Hugging Face is an Infrastructure & APIs company founded in 2016 and based in New York, United States. It has raised $395.2M in total funding, most recently a Series D in 2023 at a $4.5B valuation.
| Date | Stage | Amount | Valuation | Lead investors |
|---|---|---|---|---|
| Aug 22, 2023 | Series D | $235M | $4.5B | Salesforce Ventures |
| May 9, 2022 | Series C | $100M | $2B |
| Lux Capital |
| Mar 11, 2021 | Series B | $40M | — | Addition |
| Dec 17, 2019 | Series A | $15M | — | Lux Capital |
| May 23, 2018 | Seed | $4M | — | A.Capital Ventures |
| Mar 1, 2017 | Seed | $1.2M | — | Betaworks |

ByteDance releases DMAD, a 4-step adversarial distillation method for Minimax-h3 image generation.

A new image model Ming-Image-0.1 appears as a ComfyUI custom node and Hugging Face upload.

Comfy UI adds native system-prompt support for Qwen Image 2.1 text generation, enabling prompt enhancement for both T2I and edit workflows.

HyperFlow, an open-weight video diffusion model, claims improvements in camera control, consistency, and material detail; weights hosted on Hugging Face.

A Reddit user tests a 3-step Taomate turbo LoRA for Minimax's video model, generating 0.7MP clips in ~2 minutes on an RTX 5090.

SMACK! LoRA Beta 2 for MiniMax H3 adds explosive impacts, multi-enemy fights, and blood squibs, hosted on Hugging Face.
A centralized platform and repository where users can discover, share, and collaborate on machine learning models, datasets, and demo applications. The Hub hosts 500,000+ open-source models including Flux, Stable Diffusion, and others across text, vision, audio, and multimodal domains. Users can upload models, datasets, and create interactive applications, enabling the global AI community to build together with version-controlled, Git-based infrastructure.
An open-source Python library providing a unified framework for state-of-the-art pre-trained models across text, vision, audio, and multimodal tasks. It supports multiple frameworks (PyTorch, TensorFlow, JAX) and includes over 630,000 model checkpoints available on the Hub. Developers use the high-level pipeline API for simple inference or access lower-level APIs for fine-tuning and custom training across diverse machine learning tasks.
A serverless inference service providing instant access to thousands of machine learning models for prototyping and production use. Users can run inference on text generation, image generation, embeddings, and other tasks with GPU acceleration, free tier for testing, and paid endpoints for production workloads. The API integrates seamlessly with the Hub ecosystem and supports both pay-as-you-go and dedicated inference endpoints.
A deployment platform for building and hosting interactive machine learning applications with web interfaces. Users can upload demos, notebooks, or custom web apps built with frameworks like Gradio or Streamlit, and Hugging Face manages hosting with GPU acceleration options. The platform hosts over 1 million community-created demos, enabling researchers and developers to showcase models and build collaborative AI applications.