What are the hardware requirements for Gemma 3n E4B Bf16?

Gemma 3n E4B Bf16 requires approximately 15.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma 3n E4B Bf16 and how large is it?

Gemma 3n E4B Bf16 is developed by mlx-community, a model with 8.4b parameters. 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 Bf16?

Gemma 3n E4B Bf16 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 3n E4B Bf16 by mlx-community — VRAM 15.8GB

Name: Gemma 3n E4B Bf16
Author: mlx-community

Gemma 3n E4B Bf16 is an open-source language model by mlx-community. Features: 8.4b LLM, VRAM: 15.8GB, License: gemma.

Audio-text-to-text Automatic-speech-recognition Automatic-speech-translation Endpoints compatible Gemma3n Image-text-to-text Mlx Region:us Safetensors Sharded Tensorflow Video-text-to-text

Model Card on HF 🤗: https://huggingface.co/mlx-community/gemma-3n-E4B-bf16

Gemma 3n E4B Bf16 Parameters and Internals

LLM Name	Gemma 3n E4B Bf16
Repository 🤗	https://huggingface.co/mlx-community/gemma-3n-E4B-bf16
Model Size	8.4b
Required VRAM	15.8 GB
Updated	2026-08-08
Maintainer	mlx-community
Model Type	gemma3n
Model Files	5.4 GB: 1-of-4 3.6 GB: 2-of-4 5.4 GB: 3-of-4 1.4 GB: 4-of-4
Model Architecture	Gemma3nForConditionalGeneration
License	gemma
Transformers Version	4.53.2
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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