Skip to content

medgemma-27b-it-bf16

mlx-community/medgemma-27b-it-bf16
Vision + text · transformers
bf16 Open on Hugging Face
Parameters
—
Weights (est.)
—
Mac memory (est.)
—

Size is estimated from the parameter count and quantisation. Memory allows a fifth extra for context plus 2 GB for the system; long contexts need more.

Run it

With mlx-vlm on an Apple silicon Mac:

pip install mlx-vlmpython -m mlx_vlm.generate --model mlx-community/medgemma-27b-it-bf16 --image photo.jpg --prompt "Describe this image"

Details

Base model
google/gemma-3-27b-pt (finetune)
Vendor
Google · Gemma
Task
Vision + text
Quantisation
bf16
Licence
health-ai-developer-foundations
Downloads
76 in the last 30 days · 2.6K all time · 3 likes
Published
2025-07-10 · updated 2025-07-10 (1y ago)
Languages
en
Tags
gemma3, medical, x-ray, pathology, dermatology, fundus, radiology report generation, chest-x-ray, medical-embeddings, image-classification, zero-shot-image-classification, image-feature-extraction

Other MLX builds of google/gemma-3-27b-pt

Build Quantisation Weights Mac memory Downloads
gemma-3-27b-it-4bit 4-bit — — 1.1K
medgemma-27b-it-8bit 8-bit — — 301
medgemma-27b-it-4bit 4-bit — — 155
gemma-3-27b-it-8bit 8-bit — — 110
medgemma-27b-it-bf16 (this one) bf16 — — 76
gemma-3-27b-it-bf16 bf16 — — 66
medgemma-27b-it-6bit 6-bit — — 57
gemma-3-27b-it-6bit 6-bit — — 45