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Stable Diffusion: Open-source image generation model available on Hugging Face
Hugging Face
The AI community building the future
As of 30 August 2026, Hugging Face is free to use. Open-source AI platform hosting models, datasets, and ML applications. Softwr lists it under Machine Learning. Hugging Face is launched in 2016, available on Web, API.
Overview
What Hugging Face does
Open-source AI platform hosting models, datasets, and ML applications. Hugging Face is the leading hub for sharing and discovering machine learning models with 500,000+ models available.
What people use it for
- ai tools management
- Workflow automation
- Reporting
Related searches
The honest half
Where it falls short
Concrete and checkable, so you can decide whether any of them matter to you. This is the half of a review a vendor will not write about Hugging Face.
- Model discovery across 3 million models lacks robust filtering and sorting by quality metrics
- Community-driven content means variable model quality and documentation
- Private models and datasets require Pro subscription
- Enterprise support and SLAs require custom arrangements
Cross-shopped
What people choose instead of Hugging Face
Each pairing was judged by two reviewers asking whether a buyer would genuinely weigh the two against each other. The ones that failed were deleted rather than published.
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Capabilities
Features
Model hub
Datasets
Spaces
Transformers library
GitHub
Integration with GitHub
Cloud providers
Integration with Cloud providers
MLOps tools
Integration with MLOps tools
Web support
Available on web
Api support
Available on api
Library support
Available on library
Answered, with sources
Questions people ask
Each answer names the page it came from, so you can check it rather than take our word for it.
Is Hugging Face free to use?
Yes. Hugging Face allows users to host and collaborate on unlimited public models, datasets, and applications at no cost. Models can be accessed and used freely from the Hub.
SourceHow many models are available on Hugging Face?
Hugging Face Hub currently hosts nearly 3 million machine learning models across various tasks including text generation, image processing, and video generation.
SourceWhat is the Hugging Face Inference API?
Hugging Face provides access to 45,000+ models from leading AI providers through a single unified API with no service fees, simplifying access to diverse models.
SourceWhat content types does Hugging Face support?
Hugging Face supports text, image, video, audio, and 3D content models, allowing collaboration across multiple modalities and use cases.
SourceWhat is the transformers library?
Transformers is a Hugging Face library built for natural language processing applications, providing pre-built models and utilities for NLP tasks.
SourceBehind it
Who makes Hugging Face
- Company
- Hugging Face
- Based in
- New York, New York
- Founders
- Clément Delangue, Julien Chaumond, Thomas Wolf
Timeline
Hugging Face over time
- Funding2023-08-01$235m
Series D of $235M led by Salesforce Ventures, valuation $4.5B
Source - Funding2019-12-01$15m
Series A of $15M
Source - Funding2018-05-01$4m
Series A of $4M
Source - Funding2017-03-01$1.2m
Series seed of $1.2M from Betaworks, SV Angel, and Kevin Durant
Source - Founded2016-01-01
Hugging Face founded in New York City as AI chatbot company
Source
Keep looking
Where to go from Hugging Face
- Hugging Face alternativesEvery product people weigh against it
- Hugging Face pricingPlans, floors and what the tiers exclude
- Hugging Face badgesWhich rules it meets, and the figure behind each
- All Machine Learning softwareThe full category
- Best Machine Learning softwareThe shortlist, and how it was cut
Best Machine Learning software for
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From $2,394/yr14 researched notesUnified API gateway routing requests across 500+ models from 80+ providers
Free plan11 researched notes
Softwr does not host reviews and shows no star rating for Hugging Face, because a rating we did not collect is not ours to publish. What is here is the pricing and platform detail from the vendor’s own pages, limitations we could state concretely, and alternatives a reviewer confirmed people weigh against it. Tell us if any of it is wrong.
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