reacher-z/Awesome-CUA
Open, source-backed catalog of computer-use agents: reviewed papers, GUI models, datasets, benchmarks, tools, and reusable JSONL/SQLite data.
- Stars
- 384
- Forks
- 137
- Open issues
- 2.1k
- Last push
- today
Awesome-CUA star history
+171 this week
Get Awesome-CUA running
Setup: Hard · build from source, typically 1–3 hours
Full install steps in the README →Can I sell what I build with it?
Check first
A guide, not legal advice.
About Awesome-CUA
Awesome-CUA is a free, open-source AI resource list by reacher-z, written mainly in Python. Open, source-backed catalog of computer-use agents: reviewed papers, GUI models, datasets, benchmarks, tools, and reusable JSONL/SQLite data. It has 384 GitHub stars and 137 forks, and was last updated today. GitHub doesn't detect a standard license, so check the repository before using it commercially.
- License
- Not detected
- Commercial use
- No license
- Language
- Python
- Stars
- 384
- Last update
- today
- Runs on Mac
- Not stated
- GPU
- Not stated
- Paid API key
- Not stated
- Self-hostable
- Not stated
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Awesome-CUA FAQ
Can I use Awesome-CUA commercially?
Unclear. No license was detected, which legally means all rights are reserved. Ask the author before using it commercially. This is a plain-English summary, not legal advice.
Is Awesome-CUA free?
Yes. Awesome-CUA is open source and free to use. GitHub doesn't detect a standard license, so check the repository before using it commercially.
Does Awesome-CUA run on a Mac?
The project doesn't say. Check its installation guide before you start.
Does Awesome-CUA need a GPU?
The project doesn't state hardware needs. AI models generally run much faster with a GPU.
Is Awesome-CUA still maintained?
Yes. It was last updated today and has 2,091 open issues on GitHub.
How hard is Awesome-CUA to set up?
Hard: typically 1–3 hours, using build from source.
What are alternatives to Awesome-CUA?
Similar free, open-source tools include 500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code, CVPR2026-Papers-with-Code, Prompt-Engineering-Guide, deep-learning-drizzle.
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