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Hugging Face

AI InfrastructureVerified100% conf

AI platform providing machine learning models, datasets, and development tools

huggingface.co ↗

📍 Brooklyn, New York

Verified Data

💰

Revenue$130.1M ARR

🔗getlatka.com↗

🚀

Funding$395.2M total funding, Series D

🔗techcrunch.com↗

📊

Monthly Traffic19M-110M visits/month

🔗similarweb.com↗

👥

Users13 million users

🔗huggingface.co↗

🧑‍💻

Team Size730 employees

“team_size: Approximately 730 employees”

📈

Growth85% YoY revenue growth

🔗getlatka.com↗

🏷️

StageSeries D (August 2023)

📅

Founded2016

Company Profile

ModelOpen-source Freemium platform

VerticalMachine learning, AI research, Enterprise AI

ClientsIntel, Qualcomm, Pfizer, Grammarly, eBay

BuyersMachine learning practitioners, researchers, and enterprise AI teams. Primarily developers and technical researchers, aged 18-34, with global distribution.

PricingFree Community tier, Pro $9/month, Enterprise Hub $20/user/month, Usage-based Inference Endpoints

Contact

✉️ [email protected] LinkedIn

@huggingface

Strategic Analysis

Strategy

Open-source freemium model positioning as the GitHub for AI/ML. Building the central platform for AI collaboration with 2M+ models and 500K+ datasets. Monetizing through Pro subscriptions, Enterprise Hub, and managed inference services while maintaining strong open-source community.

Tactics

Community-driven growth through free hosting of models and datasets. Enterprise sales targeting Fortune 500 companies with private collaboration features and SSO. Usage-based pricing for inference endpoints to capture production workloads. Heavy investment in developer experience and platform reliability.

Competitive Positioning

Positioned as the de facto standard for AI model sharing and collaboration, competing with GitHub (for code) and cloud providers' AI platforms. Differentiates through open-source community, ease of use, and comprehensive model library versus proprietary alternatives from Google, AWS, and Microsoft.

Marketing Approach

Developer-first community building through open-source contributions and free tier. Technical content marketing via blog posts and research publications. Conference presence at AI/ML events. Word-of-mouth growth through researcher and practitioner networks.

Notable

Valued at $4.5 billion, backed by major tech companies including Salesforce, Nvidia, Google, Amazon, IBM. Hosts 2M+ public models and 500K+ datasets.

🔗 Source ↗

Tech Stack

JavaScript

HTML5

CSS3

Svelte

React

Tailwind CSS

Python

Rust

PyTorch

TensorFlowSentenceTransformers

AWS

CloudFlare

MongoDB

Ruby on Rails

Recent News

State of Open Source on Hugging Face: Spring 2026May 1, 2026Hugging Face reached a milestone of 13 million users and 2 million models, highlighting the platform's role as the central hub for the AI ecosystem.Hugging Face CEO Predicts 2026 Burst While AI Innovation SoarsFeb 1, 2026Clem Delangue discussed the potential for a bubble burst in the LLM sector while forecasting continued long-term AI growth.Top Tech News Today, May 11, 2026May 11, 2026An analysis of the current AI landscape and the challenges of energy consumption and regulation, featuring Hugging Face as a key player.

Related AI Infrastructure Companies

Discovery Sources

huggingface/tokenizers

May 13, 2026

huggingface/transformers

May 13, 2026

Signals

web traffic19M-110M visits/month🔗 source ↗

growth rate85% YoY revenue growth🔗 source ↗

team size730 employees

“team_size: Approximately 730 employees”

user count13 million users🔗 source ↗

funding raised$395.2M total funding, Series D🔗 source ↗

revenue claim$130.1M ARR🔗 source ↗

trend indicatornatural-language-understanding🔗 source ↗

trend indicatorbert🔗 source ↗

trend indicatorlanguage-model🔗 source ↗

trend indicatorgpt🔗 source ↗

trend indicatortransformers🔗 source ↗

trend indicatornatural-language-processing🔗 source ↗

trend indicatornlp🔗 source ↗

trend indicatorComputer Vision🔗 source ↗

trend indicatorAudio🔗 source ↗

trend indicatorDeep Learning🔗 source ↗

trend indicatorTransformers🔗 source ↗

trend indicatorNLP🔗 source ↗

trend indicatorMachine Learning🔗 source ↗

Evidence

github.com

Transformers works with Python 3.10+, and PyTorch 2.4+.

github.com

Extremely fast (both training and tokenization), thanks to the Rust implementation. Takes less than 20 seconds to tokenize a GB of text on a server's CPU.

getlatka.com

$130.1M ARR

techcrunch.com

$395.2M total funding, Series D

huggingface.co

13 million users

getlatka.com

85% YoY revenue growth

similarweb.com

19M-110M visits/month