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

Meta Llama 3 8B Instruct AWQ requires approximately 5.8 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 AWQ and how large is it?

Meta Llama 3 8B Instruct AWQ is developed by TechxGenus, 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 AWQ perform on standard benchmarks?

Meta Llama 3 8B Instruct AWQ has the following published scores: MMLU 64.8. Compare against reference models on this page or on the LLM Explorer leaderboards.

Meta Llama 3 8B Instruct AWQ by TechxGenus — VRAM 5.8GB, 8K context

Name: Meta Llama 3 8B Instruct AWQ
Author: TechxGenus

Meta Llama 3 8B Instruct AWQ is an open-source language model by TechxGenus. Features: 8b LLM, VRAM: 5.8GB, Context: 8K, License: other, Quantized, Instruction-Based, LLM Explorer Score: 0.14, Arc: 59.9, HellaSwag: 80, MMLU: 64.8, GSM8K: 65.7.

4-bit Awq Conversational Deploy:azure En Endpoints compatible Facebook Instruct Llama Llama-3 Meta Pytorch Quantized Region:us Safetensors Sharded Tensorflow

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

Meta Llama 3 8B Instruct AWQ Parameters and Internals

Model Type

text generation

Use Cases

Areas:

commercial, research

Applications:

text generation, assistant-like chat

Primary Use Cases:

instruction-tuned models are for assistant-like chat., pretrained models for natural language generation tasks.

Limitations:

Not for use violating laws or outside Acceptable Use Policy., Primarily English language.

Considerations:

Compliance with Llama 3 Community License and Acceptable Use Policy is required.

Additional Notes

Model was pre-trained with data up until March 2023 for 8B and December 2023 for 70B models. Carbon footprint for training was fully offset.

Supported Languages

en (High)

Training Details

Data Sources:

publicly available online data

Data Volume:

15 trillion tokens

Methodology:

Supervised fine-tuning (SFT) with Reinforcement Learning with Human Feedback (RLHF)

Context Length:

8000

Hardware Used:

H100-80GB GPUs

Model Architecture:

Auto-regressive language model using optimized transformer architecture

Safety Evaluation

Ethical Considerations:

Model outputs are provided 'as is' and developers should conduct safety testing.

Responsible Ai Considerations

Fairness:

Model aims to be accessible without unnecessary judgment or bias.

Accountability:

Meta and developers share accountability.

Mitigation Strategies:

Includes safety tools like Llama Guard and Purple Llama for input-output filtering.

Input Output

Input Format:

text input

Accepted Modalities:

text

Output Format:

text and code output

Release Notes

Date:

April 18, 2024

Notes:

Initial release of Meta Llama 3, available in 8B and 70B sizes.

LLM Name	Meta Llama 3 8B Instruct AWQ
Repository 🤗	https://huggingface.co/TechxGenus/Meta-Llama-3-8B-Instruct-AWQ
Base Model(s)	Meta Llama 3 13B Instruct andrijdavid/Meta-Llama-3-13B-Instruct
Model Size	8b
Required VRAM	5.8 GB
Updated	2026-07-16
Maintainer	TechxGenus
Model Type	llama
Instruction-Based	Yes
Model Files	4.7 GB: 1-of-2 1.1 GB: 2-of-2
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	LlamaForCausalLM
License	other
Context Length	8192
Model Max Length	8192
Transformers Version	4.40.0
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	128256
Torch Data Type	float16

Rank the Meta Llama 3 8B Instruct AWQ 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 AWQ

Best Alternatives	Context / RAM	Downloads	Likes
...8B Instruct Gradient 1048K AWQ	1024K / 5.8 GB	8	0
...radient 1048K AWQ 4bit Smashed	1024K / 5.8 GB	7	1
...Instruct 262K AWQ 4bit Smashed	256K / 5.8 GB	5	4
...ta Llama 3 8B Instruct 64K AWQ	64K / 5.8 GB	6	0
... Instruct 8B 32K V0.1 4bit AWQ	64K / 5.8 GB	9	0
Llama 3 8B Instruct AWQ	8K / 5.8 GB	25458	31
Meta Llama 3 8B Instruct AWQ	8K / 5.8 GB	6	0
Meta Llama 3 8B Instruct AWQ	8K / 5.8 GB	563	0
Meta Llama 3 8B Instruct AWQ	8K / 5.8 GB	7	0
...eta Llama 3 8B Instruct Hf AWQ	8K / 5.8 GB	179	9

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