MLX Community · First MLX build 29 Jul 2026
gemma-4-E2B-it-qat-mobile
MLX
TextVision
A 2.3B parameter vision and text model, with one MLX build at 8-bit.
- Parameters
- 2.3B From Hugging Face
- Quantisation
- 8-bit gemma-4-E2B-it-qat-mobile
- Memory needed
- 5 GB Estimate, unified memory
- Download
- 2.5 GB Weights, estimated
- Downloads
- 17K This build, last 30 days
- Task
- Vision and text Text, Vision
- MLX builds
- 1 On mlx-community
- Devices
- Mac Apple silicon
Memory
Will it fit?Needs about 5 GB at 8-bit
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-4-E2B-it-qat-mobile --image photo.jpg --prompt "Describe this image"MLX builds
1 on mlx-community| gemma-4-E2B-it-qat-mobile | 8-bit | 2.5 GB | 5 GB | 17K |
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Sizes are estimated from Hugging Face’s parameter counts and the quantisation. Downloads are for the last 30 days.