AReaL System Requirements (CPU, RAM, Disk)

AReaL is a large-scale asynchronous reinforcement learning (RL) system built to bridge foundation model training with modern agent-based applications. Developed by researchers from Tsinghua IIIS and Ant Group, it is optimized for efficiency and scalability, making it ideal for training reasoning and agentic models. Its fully asynchronous RL training paradigm delivers industry-leading throughput, and its flexible design lets you plug in black-box agent applications by simply replacing the base_url.