NVIDIA's Molt Framework Enhances Agentic Reinforcement Learning
NVIDIA has introduced Molt, a PyTorch-native framework designed for agentic reinforcement learning (RL). Molt focuses on agentic-first research, offering a streamlined stack that includes Ray for placement, vLLM for rollout, and NVIDIA AutoModel for training. The framework supports large-scale models and aims to optimize research velocity by providing a minimal yet powerful RL environment. Molt is designed to be hackable, allowing researchers to modify and extend its capabilities easily. It supports various RL algorithms and offers tools for on-policy distillation and MoE routing stability. 
