🩺 Meet Ling-3.0-flash-Sante-fp8!
Healthcare-focused AI just got a little lighter. Same powerful reasoning, less memory to worry about. 🤖 https://modelscope.cn/models/inclusionAI/Ling-3.0-flash-Sante-fp8
- FP8 efficiency: 124B total parameters, just 5.1B active per token, with a smaller memory footprint for deployment.
- Quality holds up: Matches the BF16 model's 73.9 average across five healthcare benchmarks.
- 256K context: Built for long medical documents, evidence synthesis, and deep research.
- Beyond medical Q&A: Native reasoning, tool calling, and support for multi-agent research workflows.
- Ready to deploy: Supports SGLang and vLLM on compatible hardware.
🔬 For research use only, not clinical diagnosis or treatment.