AgileRL logo
AgileRL
★ 960
vs
verl-agent logo
verl-agent
★ 2.4k

AgileRL vs verl-agent

AgileRL: AgileRL is a Deep Reinforcement Learning library that streamlines development by introducing RLOps, or MLOps for reinforcement learning. It significantly reduces training time and hyperparameter optimization using pioneering evolutionary techniques, offering up to 10x faster optimization than state-of-the-art methods.; 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

AgileRL logo
AgileRLLLM Infra · ★ 960

Training single-agent tasks in standard Gymnasium environments.

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

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

02

Side-by-Side Comparison

Field
AgileRL logoAgileRL
verl-agent logoverl-agent
Category
LLM Infra
LLM Infra
Stars
★ 960
★ 2.4k
License
Apache-2.0
Apache-2.0
Install Command
pip install agilerl
pip install -e .
Updated
1d ago
4mo ago
Open Source
Yes
Yes
Tags
Reinforcement Learning, Deep Learning, Hyperparameter Optimization
LLM Agents, Reinforcement Learning, Deep Learning
03

Features

AgileRL logoAgileRL
01RLOps integration for streamlined reinforcement learning development.
02Pioneering evolutionary hyperparameter optimization (HPO) techniques.
03Comprehensive suite of evolvable on-policy, off-policy, offline, multi-agent, and contextual multi-armed bandit algorithms.
04Support for distributed training.
05Algorithms for Large Language Model (LLM) finetuning.
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
04

Use Cases

AgileRL logoAgileRL
↳Training single-agent tasks in standard Gymnasium environments.
↳Developing multi-agent reinforcement learning solutions in PettingZoo environments.
↳Fine-tuning Large Language Models (LLMs) with reinforcement learning algorithms.
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.
05

Best For

AgileRL logoAgileRL
TrendingHidden Gem
verl-agent logoverl-agent
—
FAQ

FAQ

What is the difference between AgileRL and verl-agent?
Both AgileRL and verl-agent are in the LLM Infra category. AgileRL has 960 stars, while verl-agent has 2.4k stars.
Which is better, AgileRL or verl-agent?
The best choice depends on your use case. Choose AgileRL if Training single-agent tasks in standard Gymnasium environments., and verl-agent if Training large language model agents for complex multi-turn, long-horizon tasks..
Is AgileRL free or open source?
Yes, AgileRL is open source on GitHub (Apache-2.0).
Is verl-agent free or open source?
Yes, verl-agent is open source on GitHub (Apache-2.0).
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