verl-project/verl-omni

UniRL is a Framework for Unified Multimodal Model Reinforcement Learning

An Asynchronous Reinforcement Learning Engine for Omni-Modal Post-Training at Scale

EasyR1: An Efficient, Scalable, Multi-Modality RL Training Framework based on veRL

Agentic RL Training at Scale

VeOmni: Scaling Any Modality Model Training with Model-Centric Distributed Recipe Zoo

World model reinforcement learning for multi-turn VLM agents. RL for vision framework (NeurIPS 2025).

A framework for efficient model inference with omni-modality models

An Easy-to-use, Scalable and High-performance Agentic RL Framework based on Ray (PPO & DAPO & REINFORCE++ & VLM & TIS & vLLM & Ray & Async RL)

A unified framework for easy fine-tuning in Flow-Matching models