What are the hardware requirements for Llama 3 8B Instruct 64K AWQ?

Llama 3 8B Instruct 64K 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 Llama 3 8B Instruct 64K AWQ and how large is it?

Llama 3 8B Instruct 64K AWQ is developed by solidrust, a model with 8b 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 8B Instruct 64K AWQ?

Llama 3 8B Instruct 64K AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 3 8B Instruct 64K AWQ by solidrust — VRAM 5.8GB, 8K context

Name: Llama 3 8B Instruct 64K AWQ
Author: solidrust

Llama 3 8B Instruct 64K AWQ is an open-source language model by solidrust. Features: 8b LLM, VRAM: 5.8GB, Context: 8K, License: llama3, Quantized, Instruction-Based, LLM Explorer Score: 0.12.

Arxiv:2309.10400 4-bit 64k Autotrain compatible Awq Axolotl Base model:maziyarpanahi/llama... Base model:quantized:maziyarpa... Conversational Dataset:intel/orca dpo pairs Dpo En Endpoints compatible Facebook Finetuned Instruct Llama Llama-3 Meta Pose Pytorch Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/solidrust/Llama-3-8B-Instruct-64k-AWQ

Llama 3 8B Instruct 64K AWQ Parameters and Internals

Model Type

text generation

Additional Notes

AWQ offers faster Transformers-based inference with equivalent or better quality compared to GPTQ settings.

Training Details

Data Sources:

Intel/orca_dpo_pairs, RedPajama V1

Data Volume:

300M tokens

Methodology:

Continued pretraining with PoSE, rank stabilized LoRA of rank 256

Context Length:

64000

Model Architecture:

Rank stabilized LoRA with PoSE

Input Output

Accepted Modalities:

text

Output Format:

text

LLM Name	Llama 3 8B Instruct 64K AWQ
Repository 🤗	https://huggingface.co/solidrust/Llama-3-8B-Instruct-64k-AWQ
Model Name	Llama-3-8B-Instruct-64k
Model Creator	MaziyarPanahi
Base Model(s)	Llama 3 8B Instruct 64K MaziyarPanahi/Llama-3-8B-Instruct-64k
Model Size	8b
Required VRAM	5.8 GB
Updated	2026-07-18
Maintainer	solidrust
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	llama3
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 8B Instruct 64K 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 Llama 3 8B Instruct 64K AWQ

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...8B Instruct Gradient 1048K AWQ	1024K / 5.8 GB	8	0
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...ta Llama 3 8B Instruct 64K AWQ	64K / 5.8 GB	6	0
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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
Meta Llama 3 8B Instruct AWQ	8K / 5.8 GB	401	5

Note: green Score (e.g. "73.2") means that the model is better than solidrust/Llama-3-8B-Instruct-64k-AWQ.