⚔️ Comparison
Streamlit vs Gradio — Which Should You Choose in 2026?
Both turn Python scripts into web apps, but they serve different purposes. Here's the full breakdown.
Quick answer: Choose Streamlit for data dashboards, complex layouts, and multi-page applications. Choose Gradio for rapid machine learning model demos, Hugging Face Spaces, and simple input-output interfaces. Streamlit is the better long-term choice for production data tools, while Gradio excels at quick ML prototypes.
What is Streamlit?
Streamlit is an open-source Python framework designed for building data-rich, interactive web applications. It is particularly popular among data scientists and analysts for creating dashboards, reports, and complex multi-page applications.
👉 Read our What is Streamlit Guide for a full introduction.
What is Gradio?
Gradio is an open-source Python library focused on building quick, interactive demos for machine learning models. It is deeply integrated with Hugging Face and is the de facto standard for sharing ML models on Hugging Face Spaces.
📊 Feature-by-Feature Comparison
| Feature | Streamlit | Gradio |
|---|---|---|
| Primary Use Case | Data dashboards, multi-page apps | ML model demos, Hugging Face Spaces |
| Learning Curve | Very easy | Extremely easy |
| Layout Control | Advanced (columns, tabs, sidebar, expander) | Basic (blocks, rows, columns) |
| Multi-page Support | Yes (pages/ directory, st.navigation) | Yes (with Blocks) |
| Caching | Built-in (@st.cache_data, @st.cache_resource) | Yes (@gr.cache) |
| Hugging Face Integration | Good | Native and seamless |
| Customization | Moderate (via CSS injection) | Limited |
| Best For | Production data apps, internal tools | AI demos, hackathons, ML prototyping |
When to Choose Streamlit
- You need a full data dashboard with multiple charts, KPIs, and filters.
- You are building a multi-page application (e.g., Dashboard, Settings, Reports).
- You want a sidebar for controls and a main area for visualizations.
- You want custom layouts using columns, tabs, and expanders.
- You are building a portfolio of Python data projects.
👉 Read our Streamlit Dashboard Tutorial.
When to Choose Gradio
- You want to demo a machine learning model quickly.
- You are deploying to Hugging Face Spaces.
- You need a simple input-output interface (e.g., text-to-image, image classification).
- You are building a hackathon project and need something fast.
- You want built-in support for audio, video, and image components.
⚖️ The Verdict
Choose Streamlit if you want to build a long-term, maintainable data application or dashboard. It is the more versatile, production-ready framework.
Choose Gradio if you want to show off a machine learning model as fast as possible, especially on Hugging Face. It is the fastest path from model to demo.
❓ Frequently Asked Questions
Is Streamlit better than Gradio?
It depends on your use case. Streamlit is better for full data dashboards and multi-page apps. Gradio is better for quick ML model demos and Hugging Face Spaces.
Can I use Streamlit and Gradio together?
Yes, but it's uncommon. Gradio is designed to be embedded (e.g., inside a Streamlit app) if you want to leverage specific ML components.
Which is easier to learn, Streamlit or Gradio?
Both are extremely easy. Gradio has a slightly lower barrier for basic ML demos because it requires less layout code. Streamlit requires a bit more setup for complex apps but gives more control.
Does Gradio support multi-page apps?
Gradio historically focused on single-page demos, but recent versions support multi-page apps with blocks and tabs. Streamlit remains more mature for complex multi-page architectures.
Which is better for deploying to Hugging Face Spaces?
Gradio. It is the default and most seamless framework for Hugging Face Spaces. Streamlit is also supported but requires slightly more configuration.