Ant Ling

🚀 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.

As President Trump meets President Xi this week, a call to the American AI community: If your startup, lab, non-profit or company benefits from open international AI - especially Chinese (Deepseek, Qwen, Kimi, GLM,…), please share! Open source is the most important driver of competition, jobs and wealth creation in AI today. Let’s support and promote it at critical times like this week!

We are launching Ring-2.6-1T, a trillion-parameter flagship thinking model engineered for real-world complex tasks and production env: 🚀 - Adjustable Thinking Effort: dynamic compute mechanism to flexibly balance cognitive depth, token cost, and execution speed; - Agent-Optimized: Built for high-frequency workflows, delivering rapid multi-step execution and tool orchestration with SOTA stability; - Deep Thinking: Unlocks the model's maximum capability ceiling for rigorous mathematical logic and scientific research;

Back from a little family break! Lots has happened, and I’m planning to do a deeper dive into the most interesting architectural components (soon). Btw, are there any major architectures I missed below?