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NVIDIA releases Molt PyTorch agentic RL framework
NVIDIA’s NeMo team has released Molt, an Apache 2.0 licensed, PyTorch-native agentic reinforcement learning framework designed as a compact, roughly 8.6K-line codebase for researchers and AI coding assistants. Molt simplifies rapid algorithm iteration by keeping agents as plain Python programs, integrating Ray for placement, vLLM for rollouts, and NVIDIA AutoModel with FSDP2 for training, while maintaining token-exact trajectories and policy-version consistency. Although framed as research infrastructure rather than a production service, Molt targets labs with multi-node H100 or H200 access, supporting applications like tool-use agents, vision-language environments, LLM-as-judge reward loops, and large-scale on-policy distillation.
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