AgentIndex icon
AgentIndex
verl-agent logo
verl-agent
★ 2.4k
vs
skrl logo
skrl
★ 1.1k

verl-agent vs skrl

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.; skrl: skrl is an open-source, modular Reinforcement Learning library implemented in Python, supporting PyTorch, JAX, and NVIDIA Warp. It focuses on modularity, readability, simplicity, and transparent algorithm implementation, also supporting various environment interfaces like Gym, Gymnasium, and Isaac Lab.

01

TL;DR

verl-agent logo
verl-agentLLM Infra · ★ 2.4k

Training large language model agents for complex multi-turn, long-horizon tasks.

Read verl-agent full review →
skrl logo
skrlLLM Infra · ★ 1.1k

Developing and testing new Reinforcement Learning algorithms

Read skrl full review →
02

Side-by-Side Comparison

Field
verl-agent logoverl-agent
skrl logoskrl
Category
LLM Infra
LLM Infra
Stars
★ 2.4k
★ 1.1k
License
Apache-2.0
MIT
Install Command
pip install -e .
pip install skrl
Updated
4mo ago
1d ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
LLM Agents, Reinforcement Learning, Deep Learning
Reinforcement Learning, Python, PyTorch
03

Features

verl-agent logoverl-agent
01Multi-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
skrl logoskrl
01Modular and extensible design
02Transparent algorithm implementation
03Multi-framework support (PyTorch, JAX, NVIDIA Warp)
04Compatibility with various environment interfaces (Gym, Gymnasium, PettingZoo, ManiSkill)
05Simultaneous training in NVIDIA Isaac Lab and MuJoCo Playground with scope-based resource sharing
04

Use Cases

verl-agent logoverl-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.
skrl logoskrl
↳Developing and testing new Reinforcement Learning algorithms
↳Training AI agents in various simulated environments (e.g., robotic control, game AI)
↳Research in Reinforcement Learning leveraging multiple backend frameworks
05

Best For

verl-agent logoverl-agent
—
skrl logoskrl
EssentialTrending
FAQ

FAQ

What is the difference between verl-agent and skrl?
Both verl-agent and skrl are in the LLM Infra category. verl-agent has 2.4k stars, while skrl has 1.1k stars.
Which is better, verl-agent or skrl?
The best choice depends on your use case. Choose verl-agent if Training large language model agents for complex multi-turn, long-horizon tasks., and skrl if Developing and testing new Reinforcement Learning algorithms.
Is verl-agent free or open source?
Yes, verl-agent is open source on GitHub (Apache-2.0).
Is skrl free or open source?
Yes, skrl is open source on GitHub (MIT).
Cloud Infrastructure
Ad

Deploy on DigitalOcean

Host your MCP servers, Docker containers, and AI agents with $200 free credit over 60 days.

Claim $200 Free Credit
→

Related

Alternatives to verl-agent →Alternatives to skrl →verl-agent details →skrl details →