What are the hardware requirements for Gemma 3n E2B It?

Gemma 3n E2B It requires approximately 10.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma 3n E2B It and how large is it?

Gemma 3n E2B It is developed by unsloth, a model with 6b 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 E2B It?

Gemma 3n E2B It is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 3n E2B It by unsloth — VRAM 10.9GB

Name: Gemma 3n E2B It
Author: unsloth

Gemma 3n E2B It is an open-source language model by unsloth. Features: 6b LLM, VRAM: 10.9GB, License: gemma, LLM Explorer Score: 0.2.

Base model:finetune:google/gem... Base model:google/gemma-3n-e2b... Conversational En Endpoints compatible Gemma Gemma3 Gemma3n Google Image-text-to-text Region:us Safetensors Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/unsloth/gemma-3n-E2B-it

Gemma 3n E2B It Parameters and Internals

LLM Name	Gemma 3n E2B It
Repository 🤗	https://huggingface.co/unsloth/gemma-3n-E2B-it
Base Model(s)	Gemma 3n E2B It google/gemma-3n-E2B-it
Model Size	6b
Required VRAM	10.9 GB
Updated	2026-08-10
Maintainer	unsloth
Model Type	gemma3n
Model Files	3.1 GB: 1-of-3 5.0 GB: 2-of-3 2.8 GB: 3-of-3
Supported Languages	en
Model Architecture	Gemma3nForConditionalGeneration
License	gemma
Model Max Length	32768
Transformers Version	4.53.1
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Torch Data Type	bfloat16

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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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Gemma 3n E2B	0K / 10.9 GB	79	1
Gemma 3n E2B Bf16	0K / 10.8 GB	21	3