What are the hardware requirements for Meta Llama 3 13B Instruct AWQ?

Meta Llama 3 13B Instruct AWQ requires approximately 8.8 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 13B Instruct AWQ and how large is it?

Meta Llama 3 13B Instruct AWQ is developed by solidrust, a model with 13b 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 13B Instruct AWQ?

Meta Llama 3 13B Instruct AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Meta Llama 3 13B Instruct AWQ by solidrust — VRAM 8.8GB, 8K context

Name: Meta Llama 3 13B Instruct AWQ
Author: solidrust

Meta Llama 3 13B Instruct AWQ is an open-source language model by solidrust. Features: 13b LLM, VRAM: 8.8GB, Context: 8K, Quantized, Instruction-Based, LLM Explorer Score: 0.12.

4-bit Autotrain compatible Awq Base model:andrijdavid/meta-ll... Base model:quantized:andrijdav... Conversational Endpoints compatible Instruct Llama Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/solidrust/Meta-Llama-3-13B-Instruct-AWQ

Meta Llama 3 13B Instruct AWQ Parameters and Internals

Model Type

text-generation

LLM Name	Meta Llama 3 13B Instruct AWQ
Repository 🤗	https://huggingface.co/solidrust/Meta-Llama-3-13B-Instruct-AWQ
Base Model(s)	Meta Llama 3 13B Instruct andrijdavid/Meta-Llama-3-13B-Instruct
Model Size	13b
Required VRAM	8.8 GB
Updated	2026-08-08
Maintainer	solidrust
Model Type	llama
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-2 3.8 GB: 2-of-2
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	LlamaForCausalLM
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 13B Instruct AWQ capabilities

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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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