AReaL

AReaL is an open-source, fully asynchronous reinforcement learning training system designed for large reasoning and agentic models. It offers exceptional flexibility, industry-leading speed, and scalability from a single node to over 1,000 GPUs, achieving state-of-the-art performance.

AReaL is currently grouped under LLM Infra, which makes it easier to evaluate through workflow fit instead of isolated features alone. Based on the available data, it leans most heavily toward Fully Asynchronous RL Training: Enables stable, industry-leading speed for reinforcement learning. and Training Reasoning Agents: Developing AI agents capable of complex mathematical, coding, and general reasoning tasks.. It also shows measurable community traction with 5.6k GitHub stars.