This repository contains an MLX-format 4-bit quantized version of microsoft/MediPhi-Instruct,
converted using mlx-lm for efficient on-device inference on Apple silicon.
This model is intended for iOS / iPadOS / macOS usage where memory and power
constraints require aggressive quantization while preserving clinical reasoning quality.
Model details
Base model: MediPhi-Instruct (Phi-3 family)
Parameters: ~3.8B
Quantization: 4-bit (MLX)
Format: MLX (not GGUF)
Intended use: On-device medical and clinical QA, decision support, and explanations
Language: English
⚠️ This is a conversion only. No additional fine-tuning was performed.
Why MLX 4-bit?
Compared to larger 4–7B medical models, MediPhi-Instruct shows:
Strong clinical reasoning per parameter
Better robustness under 4-bit quantization
Lower memory footprint suitable for mobile devices
This makes it a strong candidate for on-device medical assistants on iPhone and iPad.
