What are the hardware requirements for Llama 3 16B Instruct V0.1 AWQ?

Llama 3 16B Instruct V0.1 AWQ requires approximately 10.3 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 Llama 3 16B Instruct V0.1 AWQ and how large is it?

Llama 3 16B Instruct V0.1 AWQ is developed by solidrust, a model with 16b 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 Llama 3 16B Instruct V0.1 AWQ?

Llama 3 16B Instruct V0.1 AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 3 16B Instruct V0.1 AWQ by solidrust — VRAM 10.3GB, 8K context

Name: Llama 3 16B Instruct V0.1 AWQ
Author: solidrust

Llama 3 16B Instruct V0.1 AWQ is an open-source language model by solidrust. Features: 16b LLM, VRAM: 10.3GB, Context: 8K, License: other, Quantized, Instruction-Based, LLM Explorer Score: 0.12.

4-bit Autotrain compatible Awq Base model:maziyarpanahi/llama... Base model:quantized:maziyarpa... Conversational En Endpoints compatible - mergeki... Instruct Llama Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/solidrust/Llama-3-16B-Instruct-v0.1-AWQ

Llama 3 16B Instruct V0.1 AWQ Parameters and Internals

Model Type

text-generation

Additional Notes

This model is a self-merge of `MaziyarPanahi/Llama-3-11B-Instruct-v0.1` model.

Supported Languages

en (N/A)

Input Output

Input Format:

<|begin_of_text|><|start_header_id|>system<|end_header_id|>

Accepted Modalities:

text

Output Format:

<|end_header_id|>

LLM Name	Llama 3 16B Instruct V0.1 AWQ
Repository 🤗	https://huggingface.co/solidrust/Llama-3-16B-Instruct-v0.1-AWQ
Model Name	Llama-3-16B-Instruct-v0.1
Model Creator	MaziyarPanahi
Base Model(s)	MaziyarPanahi/Llama-3-16B-Instruct-v0.1 MaziyarPanahi/Llama-3-16B-Instruct-v0.1
Model Size	16b
Required VRAM	10.3 GB
Updated	2026-07-12
Maintainer	solidrust
Model Type	llama
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-3 4.2 GB: 2-of-3 1.1 GB: 3-of-3
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	LlamaForCausalLM
License	other
Context Length	8192
Model Max Length	8192
Transformers Version	4.38.2
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	128256
Torch Data Type	float16

Rank the Llama 3 16B Instruct V0.1 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