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NVIDIA NeMo RL supports FP8 low-precision reinforcement learning post-training to accelerate agent iteration.

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ME News: April 23 (UTC+8), NVIDIA AI recently announced that its open-source library NVIDIA NeMo RL has added a new capability, supporting reinforcement learning (RL) post-training using the low-precision FP8 format to accelerate related compute workloads. According to the released information, on the Qwen3-8B-Base model, using the FP8 format can increase the speed of RL workloads by 1.48x. This acceleration is aimed at achieving faster iteration cycles for agent tool usage and multi-step tasks. (Source: InFoQ)
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