Ring-2.6-1T 正式开源,这是一个专为现实世界复杂任务构建的万亿规模旗舰思考模型。其设计目标超越单纯的“回答”,转向任务执行,能够理解上下文、规划步骤、调用工具,并在长任务链中保持稳定。模型重点支持高级智能体工作流,提供不同级别的推理努力配置:常规任务采用高级别,复杂推理则启用更高强度。通过 IcePop 算法实现了可扩展的异步强化学习,从而支撑了面向长周期智能体任务的稳定万亿规模训练。
🚀 Ring-2.6-1T is now open source.
A trillion-scale flagship thinking model built for real-world complex tasks: Agent workflows, coding & engineering, long-horizon tasks, complex reasoning, research, and enterprise automation.
It is designed to move beyond "answering" toward execution: understanding context, planning steps, calling tools, and staying stable across long task chains.
Highlights: - Advanced agentic workflow support. - Reasoning effort levels: high for agentic tasks, xhigh for complex reasoning. - Scalable asynchronous RL via the IcePop algorithm, enabling stable, trillion-scale training for long-horizon agentic RL.