NVIDIA Unveils NeMo-RL, an Open-Source Reinforcement Learning Library with GRPO Integration

NVIDIA has launched NeMo-RL, a new open-source library designed to advance reinforcement learning (RL) capabilities. The library supports scalable training, from single-GPU prototypes to large-scale deployments across thousands of GPUs, and integrates seamlessly with Hugging Face models.

Built within the Nvidia NeMo Framework, NeMo-RL features optimized training and inference processes, along with support for RL algorithms like GRPO and DPO. Its architecture ensures flexibility, allowing high-level algorithm implementations to remain backend-agnostic. This enables effortless scaling without modifying algorithm code, catering to both small and large-scale projects.

The library employs Ray-based orchestration for efficiency and includes native Hugging Face compatibility, positioning it as a versatile tool for AI researchers and developers.