---
library_name: mlx
license: gemma
base_model: google/gemma-4-E2B-it
tags:
- mlx
- mlx-vlm
- gemma4
- text-generation
---

# gemma-4-e2b-it-4bit-textonly

A stripped-down MLX build of Google's Gemma 4 E2B (instruction-tuned), based on
[mlx-community/gemma-4-e2b-it-4bit](https://huggingface.co/mlx-community/gemma-4-e2b-it-4bit),
with the **vision tower and audio tower weights removed**.

Gemma 4 E2B is natively multimodal (text/image/audio), but the vision and audio
encoders together account for roughly a quarter of the checkpoint's size while
going largely unused in text-only chat deployments. This variant drops both,
shrinking the download from **3.55 GB to 2.5 GB (~30% smaller)** with no change
to the language model's weights or quantization — text generation quality is
identical to the source model.

Built for **[MLX Chat](https://mlxserve.com)**, an iOS app (not yet released)
that runs Gemma 4 fully on-device. Apple App Store review flagged the original
build's download size, and this app doesn't use image or audio input, so both
towers were removed rather than kept unused.

- Source: `mlx-community/gemma-4-e2b-it-4bit`
- Removed: all `vision_tower.*`, `embed_vision.*`, `audio_tower.*`, `embed_audio.*` tensors (1,415 of 2,511 total)
- Quantization: unchanged (4-bit affine, language backbone + embeddings, same as source)
- `config.json`: `audio_config` set to `null`; `vision_config` left in place structurally (some MLX loaders instantiate the vision module unconditionally) — load with `strict=False` if your loader errors on the missing vision weights

## What this model can't do

No image or audio input. Text-in, text-out only. If you need Gemma 4's
multimodal capabilities, use the upstream
[mlx-community/gemma-4-e2b-it-4bit](https://huggingface.co/mlx-community/gemma-4-e2b-it-4bit) instead.

## Usage

```bash
pip install mlx-vlm
python -m mlx_vlm generate \
  --model ddalcu/gemma-4-e2b-it-4bit-textonly \
  --prompt "Explain what a black hole is in two sentences." \
  --max-tokens 80
```

If your `mlx-vlm` version raises a shape error while loading, load with
`strict=False`:

```python
from mlx_vlm import load, generate
model, processor = load("ddalcu/gemma-4-e2b-it-4bit-textonly", strict=False)
```