What are the hardware requirements for Gemma 3n E4B It 4bit?

Gemma 3n E4B It 4bit requires approximately 5.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma 3n E4B It 4bit and how large is it?

Gemma 3n E4B It 4bit is developed by mlx-community. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Gemma 3n E4B It 4bit?

Gemma 3n E4B It 4bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 3n E4B It 4bit by mlx-community — VRAM 5.9GB

Name: Gemma 3n E4B It 4bit
Author: mlx-community

Gemma 3n E4B It 4bit is an open-source language model by mlx-community. Features: LLM, VRAM: 5.9GB, License: gemma, Quantized.

4-bit 4bit Audio-text-to-text Automatic-speech-recognition Automatic-speech-translation Base model:google/gemma-3n-e4b Base model:quantized:google/ge... Conversational Endpoints compatible Gemma3n Image-text-to-text Mlx Quantized Region:us Safetensors Sharded Tensorflow Video-text-to-text

Model Card on HF 🤗: https://huggingface.co/mlx-community/gemma-3n-E4B-it-4bit

Gemma 3n E4B It 4bit Parameters and Internals

LLM Name	Gemma 3n E4B It 4bit
Repository 🤗	https://huggingface.co/mlx-community/gemma-3n-E4B-it-4bit
Base Model(s)	google/gemma-3n-E4B google/gemma-3n-E4B
Required VRAM	5.9 GB
Updated	2026-08-08
Maintainer	mlx-community
Model Type	gemma3n
Model Files	5.4 GB: 1-of-2 0.5 GB: 2-of-2
Quantization Type	4bit
Model Architecture	Gemma3nForConditionalGeneration
License	gemma
Transformers Version	4.54.0.dev0
Padding Token	<pad>

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

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