Gradio
Build ML demos in Python — images, audio, video, text
📋 Overview
Gradio is the standard Python framework for building interactive demos of machine learning models — supporting images, audio, video, text, and 20+ input/output types with minimal code. Unlike Streamlit (which is general-purpose), Gradio is purpose-built for ML model demonstration: you define a function, specify input/output types, and Gradio generates a web UI with built-in examples, sharing, and Hugging Face Spaces integration. The framework supports real-time streaming, batch processing, and custom JavaScript components. It is the default UI for Hugging Face model demos and is used by OpenAI, Google, and Meta for model showcases.
✨ Key Features
- •43K+ GitHub stars — standard for ML model demos
- •20+ input/output types: image, audio, video, text, 3D, etc.
- •Hugging Face Spaces integration — one-click deploy
- •Real-time streaming for audio/video models
- •Built-in examples and sharing links
- •Custom JavaScript/Svelte components for advanced UIs
- •Used by OpenAI, Google, Meta for model showcases
🎯 The Problem It Solves
ML researchers and engineers need to demo models to stakeholders, collaborators, or the public — but building a web UI for each model is time-consuming. Gradio lets you wrap any Python function with a decorator and get a shareable web interface in seconds.
🔧 How It Works
You define a Python function that takes model inputs and returns predictions. The @gradio.ui decorator (or gr.Interface) generates a web UI with appropriate input widgets (image upload, microphone, text box, etc.) and output displays. Gradio handles the web server, WebSocket communication, and file handling. Demos can be shared via temporary links or deployed permanently to Hugging Face Spaces (free tier available). Custom components can be built with Svelte for advanced use cases.
🚀 Installation & Quick Start
Installation
See websiteQuick Start
- See documentation
✅ Pros
- •Fastest way to demo ML models
- •20+ input/output types out of the box
- •Hugging Face Spaces integration for free hosting
- •Real-time streaming for audio/video
- •Built-in examples and sharing
- •Custom components with Svelte
- •Apache 2.0 licensed — completely free
❌ Cons
- •Not designed for production apps (stateless)
- •No built-in authentication or user management
- •Complex multi-step workflows require workarounds
- •Limited UI layout customization
- •Performance degrades with large file uploads
💬 Practitioner Verdict
“Gradio is the default choice for ML model demos — the input/output type system is intuitive, the Hugging Face Spaces integration is seamless, and the community components extend functionality significantly. The trade-off: not designed for production apps (stateless, no auth), complex multi-step workflows require workarounds, and custom UI layouts are limited. For ML researchers who need to share models quickly, Gradio is unmatched.”
Self-Hosted (Free)
Open source, MIT/Apache licensed. Run it yourself.
⭐ Star & Clone on GitHubFree forever. Your infrastructure, your data.
Hugging Face Spaces Free
CPU, 50GB storage, public
- CPU only
- 50GB storage
- Public spaces
Hugging Face Spaces Pro
GPU, private spaces
- GPU support
- Private spaces
- Priority queue
Deployment Options
Ways to run Gradio in production
📊 Specifications
- Language
- Python
- License
- Apache-2.0
- Platform
- Linux, macOS, Windows
- Supported Models
- REST API, CLI
💰 Pricing Reality
100% free and open source under Apache 2.0. Hugging Face Spaces: Free tier (CPU, 50GB storage), Pro /mo (GPU, private spaces), Enterprise custom. No per-deployment fees.