Ring 2.6
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.
Learn more
LingFlow
LingFlow is a platform designed for the translation and formatting of various multilingual assets, including product imagery, marketing collateral, and technical manuals. The system follows a workflow that transitions from automated translation to an interface for manual editing and review.
Key features include the ability to process large batches of product images and the retention of original layouts within complex PDF documents. By automating the conversion and typesetting process, the platform handles high-volume material turnover, replacing the need for manual reconstruction of localized content.
Learn more
Ling 2.6 Flash
Ling 2.6 Flash is the latest cost-effective model in the Ling series, built on a Mixture of Experts architecture with 104B total parameters and 7.4B activated parameters. It is designed to achieve an optimal balance between inference performance and compute cost, making it suitable for general-purpose scenarios where strong reasoning capability, high throughput, and efficient deployment matter. 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. Ling 2.6 Flash provides a native 256K context window and can process approximately 200,000 characters of long-form input, with reliable long-range information retrieval whether key information appears at the beginning, middle, or end of the context. Its aggregate benchmark performance is comparable to or exceeds 40B-class Dense models.
Learn more
LingQ
The fast, fun and effective way to learn. Learn languages from content you love. Everyone learns to speak their native language. Why not use the same approach with a second language? Surround yourself with meaningful input that matters to you. Start at an easy level and work your way up. Immerse yourself in our vast library of language courses online and on mobile. You choose what to study. In addition to our huge course library you can import anything into LingQ and instantly turn it into an interactive lesson. Want to watch popular YouTube videos in your new language? Or, maybe the latest bestselling novel? What interests you? Books, articles, songs, podcasts even emails...you decide. You choose what to study. In addition to our huge course library you can import anything into LingQ and instantly turn it into an interactive lesson. Want to watch popular YouTube videos in your new language? Or, maybe the latest bestselling novel? What interests you? Books, articles, songs and more.
Learn more
