Replicate
Run and fine-tune thousands of open-source AI models with one line of code via a cloud API, billed per second of GPU or CPU compute
USAGE-BASED Verified JUN 23, 2026
Hugging Face
The open-source AI hub — 2M+ models, 500k+ datasets, hosted Spaces apps, and routed inference, with free accounts and usage-based compute
Hugging Face is the default registry for open machine learning: 2M+ models, 500k+ datasets, and 1M+ Spaces applications. A Hub account is free; PRO is $9/month, Team is $20/user/month, and Enterprise is $50/user/month. Compute is billed separately and by usage — Spaces hardware from free CPU up to $20.00/hour for 8x A100, Inference Endpoints from $0.03/hour, and Inference Providers passed through at provider cost with no Hugging Face markup.
Verified JUL 20, 2026 FREEMIUM Live
What is Hugging Face?
Hugging Face is the central registry and hosting platform for open machine learning. The Hub stores 2M+ models, 500k+ datasets, and 1M+ Spaces applications, all versioned with git and served over a CDN. Most developers meet it first through the open-source libraries — transformers, diffusers, datasets, PEFT — which pull weights straight from the Hub with a single identifier such as an organisation and model name. Those libraries work without an account, which is why the Hub became the de facto distribution channel for open-weight releases from Meta, Alibaba, Mistral, Google, and thousands of independent labs.
Around that registry sit three paid compute products. Spaces host interactive Gradio, Streamlit, or Docker demos, free on CPU Basic and on the shared ZeroGPU pool, or upgraded to dedicated hardware billed hourly from $0.03 for a CPU upgrade to $20.00 for 8x A100. Inference Endpoints deploy one model to dedicated autoscaling infrastructure on AWS, Azure, or GCP, from $0.03 per hour on CPU up to $9.25 per hour for a B200. Inference Providers is a routing layer over 17 external vendors — Groq, Together, Cerebras, Fireworks, Replicate and others — reachable through one key, with provider rates passed through unchanged and no Hugging Face fee on top. Subscriptions sit alongside all of this: PRO at $9 per month raises personal quotas, Team at $20 per user per month adds SSO and audit logs, and Enterprise at $50 per user per month adds SCIM and dedicated support. Hub storage is separately metered at $12/TB/month for public repositories and $18/TB for private, dropping to $8 and $12 respectively above 500TB.
Who is it for?
Hugging Face is aimed at anyone who works with open models rather than only closed APIs. The free tier is genuinely usable for public work, and the paid tiers mostly buy quota, privacy, and organisational controls rather than new capability. Teams that never touch open weights and only call a hosted frontier model will get less from it than teams fine-tuning, self-hosting, or comparing models — for pure coding assistance, Claude remains the stronger choice.
- ML engineers and researchers who download, fine-tune, and evaluate open-weight models and need somewhere to version checkpoints and share results.
- Developers shipping model-backed features who want one API key across 17 inference vendors instead of separate billing relationships, similar to what OpenRouter does for chat models.
- Teams deploying open models to production who need dedicated autoscaling endpoints without building GPU infrastructure — the same trade-off offered by Replicate, Modal, and Baseten.
- Enterprises with compliance requirements needing SSO, audit logs, storage regions, and SCIM provisioning on top of a private model registry, which is where the Team and Enterprise per-seat plans apply.
- Educators and demo builders who want a free public URL for an interactive model demo, using free CPU Basic or ZeroGPU Spaces hardware.
How much does Hugging Face cost?
