Hugging Face
The registry the open-source AI world runs on
Overview
The default host and registry for open-weight models, datasets, and demo apps — over 2 million models and 500,000 datasets, free to browse and download, with paid seats and hosted inference on top. For ML engineers, researchers, and hobbyists.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 13 Jul 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
- Browse/download 2M+ models
- 100GB private storage
- Small ZeroGPU quota
- 8x ZeroGPU quota
- 1TB storage
- SSH Dev Mode
- SSO
- Audit logs
- Resource groups
- Dedicated CSM
- Custom SLAs
- Annual billing
What you can produce with Hugging Face
- 2M+ open-weight models and 500K+ public datasets
- Serverless Inference API plus dedicated Inference Endpoints
- Spaces for hosting Gradio/Streamlit demo apps
- ZeroGPU shared GPU quota (scales with paid tier)
- AutoTrain low-code fine-tuning
- SSO, audit logs, and resource groups on Team/Enterprise
- Open-source transformers, diffusers, and huggingface_hub libraries
ASEAN Perspective
Hugging Face in Southeast Asia
ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).
The open-source AI world runs on this. If a model is public — Llama, Qwen, Whisper, a fine-tuned diffusion checkpoint — it almost certainly lives on the Hub, and pulling it down is a two-line call in the transformers library. Browsing and downloading stay free with no account, which is why it became default infrastructure rather than just another SaaS. Paid seats ($9 PRO, $20 Team, $50 Enterprise) buy storage, a bigger ZeroGPU quota, SSO, and audit logs. The catch worth knowing: a seat price never covers compute. Every Inference Endpoint or busy Space you spin up bills separately, and that's where surprise costs come from. For researchers and ML engineers it's non-negotiable. For a business standardizing on hosted inference, price the compute first and treat the seat as the smaller line item.
What people say
Reviewers who use the Hub daily tend to treat the free tier as the real product. SaaSLens rated it 4.7/5 in a March 2026 write-up, singling out the PRO plan as "enterprise-grade GPU access for the cost of a couple of coffees per month" — a fair read of the $9 tier's 8x ZeroGPU quota and 1TB of storage.
The most common source of confusion isn't the product, it's the billing model. As one breakdown put it, the plan price "only covers your Hub seat — every model you run adds separate compute charges on top." Teams that assume a subscription includes inference get caught out when Inference Endpoints or heavily-trafficked Spaces show up as separate line items.
Support comes up repeatedly as the soft spot. Several reviewers flag the absence of live chat even on paid plans as dated for a 2026 developer platform, contrasting it with the real-time chat that Vercel and Netlify offer; Hugging Face leans on async email and Slack, which works but adds friction during time-sensitive debugging. There's also a gap in the tier ladder — one user wanted paid expert support below the Enterprise level, noting "we might not be that big to get ourselves the Enterprise account."
On capability, the praise is consistent and unflashy: the sheer breadth of public models and datasets, the tight integration with the transformers, diffusers, and huggingface_hub libraries, and Spaces as a fast way to demo a project without standing up your own infrastructure. AutoTrain and the serverless Inference API get called out as low-friction ways to test models before committing to dedicated hosting.
The recurring verdict across reviews: an outstanding free tier for public work, a PRO plan that's an easy yes at $9, Team worth it once you're past roughly five collaborators who need SSO and audit logs, and Enterprise that competes credibly against standing up equivalent tooling on a cloud provider — provided you've modeled the compute bill separately from the seats.
Summary of public user & expert reviews, compiled by RECATOOLS.
About this listing
This entry was compiled from publicly available data including Hugging Face's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Hugging Face unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
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