What are the hardware requirements for Gemma 4 E4B It Qat 6bit?

Gemma 4 E4B It Qat 6bit requires approximately 7.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma 4 E4B It Qat 6bit and how large is it?

Gemma 4 E4B It Qat 6bit is developed by mlx-community, a model with 2.3b 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 4 E4B It Qat 6bit?

Gemma 4 E4B It Qat 6bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 4 E4B It Qat 6bit by mlx-community — VRAM 7.9GB

Name: Gemma 4 E4B It Qat 6bit
Author: mlx-community

Gemma 4 E4B It Qat 6bit is an open-source language model by mlx-community. Features: 2.3b LLM, VRAM: 7.9GB, Quantized, LLM Explorer Score: 0.25.

6-bit 6bit Conversational En Gemma4 Image-text-to-text Mlx Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mlx-community/gemma-4-E4B-it-qat-6bit

Gemma 4 E4B It Qat 6bit Parameters and Internals

LLM Name	Gemma 4 E4B It Qat 6bit
Repository 🤗	https://huggingface.co/mlx-community/gemma-4-E4B-it-qat-6bit
Model Size	2.3b
Required VRAM	7.9 GB
Updated	2026-08-08
Maintainer	mlx-community
Model Type	gemma4
Model Files	4.6 GB: 1-of-2 3.3 GB: 2-of-2
Supported Languages	en
Quantization Type	6bit
Model Architecture	Gemma4ForConditionalGeneration
Transformers Version	5.6.2
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>

Rank the Gemma 4 E4B It Qat 6bit capabilities

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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

Best Alternatives to Gemma 4 E4B It Qat 6bit

Best Alternatives	Context / RAM	Downloads	Likes
Gemma 4 E4b It Nvfp4	0K / 5.2 GB	634	7

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/gemma-4-E4B-it-qat-6bit.