from inclusionAI: Introduction Ling-3.0-flash-Sante is our healthcare-specialized model built on Ling-3.0-flash. Its name comes from the French word santé, meaning “health.” With 124B total parameters and 5.1B active parameters per token, Sante is designed for medical reasoning, healthcare research, deep research, and tool-assisted workflows while retaining the general capabilities of Ling-3.0-flash. Model weights are available on Hugging Face and ModelScope. Important: Ling-3.0-flash-Sante is a research model, not a medical device. Its outputs may be incomplete or incorrect and must not be used as a substitute for professional medical advice, diagnosis, or treatment. High-stakes use requires qualified human review, independent verification, and compliance with applicable privacy, security, and healthcare regulations. Highlights Strong healthcare capabilities: Sante performs well across professional healthcare tasks, complex medical reasoning, medical knowledge, and healthcare safety benchmarks. Efficient at scale: Its hybrid-linear MoE architecture combines Kimi Delta Attention (KDA), gated MLA, and sparse MoE layers, activating 5.1B of 124B parameters per token. Built for long contexts: Training extends to 256K tokens, supporting long-document analysis, evidence synthesis, and multi-step research. Beyond medical QA: Sante is designed for deep research, tool-assisted workflows, and multi-agent collaboration as well as question answering. Native reasoning and tool use: Thinking mode is enabled by default, with tool calling supported through compatible serving frameworks.Introduction   submitted by   /u/jacek2023 [link]   [comments]