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Hugging Face

Hub of open models, datasets and free inference

Easy start 2/3Mostly free to start

The main repository for open machine-learning models. You can download weights to run locally, or use hosted inference and Spaces demos, many of which are free to try.

Free tier

Free tierYes
Credit cardNot required
Free allowanceFree tier for public models and Spaces
WatermarkNone
Sign-inRequired
Commercial useAllowed
Checked2026-09-27

Checked by hand against the vendor's own pricing and sign-up pages.

Something out of date? Report an error.

Pricing

Modelfreemium
Starts atUSD 9 / mo
Auto-renewsYes
VendorHugging Face

What it is

Hugging Face is the main repository for open machine-learning models. It hosts weights, datasets and runnable demos, and provides hosted inference for teams that do not want to run the models themselves.

Key features

  • Model hub

    Thousands of models with model cards describing licence, size and intended use.

  • Spaces

    Runnable demos hosted by the community, useful for testing before you commit.

  • Hosted inference

    Call models over an API instead of running them yourself.

Who it suits

  • Finding a model

    Comparing open alternatives to a closed API you are paying for.

  • Prototyping

    Testing a model in a Space before building anything.

  • Licence checking

    Confirming whether a model can be used commercially.

Categories

FAQ

Can I use Hugging Face models commercially?

Most models are, but each model carries its own licence. Always check the model card before commercial use.

Do I need a credit card to start?

No, free accounts can download public models and use the free inference tier.

Alternatives compared

Same job, different terms. Unverified rows stay marked — we do not fill them in.

ToolFree tierCardWatermarkFrom
Hugging Facethis toolFree tier for public models and SpacesNot requiredNoneUSD 9
Stable DiffusionUnlimited if you run it locallyNot requiredNoneUSD 0

Listed on ToolVault. Details change often — if something here is out of date, tell us.