🧩 Model Card: medgemma:4b

• Type: Image-Text-to-Text
• Think: No
• Tool Calling Support: No
• Base Model: google/medgemma-4b-it
• Quantization: Q4_1
• Max Context Length: 128k tokens
• Default Context Length: 64k tokens (change default)
• Set Context Length at Launch

▶️ Run with FastFlowLM in PowerShell:

flm run medgemma:4b

🧩 Model Card: medgemma1.5:4b

• Type: Image-Text-to-Text
• Think: No
• Tool Calling Support: No
• Base Model: google/medgemma1.5-4b-it
• Quantization: Q4_1
• Max Context Length: 128k tokens
• Default Context Length: 64k tokens (change default)
• Set Context Length at Launch

▶️ Run with FastFlowLM in PowerShell:

flm run medgemma1.5:4b

📺 Demo Video

• MedGemma:4B (Multimodal) on AMD Ryzen™ AI NPU — Demo Video
• Prompts & images in the demo are from the official paper (pp.12–13)
• Model page

⚠️ Disclaimer

This tool (MedGemma + FastFlowLM) is not a diagnostic or clinical tool. Always consult a licensed medical professional for healthcare decisions.

🔐 Why They Matter

• Privacy First — There is nothing more personal than your health!
• Powered by NPU — Leverages AMD Ryzen™ AI NPU for fast, low-power inference.
• Healthcare Applications — A concrete example of how local LLMs + NPUs enable privacy-preserving, research-driven healthcare workflows.