inclusionAI/Ling-3.0-flash-Sante · Hugging Face

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