cua
★ 31.1k
vs
verl-agent
★ 2.4k
cua vs verl-agent
cua: Cua is an open-source platform designed for building, benchmarking, and deploying AI agents capable of interacting with any computer. It provides isolated, self-hostable sandboxes using technologies like Docker, QEMU, and Apple Vz for agentic UI automation and secure code execution.; verl-agent: `verl-agent` extends veRL to train LLM agents using reinforcement learning, featuring a novel step-independent multi-turn rollout mechanism. This design ensures high scalability for long-horizon tasks by allowing customizable per-step input structures and memory management.
01
TL;DR
cuaLLM Infra · ★ 31.1k
When to choose:
- You are building Computer-Use agents and need robust, self-hostable isolated desktop/VM sandboxes (Docker, QEMU, Apple Vz).
- You need native app operating drivers, standardized benchmarking harnesses, and secure isolation for autonomous agent task execution.
When to skip:
- You only need simple UI macros on your personal physical machine (Windows-MCP or local desktop helpers are easier).
- Your agents interact solely via text APIs, shell commands, or databases and have no need for a virtual graphical desktop.
verl-agentLLM Infra · ★ 2.4k
Training large language model agents for complex multi-turn, long-horizon tasks.
02
Side-by-Side Comparison
Field
cuaverl-agentCategory
LLM Infra
LLM Infra
Stars
★ 31.1k
★ 2.4k
License
MIT
Apache-2.0
Install Command
curl -fsSL https://cua.ai/install.sh | sh
pip install -e .
Updated
1d ago
4mo ago
Open Source
Yes
Yes
Tags
AI Agents, Virtualization, UI Automation
LLM Agents, Reinforcement Learning, Deep Learning
03
Features
cua01Build AI agents for desktop UI automation and interaction.
02Provide isolated code execution environments (sandboxes).
03Benchmark computer-use models with standardized tasks.
04Train agents using reinforcement learning environments.
05Manage high-performance macOS/Linux VMs on Apple Silicon.
verl-agent01Multi-Turn Agent-Environment Interaction
02Fully Customizable Memory Module & Per-Step Input Structure
03Scalable for Very Long-Horizon Optimization
04Parallelized Gym-Style Environments and Group Environments
05Diverse Reinforcement Learning Algorithms
04
Use Cases
cua↳Developing and deploying AI agents for autonomous desktop interaction and task completion.
↳Creating secure, isolated code execution environments for AI coding assistants and development workflows.
↳Benchmarking and training computer-use agents using standardized tasks and reinforcement learning.
verl-agent↳Training large language model agents for complex multi-turn, long-horizon tasks.
↳Developing reasoning agents for both visual and text-based environments.
↳Solving digital interface control, embodied AI, and search-related challenges.
05
Best For
cuaMost PopularEssentialTrending
verl-agent—
FAQ
FAQ
What is the difference between cua and verl-agent?
Both cua and verl-agent are in the LLM Infra category. cua has 31.1k stars, while verl-agent has 2.4k stars.
Which is better, cua or verl-agent?
The best choice depends on your use case. Choose cua if Developing and deploying AI agents for autonomous desktop interaction and task completion., and verl-agent if Training large language model agents for complex multi-turn, long-horizon tasks..
Is cua free or open source?
Yes, cua is open source on GitHub (MIT).
Is verl-agent free or open source?
Yes, verl-agent is open source on GitHub (Apache-2.0).
Cloud Infrastructure
AdDeploy on DigitalOcean
Host your MCP servers, Docker containers, and AI agents with $200 free credit over 60 days.
→