What are the hardware requirements for Gemma 7B Instruct GPTQ 4bit?

Gemma 7B Instruct GPTQ 4bit requires approximately 5.6 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma 7B Instruct GPTQ 4bit and how large is it?

Gemma 7B Instruct GPTQ 4bit is developed by stan-hua, a model with 7b 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 7B Instruct GPTQ 4bit?

Gemma 7B Instruct GPTQ 4bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 7B Instruct GPTQ 4bit by stan-hua — VRAM 5.6GB, 8K context

Name: Gemma 7B Instruct GPTQ 4bit
Author: stan-hua

Gemma 7B Instruct GPTQ 4bit is an open-source language model by stan-hua. Features: 7b LLM, VRAM: 5.6GB, Context: 8K, Quantized, Instruction-Based, LLM Explorer Score: 0.12.

Arxiv:1910.09700 4-bit 4bit Conversational Endpoints compatible Gemma Gptq Instruct Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/stan-hua/Gemma-7B-Instruct-GPTQ-4bit

Gemma 7B Instruct GPTQ 4bit Parameters and Internals

LLM Name	Gemma 7B Instruct GPTQ 4bit
Repository 🤗	https://huggingface.co/stan-hua/Gemma-7B-Instruct-GPTQ-4bit
Model Size	7b
Required VRAM	5.6 GB
Updated	2026-08-02
Maintainer	stan-hua
Model Type	gemma
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-2 0.6 GB: 2-of-2
GPTQ Quantization	Yes
Quantization Type	gptq\|4bit
Model Architecture	GemmaForCausalLM
Context Length	8192
Model Max Length	8192
Transformers Version	4.41.1
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	float16

Rank the Gemma 7B Instruct GPTQ 4bit capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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 7B Instruct GPTQ 4bit

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...ruct Malayalam Model Vllm 4bit	16K / 5.6 GB	5	0
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Gemma Ko 7B Instruct V0.71	8K / 17 GB	3	1
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X Instruction 7B Ta	8K / 17.1 GB	6	0
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RoGemma 7B Instruct	8K / 17.1 GB	43	1
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Zephyr Gemma 7B Telugu	8K / 17.1 GB	13	3

Note: green Score (e.g. "73.2") means that the model is better than stan-hua/Gemma-7B-Instruct-GPTQ-4bit.