Ling Studio

Ring is a trillion-parameter thinking model from Ant Group, designed for real-world Agent workflows. It uses the same Mixture of Experts architecture as Ling, activating about 63B parameters per inference, and focuses on coding agents, tool use, multi-tool collaboration, engineering development, research analysis, and long-horizon task execution. Rather than only pursuing “smarter” results, Ring is built to consistently complete complex tasks at reasonable cost, balancing quality, speed, and execution efficiency in production environments. Ring-2.6-1T introduces an adjustable Reasoning Effort mechanism with high and xhigh reasoning intensity levels, using adaptive reasoning budget allocation based on task complexity. High mode is designed for high-frequency Agent workflows, lower token cost, faster multi-step execution, multi-turn interaction, tool collaboration, and task decomposition.

Ling 2.6 is a general-purpose large language model series independently developed and open-sourced by Ant Group, built on a Mixture of Experts architecture and designed for inference efficiency, long context modeling, training technology, and AI Agent collaborative reasoning. Ling’s MoE architecture routes each token to activate only the most relevant expert subnetworks, compressing actual computation to a minimal fraction while maintaining large-scale model capacity. The Ling 2.6 series further advances long-sequence modeling, with Ling-2.6-1T supporting up to a 1M native context window and the official API exposing a 256K context window, while Ling-2.6-flash provides a native 256K context window capable of processing approximately 200,000 characters of long-form input. The models are designed for reliable long-range information retrieval, with no noticeable degradation whether information appears at the beginning, middle, or end of the context.