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Rapid42/gemma-4-E4B-it-MLX
gemma-4-E4B-it-MLX is a image-text-to-text model from Rapid42. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for mlx. The card lists the license as apache-2.0.
Gemma 4 (~8B, E4B variant) — MLX format for Apple Silicon, instruction-tuned
Downloads · 30 days
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From the Hugging Face model README
Gemma 4 (~8B, E4B variant) — MLX format for Apple Silicon, instruction-tuned
Converted and optimized by Rapid42 — engineering tools for fast pipelines.
This is Gemma 4 E4B (Google DeepMind's 4th generation Gemma, ~8B parameters in the E4B multimodal variant) converted to MLX format for native Apple Silicon inference. Instruction-tuned (-it) for chat and task-following.
Gemma 4 is Google's latest open model family — multimodal (text + image input), with strong performance on reasoning, coding, and multilingual tasks.
| Device | RAM | Experience |
|---|---|---|
| Any M-series Mac (16GB+) | ~8GB | ✅ Fast and smooth |
| M1 MacBook Air (8GB) | ~8GB | ⚠️ Tight — works but little headroom |
| M3 Max / Pro | ~8GB | ✅ Near-instant |
A practical choice for multimodal tasks on any Apple Silicon machine.
pip install mlx-lm
Text chat:
from mlx_lm import load, generate
model, tokenizer = load("Rapid42/gemma-4-E4B-it-MLX")
messages = [{"role": "user", "content": "What are the key advantages of MLX over PyTorch for Apple Silicon?"}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True, return_dict=False
)
response = generate(model, tokenizer, prompt=prompt, max_tokens=512, verbose=True)
print(response)
With image input (via MLX-VLM):
pip install mlx-vlm
python -m mlx_vlm.generate \
--model Rapid42/gemma-4-E4B-it-MLX \
--prompt "Describe what you see in this image." \
--image /path/to/image.jpg
Gemma 4 represents a significant step up from Gemma 2/3:
The E4B variant is the sweet spot: multimodal capability at 8B-class efficiency.
Apache 2.0. Full details: ai.google.dev/gemma/docs/gemma_4_license
Authors: Google DeepMind
Rapid42 builds fast, precise engineering tools — from VFX pipeline utilities to optimized ML model distributions.
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