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

Meta Llama 3 8B Instruct GPTQ 8B requires approximately 9.2 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 8B and how large is it?

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

Meta Llama 3 8B Instruct GPTQ 8B 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 8B by cortecs — VRAM 9.2GB, 8K context

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

Meta Llama 3 8B Instruct GPTQ 8B is an open-source language model by cortecs. Features: 8b LLM, VRAM: 9.2GB, Context: 8K, License: other, Quantized, Instruction-Based, LLM Explorer Score: 0.14, Arc: 59.6, HellaSwag: 78.8, MMLU: 65.1, GSM8K: 57.3.

8-bit 8bit Autotrain compatible 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-8b

Meta Llama 3 8B Instruct GPTQ 8B Parameters and Internals

Model Type

text generation

Use Cases

Areas:

research, commercial applications

Additional Notes

The evaluations were conducted using the Eval Harness with a limit of 1000. Performance measurements were done on Cortecs Inference.

Supported Languages

English (high), French (high), German (high), Italian (high), Spanish (high)

Training Details

Data Sources:

Wikitext

Methodology:

Quantization using GPTQ

Input Output

Input Format:

JSON

Accepted Modalities:

text

Output Format:

text

LLM Name	Meta Llama 3 8B Instruct GPTQ 8B
Repository 🤗	https://huggingface.co/cortecs/Meta-Llama-3-8B-Instruct-GPTQ-8b
Base Model(s)	...eta Llama 3 8B Instruct FP8 KV neuralmagic/Meta-Llama-3-8B-Instruct-FP8-KV
Model Size	8b
Required VRAM	9.2 GB
Updated	2025-09-23
Maintainer	cortecs
Model Type	llama
Instruction-Based	Yes
Model Files	9.2 GB
GPTQ Quantization	Yes
Quantization Type	gptq\|8bit
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 8B 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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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	2895	7

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