What are the hardware requirements for Meta Llama 3 8B Instruct GPTQ?

Meta Llama 3 8B Instruct GPTQ requires approximately 5.7 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 Meta Llama 3 8B Instruct GPTQ and how large is it?

Meta Llama 3 8B Instruct GPTQ is developed by MaziyarPanahi, a model with 8b 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 Meta Llama 3 8B Instruct GPTQ?

Meta Llama 3 8B Instruct GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Meta Llama 3 8B Instruct GPTQ by MaziyarPanahi — VRAM 5.7GB, 8K context

Name: Meta Llama 3 8B Instruct GPTQ
Author: MaziyarPanahi

Meta Llama 3 8B Instruct GPTQ is an open-source language model by MaziyarPanahi. Features: 8b LLM, VRAM: 5.7GB, Context: 8K, Quantized, Instruction-Based, LLM Explorer Score: 0.14.

4-bit Autotrain compatible Base model:meta-llama/meta-lla... Base model:quantized:meta-llam... Conversational Deploy:azure En Endpoints compatible Facebook Finetuned Gptq Has space Instruct Llama Llama-3 Meta Pytorch Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/MaziyarPanahi/Meta-Llama-3-8B-Instruct-GPTQ

Meta Llama 3 8B Instruct GPTQ Parameters and Internals

Model Type

text-generation

Use Cases

Areas:

research, commercial applications

Additional Notes

Quantized version (GPTQ) of Meta-Llama-3-70B-Instruct, finetuned and optimized for 4-bit performance.

Supported Languages

en (proficient)

Input Output

Accepted Modalities:

text

Output Format:

generated text

LLM Name	Meta Llama 3 8B Instruct GPTQ
Repository 🤗	https://huggingface.co/MaziyarPanahi/Meta-Llama-3-8B-Instruct-GPTQ
Model Name	Meta-Llama-3-8B-Instruct-GPTQ
Model Creator	meta-llama
Base Model(s)	Meta Llama 3 8B Instruct meta-llama/Meta-Llama-3-8B-Instruct
Model Size	8b
Required VRAM	5.7 GB
Updated	2026-08-05
Maintainer	MaziyarPanahi
Model Type	llama
Instruction-Based	Yes
Model Files	5.7 GB
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	LlamaForCausalLM
Context Length	8192
Model Max Length	8192
Transformers Version	4.39.2
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	128256
Torch Data Type	float16

Rank the Meta Llama 3 8B Instruct GPTQ 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 Meta Llama 3 8B Instruct GPTQ

Best Alternatives	Context / RAM	Downloads	Likes
...a 3 8B Instruct 262K 4bit GPTQ	256K / 5.8 GB	5	1
... 8B Instruct 262K 4bit GPTQ 02	256K / 5.7 GB	6	0
...lama 3.1 8B Instruct GPTQ INT4	128K / 5.8 GB	9169	42
...Instruct 80K Qlora Merged GPTQ	80K / 5.8 GB	6	0
...oLeo Instruct 8B 32K V0.1 GPTQ	64K / 5.7 GB	5	0
Meta Llama 3 8B Instruct GPTQ	8K / 5.8 GB	6	0
...ta Llama 3 8B Instruct GPTQ 8B	8K / 9.2 GB	7	0
Meta Llama 3 8B Instruct GPTQ	8K / 5.8 GB	7	1
...truct Abliterated V3 GPTQ 4bit	8K / 5.8 GB	9	0
Meta Llama 3 8B Instruct GPTQ	8K / 5.7 GB	318	6

Note: green Score (e.g. "73.2") means that the model is better than MaziyarPanahi/Meta-Llama-3-8B-Instruct-GPTQ.