Molt: A Scalable PyTorch-Native Training Framework for Agentic Reinforcement Learning

NVIDIA open-sources Molt, a PyTorch-native asynchronous RL training system built to stay small and readable enough for a single researcher to hold in their head, while matching the throughput of Megatron-based stacks. It supports multimodal and mixture-of-experts policies and enforces on-policy training by never training on a token the current policy did not generate. Uses Ray for placement/async queues, vLLM for rollout, and NVIDIA AutoModel + FSDP2 for training.