MLX Community · First MLX build 11 Oct 2026
gemma-4-e2b-it-OptiQ-4bit
MLX
Text gemma Trending
A 4.6B parameter text classification model, with one MLX build at 4-bit.
- Parameters
- 4.6B From Hugging Face
- Quantisation
- 4-bit gemma-4-e2b-it-OptiQ-4bit-decision
- Memory needed
- 5 GB Estimate, unified memory
- Download
- 2.6 GB Weights, estimated
- Downloads
- 1.1K This build, last 30 days
- Task
- Text classification Text
- MLX builds
- 1 On mlx-community
- Devices
- Mac Apple silicon
Memory
Will it fit?Needs about 5 GB at 4-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 · Hugging Face CLI$ pip install -U huggingface_hub
$ hf download mlx-community/gemma-4-e2b-it-OptiQ-4bit-decisionMLX builds
1 on mlx-community| gemma-4-e2b-it-OptiQ-4bit-decision | 4-bit | 2.6 GB | 5 GB | 1.1K |
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Sizes are estimated from Hugging Face’s parameter counts and the quantisation. Downloads are for the last 30 days.