What are the hardware requirements for NeuralQuant 9B?

NeuralQuant 9B requires approximately 17.9 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed NeuralQuant 9B and how large is it?

NeuralQuant 9B is developed by mlabonne, 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?

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

NeuralQuant 9B by mlabonne — VRAM 17.9GB, 32K context

Name: NeuralQuant 9B
Author: mlabonne

NeuralQuant 9B is an open-source language model by mlabonne. Features: 9b LLM, VRAM: 17.9GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.11.

Endpoints compatible Merge Mistral Region:us Safetensors Sharded Tensorflow

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

NeuralQuant 9B Benchmarks

LLME Score: 0.1057

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

NeuralQuant 9B (mlabonne/NeuralQuant-9B)

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NeuralQuant 9B Parameters and Internals

Additional Notes

This model is a merge of '[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)'. Merge performed using [mergekit](https://github.com/cg123/mergekit).

LLM Name	NeuralQuant 9B
Repository 🤗	https://huggingface.co/mlabonne/NeuralQuant-9B
Model Size	9b
Required VRAM	17.9 GB
Updated	2026-07-09
Maintainer	mlabonne
Model Type	mistral
Model Files	9.9 GB: 1-of-2 8.0 GB: 2-of-2
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.35.2
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	bfloat16

Quantized Models of the NeuralQuant 9B

Model	Likes	Downloads	VRAM
NeuralQuant 9B GGUF	1	54	3 GB

Best Alternatives to NeuralQuant 9B

Best Alternatives	Context / RAM	Downloads	Likes
Peagle 9B	32K / 18 GB	12814	0
MetaMath Mistral Pro	32K / 17.9 GB	15	5
Peagle 9B	32K / 18 GB	8223	0
...onarch Neurotic 9B Passthrough	32K / 17.9 GB	96	0
Mistral 9B Instruct	32K / 35.9 GB	7	0
GML Mistral Merged V1	32K / 18 GB	101	1
Garbage 9B	32K / 17.9 GB	100	3
Bepis 9B	32K / 18 GB	74	6
Mistral 9B Instruct V0.2	32K / 17.9 GB	102	3
Notus TheTop 7B Passthrough	32K / 18 GB	5	0

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

Rank the NeuralQuant 9B Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Release v20260328a

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NeuralQuant 9B by mlabonne