Starting price: $9/mo · Free tier: yes · Model: freemium
Pricing verified JUL 20, 2026
Price history tracked from June 2026
| Plan | Price | Includes |
|---|---|---|
| Hub account | Free | Unlimited public models, datasets, and Spaces · CPU Basic Spaces hardware (2 vCPU, 16GB) free · ZeroGPU Spaces hardware free, with standard queue priority · $0.10 monthly Inference Providers credits |
| PRO | $9/mo | 10x private storage capacity, 2x public storage capacity · 20x included inference credits ($2.00/month) · 8x ZeroGPU quota and highest queue priority · Spaces Dev Mode (SSH / VS Code) and features preview · Dataset Viewer for private datasets, personal blog publishing |
| Team | $20/user/mo | Self-serve by credit card, no sales call · SSO via SAML and OIDC, centralized token control and approvals · Storage Regions for data location control, Audit Logs · Resource Groups for granular access control, repo analytics · All members get ZeroGPU and Inference Providers PRO benefits |
| Enterprise | $50/user/mo | Everything in Team, sold through sales · Highest storage, bandwidth, and API rate limits · SCIM automated user provisioning · Managed billing with annual commitments, compliance processes · Dedicated support and custom onboarding |
| Hub storage | $12–18/TB/mo | Base: $12/TB public repositories, $18/TB private · Volume discounts at 50TB (-20%), 200TB (-25%), 500TB (-33%) · Floor of $8/TB public and $12/TB private at 500TB+ · Egress and CDN included at no extra cost |
| Spaces hardware | $0–$23.50/hr | CPU Basic and ZeroGPU free; CPU Upgrade $0.03/hr · Nvidia T4 small $0.40/hr, 1x L40S $1.80/hr · A100 large $2.50/hr; 8x A100 $20.00/hr; 8x L40S $23.50/hr |
| Inference Endpoints | from $0.03/hr | Dedicated autoscaling deployments, no cold starts · CPU from $0.03/hr; Nvidia T4 $0.50/hr, L40S $1.80/hr · A100 $2.50/hr, H100 $4.50/hr, H200 $5.00/hr, B200 $9.25/hr |
| Inference Providers | Pay-as-you-go | Provider rates passed through with no Hugging Face markup · Monthly credits: $0.10 free, $2.00 PRO, $2.00 per seat on Team · Routes to 17 providers including Groq, Together, Cerebras, Replicate |
What are Hugging Face's key features?
- Model, dataset, and Spaces hub with git-based versioning and large-file storage
- Spaces — hosted Gradio, Streamlit, and Docker apps with on-demand GPU upgrades
- ZeroGPU — shared Nvidia RTX Pro 6000 Blackwell capacity, free with quota, 8x quota on PRO
- Inference Providers — one API routing to 17 third-party inference vendors at pass-through pricing
- Inference Endpoints — dedicated autoscaling model deployments billed hourly across AWS, Azure, and GCP
- Open-source library stack: transformers, diffusers, datasets, PEFT, TRL, accelerate, smolagents
- Dataset Viewer, model evaluation tooling, and leaderboards for comparing models
- Enterprise controls: SAML/OIDC SSO, SCIM, audit logs, resource groups, storage regions
What people use Hugging Face for
- 01 Downloading and running open-weight models (Llama, Qwen, GLM, Mistral) locally via the transformers library
- 02 Hosting an interactive model demo as a Gradio or Docker Space, on free CPU or paid GPU hardware
- 03 Calling 200+ hosted models through one Inference Providers API key instead of signing up with each provider
- 04 Deploying a specific model on dedicated autoscaling infrastructure via Inference Endpoints for production traffic
- 05 Storing and versioning private model checkpoints and datasets with git-based workflows and access controls
- 06 Discovering and evaluating datasets with the Dataset Viewer before committing to a training run
Pros and cons
| Pros | Cons |
|---|---|
| The free Hub account covers unlimited public repos plus free CPU Basic and ZeroGPU Spaces hardware | Two separate billing systems — flat subscription plus usage-based compute — make total monthly cost hard to forecast |
| Inference Providers charges provider rates with no markup, so routing through Hugging Face costs no more than going direct | Free inference credits of $0.10 per month are token-sized; any real evaluation requires PRO or purchased credits |
| Breadth is unmatched — 2M+ models and 500k+ datasets make it the practical starting point for any open-model project | Private repository storage at $18/TB/month is 50% more than public at $12/TB, so keeping checkpoints private is a real cost |
| Storage pricing is published per terabyte with egress and CDN included, rather than metered separately | Enterprise at $50/user/month is per-seat and sales-gated, which is expensive for orgs that only need SCIM or higher rate limits |
| The open-source libraries work without any Hugging Face account, so the platform is not a hard dependency | With 2M+ models there is no curation guarantee: licences vary widely, and permissive-looking repos can carry non-commercial or gated terms |
| Spaces GPU hardware bills for uptime rather than requests, so an idle upgraded Space keeps costing money until it is paused |
What are the best Hugging Face alternatives?
