short description

Hugging Face operates the leading open-source platform for machine learning, hosting over 2 million models, 500K+ datasets, and serving 16 million developers and 50,000+ organizations globally. The company provides model hub services, enterprise AI infrastructure, and inference deployment through subscriptions and usage-based compute.

Ownership category

akta.pro rank

Headquarters

HQ city

Brooklyn

HQ country

United States

HQ region

North America

Offices2 records

Markets served

GTM type

B2B

Offering type

Software

Cost components

Technology or R&D, Personnel, Infrastructure, Operations, Marketing or Sales

Revenue model

1. Enterprise Subscriptions: Team and Enterprise tier subscriptions providing security, access controls, dedicated support, SSO, audit logs, and resource groups. Starting at $20/user/month for Team tier.
2. Compute Services (Inference Endpoints & Spaces): Pay-as-you-go and subscription-based GPU compute for model deployment. Starting at $0.60/hour for GPU instances on Inference Endpoints. Enables deployment of 45,000+ models from providers.
3. Model Hosting (Public): Free hosting of public models, datasets, and Spaces. Creates the open ecosystem that drives adoption and enterprise conversion.
4. Enterprise Support: Dedicated support packages for enterprise customers with priority response times and custom SLAs.
5. Paid Inference and Fine-tuning: Revenue generated from model inference and fine-tuning services, particularly for enterprise customers requiring managed services beyond self-serve options.

Pricing tiers

Go-to-market motion3 records

Distribution channels7 records

Marketing channels9 records

Core offering

Hugging Face operates a collaboration platform for the machine learning community, hosting over 2 million public models, 500,000+ datasets, and 1 million+ applications (Spaces). The company provides open-source libraries (Transformers, Diffusers, TRL, PEFT, smolagents, Safetensors) for model development and training, plus paid compute and enterprise services including Inference Endpoints for managed model deployment and Hugging Face Enterprise for organizational security, SSO, audit logs, and dedicated support.

Product overview

Hugging Face operates a platform-plus-modules architecture centered on the Hub, which hosts over 2 million models, 500k+ datasets, and 1M+ Spaces applications. The ecosystem includes core libraries (Transformers, Diffusers, Safetensors, TRL, smolagents, PEFT, Datasets, Tokenizers) for model development and training, Inference Endpoints for production deployment, and consumer products (HuggingChat). Enterprise offerings include Buckets storage, Enterprise subscriptions, and PRO tiers. Recent additions include LeRobot for robotics, Reachy Mini robot hardware, and ML Intern agent. The platform supports text, image, audio, video, code, and multimodal AI with extensive inference engine integrations (vLLM, SGLang, llama.cpp, TGI, TEI).

Differentiator

Problem solved

Functional benefit

Brands

• HuggingChat: Chat application powered by open source AI models
• Inference Endpoints
• LeRobot

Products and services

• Hugging Face Hub The central collaboration platform hosting over 2 million public models, 500k+ datasets, and 1M+ Spaces applications, enabling the ML community to share, version, and collaborate on AI artifacts.
• Inference Endpoints Fully managed platform for deploying AI models to production with autoscaling, built-in observability, and support for vLLM, SGLang, llama.cpp, TGI, and TEI inference engines. Starting at $0.60/hour for GPU instances.
• Hugging Face Enterprise Enterprise-grade platform offering security, access controls, dedicated support, SSO, audit logs, regions, and resource groups for organizational AI deployment. Starting at $20/user/month for Team tier.
• Hugging Face PRO Professional subscription tier providing advanced features and capabilities for individual developers on the Hugging Face platform.
• HuggingChat Open-source AI chat application powered by models on the Hub with Omni router for automatic best model selection.
• Hugging Face Buckets (Storage Buckets) Enterprise storage and distribution platform for AI models, datasets, and agent traces with multi-million dollar commercial partnerships replacing AWS S3 for organizations.
• Transformers State-of-the-art machine learning library for PyTorch providing 161,925+ pre-trained models for NLP, vision, audio, and multimodal tasks.
• Diffusers State-of-the-art diffusion models library for PyTorch enabling image, audio, and molecular structure generation.
• Safetensors Secure tensor serialization format preventing arbitrary code execution risks during neural network weight distribution; now a PyTorch Foundation project.
• TRL (Transformer Reinforcement Learning) Training library for transformers with reinforcement learning; v1.0 unifies SFT, DPO, GRPO, KTO, ORPO alignment algorithms with a unified CLI.
• smolagents

Quantifiable outcome

• 367% revenue growth to $130M in 2024
• +3 more outcomes

Named customers15 records

Segments5 records

Ideal customer profiles4 records

Technology focussed Yes

API detail

Has API

Yes

API docs

API detail

Core technology

AI maturity

App detail

Integration16 records

AI capability16 records

Feature9 records

Partnerships

Four partnerships are on record, tiered major, flagship and minor.

