Hugging Face Pricing (2026)

It's a layered hybrid: flat per-seat fees for PRO/Team/Enterprise get you account-level perks, but the real spend lives in metered usage — storage per TB, Spaces hardware by the GPU/CPU hour, and Inference Endpoints by instance-hour. So the subscription is really just the entry ticket, and compute is where they make money.

PRO Account
$9/mo
Team Popular
$20/mo
Enterprise
$50/mo
Verified Sep 29, 2026 Official pricing page
Screenshot of Hugging Face's pricing page showing its plans and prices
Their pricing page, captured Sep 29, 2026

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PRO Account

$9/mo
  • 10× private storage capacity
  • 2× public storage capacity
  • 20× included inference credits
  • 8× ZeroGPU quota and highest queue priority
  • Host ZeroGPU, Gradio & Docker Spaces
  • Spaces Dev Mode
  • Personal blog publishing
  • Dataset Viewer for private datasets
  • Show your support with a PRO badge

Team

Popular
$20/mo
  • SSO support (SAML & OIDC)
  • Data location control with Storage Regions
  • Detailed action reviews with Audit Logs
  • Granular access control via Resource Groups
  • Repository usage Analytics
  • Advanced auth policies and repository visibility controls
  • Centralized token control and approvals
  • Dataset Viewer for private datasets
  • Create Gradio & Docker Spaces, with advanced compute options

Enterprise

$50/mo
  • Highest storage, bandwidth, and API rate limits
  • Automated user management with SCIM provisioning
  • Advanced security and access controls
  • Managed billing with annual commitments
  • Legal and Compliance processes
  • Dedicated support

Does Hugging Face have a free plan?

No. Hugging Face lists no free plan or trial on its pricing page. Paid plans start at $9/mo.

Want free? OpenAI, Anthropic, and AssemblyAI have free plans: see all Hugging Face alternatives →

AI Pricing Analysis

Pricing Model

It's a layered hybrid: flat per-seat fees for PRO/Team/Enterprise get you account-level perks, but the real spend lives in metered usage — storage per TB, Spaces hardware by the GPU/CPU hour, and Inference Endpoints by instance-hour. So the subscription is really just the entry ticket, and compute is where they make money.

Tier Strategy

PRO is built for individual devs who want faster inference and some extra storage without touching infrastructure. Team is the jump for small orgs that need shared billing and collaboration, while Enterprise kicks in when companies need SSO, access controls, and compliance guardrails — the trigger is usually a security or procurement requirement, not just headcount.

Competitive Positioning

At $9–$50/mo for the named tiers, Hugging Face undercuts most MLOps platforms on sticker price, positioning itself as the accessible on-ramp for ML teams rather than a premium enterprise play. They're clearly trying to win developers early and let usage-based compute pricing do the heavy lifting on revenue later.

Growth Lever

The subscription tiers barely gate any real capability — the actual growth lever is compute consumption on Spaces and Inference Endpoints, which scales silently as teams train and deploy more models. Storage costs also creep up as datasets and model checkpoints pile up, making usage overage the real expansion engine, not seat count.

Want the strategist's read on the live page? Read the AI teardown of Hugging Face's pricing page →

Hugging Face Pricing FAQ

How much does Hugging Face cost?
Paid plans start at $9/mo, going up to $50/mo for larger teams.
Is there a free plan?
No free plan. You'll need to commit to a paid plan to get started.
Can I try it before paying?
Not at the moment. There's no free trial or free plan listed on their pricing page.
How does the pricing work?
It's a layered hybrid: flat per-seat fees for PRO/Team/Enterprise get you account-level perks, but the real spend lives in metered usage — storage per TB, Spaces hardware by the GPU/CPU hour, and Inference Endpoints by instance-hour. So the subscription is really just the entry ticket, and compute is where they make money.
Which plan makes sense for me?
PRO is built for individual devs who want faster inference and some extra storage without touching infrastructure. Team is the jump for small orgs that need shared billing and collaboration, while Enterprise kicks in when companies need SSO, access controls, and compliance guardrails — the trigger is usually a security or procurement requirement, not just headcount.

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