Together AI
AI cloud for running, fine-tuning, and deploying open-source models via serverless inference and on-demand GPU clusters
USAGE-BASED Verified JUN 24, 2026
Modal
Python-first serverless platform for running, deploying, and fine-tuning AI models on GPUs, billed per second with scale-to-zero and no idle charges
USAGE-BASED Verified JUL 10, 2026
Baseten
Usage-based AI inference cloud to deploy and serve ML models on dedicated GPUs with per-minute billing, per-token Model APIs, and autoscaling
USAGE-BASED Verified JUL 17, 2026
Fireworks AI
High-speed inference and fine-tuning cloud for open-weight LLMs, image, and audio models via a usage-based API
USAGE-BASED Verified JUL 10, 2026
OpenRouter
Unified API to 400+ LLMs from 70+ providers through one OpenAI-compatible endpoint, with automatic failover and pass-through token pricing
USAGE-BASED Verified JUN 23, 2026
How people make money with Hugging Face
- Publish a fine-tuned niche model plus a demo Space on the Hub, then monetise the same weights through a paid hosted endpoint billed per request while the Hub listing handles discovery
- Sell ML platform consulting to teams migrating onto the Hub — scope it as a fixed setup fee for Spaces and Inference Endpoints, then a monthly retainer for model maintenance and cost tuning
- Package curated, licence-cleared training datasets as private Hub repositories and license them per buyer, passing the per-terabyte storage cost through to the customer
Frequently asked questions
Is Hugging Face free?
Yes. A Hub account is free and includes unlimited public models, datasets, and Spaces, plus free CPU Basic and ZeroGPU hardware for Spaces. Free accounts also receive $0.10 in monthly Inference Providers credits. Paid plans begin with PRO at $9 per month for higher storage, quota, and credits.
How much does Hugging Face PRO cost?
PRO costs $9 per month for a personal account. It provides 10x private storage capacity, 2x public storage, 20x the included inference credits ($2.00 monthly instead of $0.10), 8x ZeroGPU quota with highest queue priority, Spaces Dev Mode over SSH or VS Code, private dataset viewing, and a PRO badge.
What is the difference between the Team and Enterprise plans?
Team costs $20 per user per month and is self-serve by credit card, adding SSO, storage regions, audit logs, resource groups, and repository analytics. Enterprise costs $50 per user per month through sales and layers on SCIM provisioning, the highest rate limits, advanced security controls, managed billing with annual commitments, compliance processes, and dedicated support.
How much do Hugging Face Spaces GPUs cost?
Spaces hardware is billed hourly. CPU Basic with 2 vCPU and 16GB is free, and so is ZeroGPU. Paid tiers run from CPU Upgrade at $0.03 per hour and an Nvidia T4 small at $0.40 per hour, up to an A100 large at $2.50 per hour and 8x A100 at $20.00 per hour.
Does Hugging Face add a markup on inference?
No. Inference Providers routes requests to 17 third-party vendors and passes through their rates with no additional fee. Every account gets monthly credits — $0.10 on free, $2.00 on PRO, and $2.00 per seat on Team or Enterprise — and can purchase extra credits to keep running past the allowance.
How much does Hugging Face Hub storage cost?
Storage is billed per terabyte per month with egress and CDN included. Base rates are $12/TB for public repositories and $18/TB for private ones. Volume discounts apply above 50TB (-20%), 200TB (-25%), and 500TB (-33%), taking public storage down to $8/TB and private to $12/TB. Beyond 500TB, pricing is custom.
What are Inference Endpoints and how are they billed?
Inference Endpoints are dedicated, autoscaling deployments of a single model on your own instance, billed hourly rather than per token. CPU instances start at $0.03 per hour. GPU options range from an Nvidia T4 at $0.50 per hour to an H100 at $4.50 per hour and a B200 at $9.25 per hour.