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 cortecs, a model with 8b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Meta Llama 3 8B Instruct GPTQ perform on standard benchmarks?

Meta Llama 3 8B Instruct GPTQ has the following published scores: MMLU 65.06. Compare against reference models on this page or on the LLM Explorer leaderboards.

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

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

Meta Llama 3 8B Instruct GPTQ is an open-source language model by cortecs. Features: 8b LLM, VRAM: 5.7GB, Context: 8K, License: other, Quantized, Instruction-Based, LLM Explorer Score: 0.14, Arc: 59.6, HellaSwag: 78.8, MMLU: 65.1, GSM8K: 57.3.

4-bit 4bit Conversational Dataset:wikitext Endpoints compatible Gptq Instruct Llama Quantized Region:us

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

Meta Llama 3 8B Instruct GPTQ Parameters and Internals

Model Type

text generation

Additional Notes

Quantized model using GPTQ with 4bit, Act order: True, Group size: 128.

Supported Languages

English (High), French (Intermediate), German (Intermediate), Italian (Intermediate), Spanish (Intermediate)

Safety Evaluation

Ethical Considerations:

We did not check for data contamination.

Input Output

Accepted Modalities:

text

LLM Name	Meta Llama 3 8B Instruct GPTQ
Repository 🤗	https://huggingface.co/cortecs/Meta-Llama-3-8B-Instruct-GPTQ
Base Model(s)	...eta Llama 3 8B Instruct FP8 KV neuralmagic/Meta-Llama-3-8B-Instruct-FP8-KV
Model Size	8b
Required VRAM	5.7 GB
Updated	2026-08-01
Maintainer	cortecs
Model Type	llama
Instruction-Based	Yes
Model Files	5.7 GB
GPTQ Quantization	Yes
Quantization Type	gptq\|4bit
Model Architecture	LlamaForCausalLM
License	other
Context Length	8192
Model Max Length	8192
Transformers Version	4.40.1
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

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...a 3 8B Instruct 262K 4bit GPTQ	256K / 5.8 GB	5	1
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...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
Meta Llama 3 8B Instruct GPTQ	8K / 5.7 GB	2895	7

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