What are the hardware requirements for Llama 3 Neural Chat V1 8B AWQ?

Llama 3 Neural Chat V1 8B 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 Neural Chat V1 8B AWQ and how large is it?

Llama 3 Neural Chat V1 8B 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 Neural Chat V1 8B AWQ?

Llama 3 Neural Chat V1 8B AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 3 Neural Chat V1 8B AWQ by solidrust — VRAM 5.8GB, 8K context

Name: Llama 3 Neural Chat V1 8B AWQ
Author: solidrust

Llama 3 Neural Chat V1 8B AWQ is an open-source language model by solidrust. Features: 8b LLM, VRAM: 5.8GB, Context: 8K, License: other, Quantized, Instruction-Based, LLM Explorer Score: 0.12.

4-bit Autotrain compatible Awq Base model:locutusque/llama-3-... Base model:quantized:locutusqu... Conversational Dataset:jondurbin/airoboros-3.... Dataset:m-a-p/code-feedback Dataset:maziyarpanahi/wizardlm... Dataset:microsoft/orca-math-wo... Dataset:mlabonne/orpo-dpo-mix-... Dataset:open-orca/slimorca-ded... Endpoints compatible Instruct Llama Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/solidrust/llama-3-neural-chat-v1-8b-AWQ

Llama 3 Neural Chat V1 8B AWQ Parameters and Internals

Model Type

text-generation

Additional Notes

The model is quantized by Suparious, making it compatible with 4-bit inference and various pipelines like autotrain and endpoints.

Training Details

Data Sources:

Open-Orca/SlimOrca-Dedup, jondurbin/airoboros-3.2, microsoft/orca-math-word-problems-200k, m-a-p/Code-Feedback, MaziyarPanahi/WizardLM_evol_instruct_V2_196k, mlabonne/orpo-dpo-mix-40k

Methodology:

Fine-tuned using SFT and DPO methods, adapted for coding and math skills.

LLM Name	Llama 3 Neural Chat V1 8B AWQ
Repository 🤗	https://huggingface.co/solidrust/llama-3-neural-chat-v1-8b-AWQ
Base Model(s)	Llama 3 Neural Chat V1 8B Locutusque/llama-3-neural-chat-v1-8b
Model Size	8b
Required VRAM	5.8 GB
Updated	2026-05-10
Maintainer	solidrust
Model Type	llama
Instruction-Based	Yes
Model Files	4.7 GB: 1-of-2 1.1 GB: 2-of-2
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
Padding Token	<\|end_of_text\|>
Vocabulary Size	128256
Torch Data Type	float16

Rank the Llama 3 Neural Chat V1 8B 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

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Note: green Score (e.g. "73.2") means that the model is better than solidrust/llama-3-neural-chat-v1-8b-AWQ.