head to head · open source
generative-ai-for-beginners vs PixelRAG
generative-ai-for-beginners has 119,980 GitHub stars, 63,157 forks, 23 open issues and last shipped yesterday. PixelRAG has 9,984 stars, 856 forks, 19 open issues and last shipped 4 days ago. generative-ai-for-beginners leads on adoption by 1,102% (119,980 vs 9,984 stars). generative-ai-for-beginners is written in Jupyter Notebook under MIT; PixelRAG is written in Python under Apache-2.0. generative-ai-for-beginners has attracted 53% as many forks as stars, PixelRAG 9%. generative-ai-for-beginners was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (ai), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| generative-ai-for-beginners | PixelRAG | |
|---|---|---|
| GitHub stars | ★ 120K | ★ 10.0K |
| License | MIT | Apache-2.0 |
| Written in | Jupyter Notebook | Python |
| Last push | 2026-09-17 | 2026-09-14 |
| Forks | ⑂ 63K | ⑂ 856 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick generative-ai-for-beginners if
- You weight community size — 120K stars and counting
- You want the MIT license terms
- Your stack matches Jupyter Notebook
- You value the larger contributor base for long-term maintenance
pick PixelRAG if
- You want the PixelRAG feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Python
- You evaluated both and PixelRAG fits your workflow better
About generative-ai-for-beginners
Generative AI for Beginners is Microsoft's free, MIT licensed curriculum of 21 Jupyter Notebook lessons that teaches developers how to start building generative AI applications, aimed at newcomers who want a structured, self paced path instead of scattered documentation.
read the full generative-ai-for-beginners overview →
About PixelRAG
PixelRAG is the official open source codebase for the paper "PIXELRAG: Web Screenshots Beat Text for Retrieval Augmented Generation," an Apache 2.0 Python project from Berkeley SkyLab, BAIR and Berkeley NLP that renders web pages, PDFs and images to screenshot tiles and retrieves over those images instead of parsed text, built for RAG engineers, agent developers and researchers who need tables, charts, diagrams and layout to survive retrieval.
read the full PixelRAG overview →
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Frequently asked questions
Is generative-ai-for-beginners or PixelRAG more popular?
generative-ai-for-beginners has 119,980 GitHub stars and PixelRAG has 9,984. generative-ai-for-beginners has the larger community by that measure.
Are generative-ai-for-beginners and PixelRAG free?
Both are open source. generative-ai-for-beginners is licensed under MIT and PixelRAG under Apache-2.0. Neither carries a licence fee.
What is the difference between generative-ai-for-beginners and PixelRAG?
generative-ai-for-beginners is written in Jupyter Notebook and PixelRAG in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, generative-ai-for-beginners or PixelRAG?
Choose generative-ai-for-beginners if you want the larger community (119,980 stars) or its MIT licence terms. Choose PixelRAG if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.