OpenMed - Clinical AI that never leaves the device
4.0OpenMed 1.5.5 runs clinical AI on-device for privacy. Supports PII MLX, PyTorch/MLX, Faker, 1000+ LLMs, Swift, and OpenMedKit. Apache-2.0.
About
OpenMed is an open-source platform dedicated to bringing true offline intelligence to the healthcare sector. The latest version, 1.5.5, further strengthens privacy protection and multilingual support, ensuring that all clinical AI inference runs entirely on-device and that data never leaves the user’s terminal. Built on the Apache-2.0 license with a fully open stack, OpenMed covers the complete pipeline from model training to local deployment, offering healthcare institutions, researchers, and developers a secure, transparent, and customizable medical AI solution.
Key Features
Pricing & Fees
- **Data Sovereignty Guaranteed: ** All computation happens locally on the device with no cloud uploads, fundamentally eliminating data breach risks and meeting strict compliance requirements like HIPAA and GDPR.
- **Fully Open and Transparent: ** From model weights to application-layer code, everything is publicly available, allowing developers to audit, modify, and optimize every line of code while avoiding vendor lock-in.
- **Multilingual and Global-Ready: ** A pioneer in privacy protection for non-English languages, particularly suited to healthcare scenarios in the Middle East, East Asia, and Southern Europe.
- **Lightweight and Efficient Deployment: ** Leverages the MLX optimization framework to achieve near-real-time inference on Apple Silicon devices while remaining compatible with the broader PyTorch ecosystem.
Who It's For
OpenMed is designed for healthcare institutions and IT teams looking to build localized, compliant clinical decision-support systems while minimizing data-exfiltration risks. It also serves medical AI researchers who want to fine-tune models on real de-identified data or run comparative experiments using the 1,000+ open-source LLMs. Mobile health app developers can use OpenMedKit to quickly integrate offline medical record analysis and symptom checking into iOS apps, and privacy compliance officers will find it a valuable, auditable, and verifiable anonymization solution for protecting patient data.