MLX Community · First MLX build 26 Jun 2025
gemma-3n-E4B
MLX
TextVision gemma
A 8.4B parameter vision and text model, with 6 MLX builds, from 3-bit to 6-bit.
- Parameters
- 8.4B From Hugging Face
- Quantisation
- bf16 gemma-3n-E4B-bf16
- Memory needed
- 20 GB Estimate, unified memory
- Download
- 15.7 GB Weights, estimated
- Downloads
- 65 This build, last 30 days
- Task
- Vision and text Text, Vision
- MLX builds
- 6 On mlx-community
- Devices
- Mac Apple silicon
Memory
Will it fit?Needs about 20 GB at bf16
8 GB
16 GB
24 GB
32 GB
64 GB
128 GB
Fits with headroomTight, close other appsWon’t fit
Estimated from the size of the weights, plus a fifth for context and working memory and 2 GB for macOS and your apps. Long contexts need more.
Run it
Terminal · mlx-vlm$ pip install -U mlx-vlm
$ python -m mlx_vlm.generate --model mlx-community/gemma-3n-E4B-bf16 --image photo.jpg --prompt "Describe this image"MLX builds
6 on mlx-community| gemma-3n-E4B-3bit | 3-bit | 5.0 GB | 8 GB | 29 |
|---|---|---|---|---|
| gemma-3n-E4B-bf16 | bf16 | 15.7 GB | 20 GB | 65 |
| gemma-3n-E4B-4bit | 4-bit | — | — | 43 |
| gemma-3n-E4B-8bit | 8-bit | — | — | 33 |
| gemma-3n-E4B-5bit | 5-bit | — | — | 32 |
| gemma-3n-E4B-6bit | 6-bit | — | — | 32 |
Sizes are estimated from Hugging Face’s parameter counts and the quantisation. Downloads are for the last 30 days.