Want to learn how to deploy a Gradio app on Hugging Face Spaces for free? Hugging Face Spaces is the friendliest free home for AI demos: you get a real NVIDIA RTX Pro 6000 Blackwell GPU behind a public URL with no credit card. This beginner’s guide walks you through your first Gradio app and the 2026 free tier limits that catch most newcomers.
Verdict
StacksFree Verdict: 8.2/10 — Hugging Face Spaces provides the most accessible path for beginners to deploy AI models with a real GPU without a credit card, but its strict daily GPU quota and two-Space cap on the free tier require strategic resource management.
How This Guide Was Built
This guide is based on the official Hugging Face documentation, the Hugging Face pricing page, and community reports — we did not run the tool hands-on. We verified the free tier limits, ZeroGPU quota system, signup flow, and first-Space deployment steps from official sources. Paid PRO features were not tested. Last verified: August 2026.
What is Hugging Face Spaces?
Hugging Face Spaces is a free hosting platform for interactive AI/ML demos and web apps, supporting Gradio, static HTML, and Docker SDKs. It sits next to the world’s largest open-model hub, making it the natural place to share a model. In 2026, the free compute path is exclusively through ZeroGPU, which grants access to a shared NVIDIA RTX Pro 6000 Blackwell GPU (Hugging Face Spaces overview). For a deeper dive, visit our Hugging Face Spaces tool page.
How do I deploy a Gradio app on Hugging Face Spaces for free?
To deploy a Gradio app on Hugging Face Spaces for free, create a verified account, make a new Space, pick the Gradio SDK and ZeroGPU hardware, and upload your files — the build runs automatically and ends with a live public URL. Your code needs a gr.Interface, with GPU work wrapped in @spaces.GPU functions (official Gradio Space docs).
Here’s a simplified workflow:
- Sign Up: Create a free account at huggingface.co/join and verify your email.
- Create Space: Go to huggingface.co/spaces, click Create new Space, name it, set visibility to Public, and choose Gradio as the SDK.
- Select Hardware: Under “Space Hardware,” choose ZeroGPU.
- Add Files: Create
requirements.txt(e.g.,transformers,torch) andapp.py. Yourapp.pyshould look like this:
import gradio as gr
import spaces
@spaces.GPU
def predict(image):
# Your GPU-based inference code here
# e.g., from transformers import pipeline
return result
iface = gr.Interface(fn=predict, inputs="image", outputs="label")
iface.launch()- Commit & Deploy: Push your files to the Space. It will auto-rebuild. Your live app will be at
https://<your-username>-<space-name>.hf.space.
Free tier limits to watch
The 2026 free tier has real constraints: at most two ZeroGPU Spaces, a 5-minute daily GPU quota that resets 24 hours after your first GPU usage, and per-Space limits of 16 GB RAM, 2 CPU cores, and 50 GB of ephemeral disk. Spaces sleep after 48 hours of inactivity and cold-start for the next visitor (ZeroGPU docs).
Key limits:
- ZeroGPU Spaces: Up to 2 per free account; requires an account over 30 days old with a verified email.
- GPU Quota: 5 minutes per day on the free tier.
- ZeroGPU Hardware: NVIDIA RTX Pro 6000 Blackwell;
large(48 GB VRAM, 1× quota) andxlarge(96 GB VRAM, 2× quota) options. - Storage: 100 GB for private repos; public repos use generous, best-effort free storage (storage limits).
- Disk: Ephemeral 50 GB wiped on restart.
- Sleep: After 48 hours of inactivity.
- Paid Plan: Creating new compute Spaces (CPU or Docker) requires a PRO plan ($9/month).
Common mistakes
Beginners trip on the 2026 platform in predictable ways. A frequent error is assuming the free-looking “CPU Basic” hardware lets you create a compute Space — it now requires a paid plan, so always pick ZeroGPU for free compute. Not specifying duration in @spaces.GPU wastes your 5-minute daily quota, and storing data on the ephemeral 50 GB disk loses it on restart (Spaces overview).
Other mistakes to avoid:
- Assuming Streamlit is a free built-in SDK — it is deprecated, and deploying via Docker now requires a paid plan.
- Expecting private Spaces on the free tier — those are a PRO feature.
- Forgetting that model loads count against your daily GPU quota — keep
duration=tight.
Planning your 5-minute ZeroGPU quota
Five minutes sounds small until you realize how far a single inference call goes. The quota is measured in GPU-seconds consumed while a @spaces.GPU function runs, and the duration parameter tells the scheduler how long to keep the GPU warm after a request. The practical math: if each prediction takes about 2 seconds of GPU time, one 5-minute daily quota covers roughly 150 calls; if your model takes 10 seconds per call, that drops to about 30 calls. Choosing the large size (48 GB VRAM, 1× quota) instead of xlarge (96 GB VRAM, 2× quota) effectively doubles the number of calls you can make in a day (ZeroGPU docs).