• QualcommmajorStrategic or Co-development Partner · 24 June 2026Expanded strategic collaboration to advance open, developer-driven AI from edge devices to cloud. Three pillars: integrating Qualcomm Dragonfly data center solutions with Hugging Face AI storage, enabling deployment across Qualcomm devices and data centers, and developing distributed agentic AI orchestration. Targets 16 million Hugging Face developers.
• Arcee AIflagshipStrategic or Co-development Partner · 9 June 2026Multi-million dollar commercial partnership making Hugging Face the exclusive storage and distribution platform for Arcee's models, datasets, and agent traces. Arcee becomes first major American AI lab to replace AWS S3 with Hugging Face Private Storage (Buckets). Establishes Arcee as flagship organization on Hub.
• Hugging FaceminorGTM or Marketing Partner · 20 May 2026Hugging Face provided strategic backing to NanoCo through CEO investment, positioning as an ecosystem enabler for secure AI agents.
• Dell TechnologiesmajorStrategic or Co-development Partner · 18 May 2026Dell AI Factory ecosystem partnership to help enterprises scale AI deployments beyond experimental stages. Hugging Face integrated into Dell's AI infrastructure solutions alongside Google, OpenAI, Palantir, and ServiceNow. Over 5,000 customers already deploying on Dell AI Factory.

Scale indicators12 records

Recent moves6 records

Expansion highlights8 records

Emerging players

• LangChain: Open-source framework for building LLM applications and agents, with significant overlap in the developer ecosystem around model orchestration, RAG, and agentic workflows. Competes with smolagents for developer mindshare in AI application development.
• Modal: Serverless compute platform for running AI/ML workloads in the cloud, offering GPU-backed inference and batch jobs. Emerging direct competitor in the developer-focused managed inference space alongside Replicate and Together AI.

Direct peers

• Replicate: Cloud platform for running open-source ML models via API, offering pay-per-second inference pricing. Directly competes with Hugging Face Inference Endpoints and Inference Providers for serving open-source models to developers and AI-first startups.
• Together AI: Cloud platform for open-source AI model training, fine-tuning, and inference. Competitor in managed inference and fine-tuning services, raised $235M in August 2023 with Salesforce Ventures lead (per the funding data), directly overlapping with Hugging Face's enterprise compute offering.
• Weights & Biases: ML experiment tracking, model management, and MLOps platform with strong developer community. Directly competes with Hugging Face in model versioning, experiment tracking, and team collaboration for ML workflows, though with less of a public model hub focus.
• Anyscale: Commercial platform built around Ray for distributed AI/ML compute, offering managed services for training and serving models. Competes with Hugging Face in enterprise inference and distributed training infrastructure.

Broad incumbents

• GitHub: Microsoft-owned code collaboration platform serving as the closest analog to Hugging Face's role as the central repository for ML artifacts. GitHub's developer network effects and repository hosting model directly inspired Hugging Face's Hub strategy, and both compete for the same developer mindshare as default collaboration infrastructure.
• Google Cloud (Vertex AI): Google's enterprise AI platform offering model training, deployment, and foundation model access. Major broad incumbent competing for enterprise AI workloads; Google is simultaneously a Hugging Face customer (1,130 models hosted) and integration partner for Gemini.
• AWS (SageMaker / Bedrock): Amazon's cloud AI/ML services include SageMaker for model training/deployment and Bedrock for foundation model access. Broad incumbent that competes on the same enterprise compute workloads Hugging Face targets, while also being a key infrastructure provider for Inference Endpoints.
• Microsoft Azure (Azure ML / AI Foundry): Microsoft's enterprise AI platform offering model training, deployment, and Azure OpenAI services. Major broad incumbent that competes with Hugging Face Enterprise while being both a customer (522 models) and infrastructure provider.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat7 records

Key risks5 records

Key highlights7 records

Customer concentration

• Xx.com/huggingface
• GitHubgithub.com/huggingface
• LinkedInlinkedin.com/company/home
• Facebookfacebook.com/huggingface

Revenue estimate

Valuation estimate

Number of profiles

Profiles14 records

Subsidiaries1 record

Funding overview

Funding rounds8 records

Investors24 records

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A5 records

Investments1 record

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Hugging Face