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.
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Ling Studio
Ling Studio is Ant Ling’s online environment for exploring the infinite possibilities of AI and testing the core capabilities of the Ling model family. It gives users a direct place to try Ant Ling models before building with them through API access, making it easier to experience multi-turn reasoning, long-context processing, multimodal generation, and model behavior in a practical chat workspace. It connects to Ant Ling’s high-performance model family for text, coding, reasoning, and multimodal tasks. Ling models are general-purpose LLMs built on Mixture of Experts architecture, balancing high parameter scale with low activation cost and supporting conversation, text generation, and content creation. Ring models specialize in deep reasoning and cognitive capabilities, with strong performance in math, programming, and comprehensive reasoning benchmarks.
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Ling 2.6
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.
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Infor Ming.le
Build a centralized space for team collaboration, business process improvement, and contextual analytics with Infor Ming.le®. Fully embedded within ERP, financials, and other organizational systems, this platform enables single-sign on for all Infor CloudSuite™ solutions. Ming.le also allows users to create personalized homepages that are tailored to their jobs. Infor Ming.le is the intelligent portal to your Infor application suite, establishing a common workflow and organizing conversations into enterprise-wide streams. Employees can share key screens, data, and attachments for reducing procedural processes. Allows users to create personalized homepages and streamline processes. Embeds collaboration within enterprise systems. Supports single sign-on across applications.
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