To stretch the quota, do three things. First, move model loading outside the @spaces.GPU function so cold model weights are not reloaded for every request. Second, set duration to a value that matches your expected burst — too short and every visitor pays a cold start, too long and idle GPU time eats your quota. Third, precompute anything you can: tokenizers, embeddings, and rule-based preprocessing run on CPU and do not consume GPU quota. The reset clock is also per-account, not per-Space, so spreading work across your two ZeroGPU Spaces does not double the daily budget.
When the PRO plan is worth it
The free tier is designed for demos, not operations. The moment you need any of the following, the PRO plan ($9/month) is the cheaper path than fighting the limits: more than two ZeroGPU Spaces, private Spaces, CPU or Docker-based compute, longer sleep windows, or a daily quota that survives real usage. A common upgrade trigger is a demo that starts getting shared — a single viral link will exhaust 5 minutes of GPU time in the first hour of traffic (Hugging Face pricing).
A reasonable middle path is to keep public demos on the free tier and only pay for the Spaces that need privacy or scale. Because the PRO plan is per-user rather than per-Space, one paid account can host multiple private or compute-based Spaces, which makes it a better value than paying per project. If your use case is purely a static portfolio page or documentation site, you do not need Spaces compute at all — a static host such as Vercel or Netlify is free and better suited.
How Spaces compares to other free tiers
Hugging Face Spaces is the only major free tier that gives you a real GPU with no credit card, but it is also the most constrained in compute time. Static hosting platforms give you unlimited free bandwidth for pages that do not run server-side code. CPU-oriented platforms like Render’s free tier can run a persistent web service but cannot execute GPU workloads, which rules out most modern AI inference. Docker-based hosts give you full control but bill for CPU and memory continuously, which makes a GPU demo prohibitively expensive to keep warm.
For an AI demo, the ranking is usually clear: if you need GPU inference and can tolerate a daily quota, Spaces is the right call. If your app is mostly static with a little server logic, a CPU platform or static host is simpler and has no quota to manage. The tradeoff is between capability and control — Spaces wins on capability per dollar spent (zero), while static hosts win on uptime and predictability.
FAQ
Short answers to the questions beginners ask most, with sources inline.
Is Hugging Face Spaces really free?
Yes, Hugging Face Spaces offers a genuinely free tier for hosting AI demos. Free accounts get unlimited static hosting and access to ZeroGPU, which provides a shared NVIDIA RTX Pro 6000 Blackwell GPU. However, free compute is restricted to Gradio apps using ZeroGPU, with a daily quota of 5 minutes of GPU time and a maximum of two active ZeroGPU Spaces per account (Hugging Face pricing).
Can I host a Streamlit app on Hugging Face Spaces for free?
No, the built-in Streamlit SDK is now deprecated. To host a Streamlit app, you must use the Docker SDK with a Streamlit template, which falls under “compute” and requires a paid PRO plan ($9/month) (Streamlit SDK deprecation). For a free alternative, consider using the Gradio SDK to build a similar interface.
How much GPU time do free accounts get per day?
Free accounts receive exactly 5 minutes of ZeroGPU usage per day. This quota applies to the NVIDIA RTX Pro 6000 Blackwell hardware and resets 24 hours after your first GPU usage of the day. Using the xlarge size (96 GB VRAM) consumes two units of this quota, so specifying large is more efficient (ZeroGPU docs).
Why does my Space sleep after 48 hours?
Spaces on the free tier are designed for demos, not always-on services, so they sleep after 48 hours of inactivity and cold-start for the next visitor. The wake-up takes time because the container rebuilds and the model loads again — which also draws down your daily GPU quota. If you need a Space that stays warm or wakes faster, that is a PRO feature (ZeroGPU docs).
Can I use Spaces for a production app?
For light production traffic, yes — many teams host public model demos and API front-ends on Spaces. The constraints are real, though: the 5-minute daily GPU quota, the two-Space cap, and the 48-hour sleep cycle make it unsuitable for sustained traffic or anything with an SLA. A common pattern is to use Spaces for public demos and move production workloads to a paid compute platform. Treat Spaces as the best free way to validate an AI product in front of users, not as the final hosting layer.
Where to go next
You now have the steps to get your first AI demo online for free. For more details on the platform’s features and limits, explore our detailed Hugging Face Spaces tool page. If you’re comparing hosting options, see how static hosting stacks up in our Vercel free tier guide or Netlify free tier guide. Ready to deploy? Start creating your Space directly on the Hugging Face Spaces hub.