What are the hardware requirements for NeuralQuant 9B GGUF?

NeuralQuant 9B GGUF requires approximately 3.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed NeuralQuant 9B GGUF and how large is it?

NeuralQuant 9B GGUF is developed by TheBloke, a model with 9b 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 NeuralQuant 9B GGUF?

NeuralQuant 9B GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

NeuralQuant 9B GGUF by TheBloke — VRAM 3.8GB

Name: NeuralQuant 9B GGUF
Author: TheBloke

NeuralQuant 9B GGUF is an open-source language model by TheBloke. Features: 9b LLM, VRAM: 3.8GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.1.

Base model:mlabonne/neuralquan... Base model:quantized:mlabonne/... Gguf Merge Mistral Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/TheBloke/NeuralQuant-9B-GGUF

NeuralQuant 9B GGUF Parameters and Internals

Model Type

mistral

Additional Notes

This model is a merge of the following models made with [mergekit](https://github.com/cg123/mergekit): [quantumaikr/quantum-v0.01](https://huggingface.co/quantumaikr/quantum-v0.01) and [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B).

Training Details

Data Sources:

quantumaikr/quantum-v0.01, mlabonne/NeuralHermes-2.5-Mistral-7B

LLM Name	NeuralQuant 9B GGUF
Repository 🤗	https://huggingface.co/TheBloke/NeuralQuant-9B-GGUF
Model Name	NeuralQuant 9B
Model Creator	Maxime Labonne
Base Model(s)	NeuralQuant 9B mlabonne/NeuralQuant-9B
Model Size	9b
Required VRAM	3.8 GB
Updated	2026-07-30
Maintainer	TheBloke
Model Type	mistral
Model Files	3.8 GB 4.7 GB 4.3 GB 3.9 GB 5.1 GB 5.4 GB 5.1 GB 6.2 GB 6.4 GB 6.2 GB 7.4 GB 9.6 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel
License	apache-2.0

Rank the NeuralQuant 9B GGUF 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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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/NeuralQuant-9B-GGUF.