Streamlit vs Gradio

Choosing between Streamlit and Gradio depends on your project requirements, team expertise, and target platform. Streamlit is ideal for data dashboards, CSV explorers, ML demos, and internal analytics tools, while Gradio excels at ML model demos, image processing tools, NLP interfaces, and API wrappers. Both are fully supported in LoomCode AI with live preview and one-click deployment.

Side-by-Side Comparison

Feature	Streamlit	Gradio
Category	Data & Analytics	Data & Analytics
Primary Libraries	Streamlit, Pandas, NumPy, Plotly	Gradio, Pandas, NumPy, Matplotlib
Learning Curve	beginner	beginner
Ideal For	data dashboards, CSV explorers, ML demos, and internal analytics tools	ML model demos, image processing tools, NLP interfaces, and API wrappers
Ecosystem	Streamlit turns Python scripts into interactive web applications.	Gradio is the standard for building ML model demos, used by over 500,000 Hugging Face Spaces.
Best App Types	Data apps, dashboards, ML demos	Data apps, dashboards, ML demos
Styling	Built-in widgets	Built-in widgets
Database Support	Via Python libraries	Via Python libraries
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AI Code Generation
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Streamlit

beginner

Streamlit data apps with interactive widgets and charts

Ideal for: data dashboards, CSV explorers, ML demos, and internal analytics tools

Explore Streamlit template

Gradio

beginner

Gradio ML demos with interactive inputs and outputs

Ideal for: ML model demos, image processing tools, NLP interfaces, and API wrappers

Explore Gradio template

Same Prompt, Different Output

Here is what happens when you give the same prompt to Streamlit and Gradio in LoomCode AI:

Prompt

Build a CSV file analyzer that loads a CSV, shows column stats, and generates bar and line charts for numeric columns

Streamlit Output

With Streamlit, the AI generates a Streamlit app using Pandas, NumPy, Plotly for file upload, data parsing, stats, and chart rendering. The layout uses Streamlit's native widget system — st.file_uploader, st.dataframe, and st.plotly_chart in a linear script.

Gradio Output

With Gradio, the same prompt produces a Gradio app using Pandas, NumPy, Matplotlib for the same file upload, data parsing, stats, and chart rendering. Gradio's component model handles UI differently — using declarative Interface blocks with automatic input-output wiring. Same data processing, different UI paradigm.

When to Choose Streamlit

Streamlit turns Python scripts into interactive web applications. Used by data teams at companies like Snowflake, it eliminates the frontend barrier for data scientists who need to share dashboards, tools, and ML demos.

Interactive widgets (sliders, dropdowns, file uploads) with zero frontend code
Built-in charting and data display components for instant data visualization
Automatic reactive updates — change a widget and the entire app refreshes
Native file upload and download support for data-driven workflows
Single Python file deployment — no HTML, CSS, or JavaScript needed

Build with Streamlit

When to Choose Gradio

Gradio is the standard for building ML model demos, used by over 500,000 Hugging Face Spaces. It provides ready-made UI components that connect directly to Python functions, making it trivial to demo any machine learning model.

Pre-built input/output components for images, text, audio, and video
Automatic REST API generation for every interface you create
Shareable public demo links with one line of code
Tabbed interfaces and Blocks layout for complex multi-step workflows
Native integration with Hugging Face for model deployment and sharing

Build with Gradio

The Verdict

If you need data dashboards, CSV explorers, ML demos, and internal analytics tools, Streamlit is the stronger choice with its interactive widgets (sliders, dropdowns, file uploads) with zero frontend code. If your project requires ML model demos, image processing tools, NLP interfaces, and API wrappers, Gradio's pre-built input/output components for images, text, audio, and video gives it the edge. With LoomCode AI, you can try both in seconds — describe your app idea and compare the generated code side by side.

Try Both Frameworks

Popular Apps to Build with Both

Todo App

A task management app with add, edit, delete, and status tracking

With Streamlit →With Gradio →

Note Taking App

A notes app with rich text editing, categories, and search

With Streamlit →With Gradio →

Habit Tracker

A daily habit tracking app with streaks and progress visualization

With Streamlit →With Gradio →

Bookmark Manager

A bookmark organizer with folders, tags, and search

With Streamlit →With Gradio →

Invoice Generator

An invoice creation tool with line items, calculations, and PDF-style output

With Streamlit →With Gradio →

Analytics Dashboard

A data dashboard with KPI cards, charts, and trend analysis

With Streamlit →With Gradio →

Which Should You Choose?

Choose Streamlit if:

✓Interactive widgets (sliders, dropdowns, file uploads) with zero frontend code
✓Built-in charting and data display components for instant data visualization
✓Automatic reactive updates — change a widget and the entire app refreshes

Choose Gradio if:

✓Pre-built input/output components for images, text, audio, and video
✓Automatic REST API generation for every interface you create
✓Shareable public demo links with one line of code

Try both in LoomCode AI — describe your app once and generate it in Streamlit and Gradio to compare the results side by side.

Frequently Asked Questions

Should I use Streamlit or Gradio for my project?

The right choice depends on your project requirements. Streamlit is ideal for data dashboards, CSV explorers, ML demos, and internal analytics tools. Gradio excels at ML model demos, image processing tools, NLP interfaces, and API wrappers. If you're building in the same domain, consider team expertise and learning curve — Streamlit has a beginner learning curve while Gradio is beginner. With LoomCode AI, you can generate working code in both frameworks and compare the output side by side.

Can I switch between Streamlit and Gradio in LoomCode AI?

Yes. LoomCode AI supports both Streamlit and Gradio in the same session. You can describe your app idea once and generate it in each framework, then compare the results. Switch frameworks at any time — no need to start over. Both support live preview and one-click deployment.

Which framework generates better code with AI?

Both Streamlit and Gradio produce high-quality AI-generated code in LoomCode AI. Streamlit tends to leverage its interactive widgets (sliders, dropdowns, file uploads) with zero frontend code, while Gradio benefits from pre-built input/output components for images, text, audio, and video. The best output depends on your prompt — be specific about your requirements. Try the same prompt in both frameworks to see which fits your use case better.

Is Streamlit or Gradio easier to learn?

Streamlit has a beginner learning curve, and Gradio has a beginner learning curve. Both are generally considered more approachable. Using LoomCode AI to generate working examples in either framework can accelerate your learning — you'll see real, runnable code that you can modify and experiment with.

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