Verl Rl Training

verl: Volcano Engine Reinforcement Learning for LLMs

verl is a flexible, efficient, and production-ready RL training library for large language models from ByteDance's Seed team. It implements the HybridFlow framework (EuroSys 2025) and powers models like Doubao-1.5-pro achieving O1-level performance on math benchmarks.

When to Use verl

Choose verl when you need:

• Production-ready RL training at scale (tested up to 671B parameters)
• Flexibility to swap backends (FSDP ↔ Megatron-LM ↔ vLLM ↔ SGLang)
• Support for multiple RL algorithms (PPO, GRPO, RLOO, REINFORCE++, DAPO)
• Multi-turn rollout with tool calling for agentic workflows
• Vision-language model RL training

Consider alternatives when:

• You need Megatron-native training → use slime or miles
• You want PyTorch-native abstractions with Monarch → use torchforge
• You only need simple SFT/DPO → use TRL or Axolotl

Key Features