What are the hardware requirements for NeuralMonarch 7B GPTQ?

NeuralMonarch 7B GPTQ requires approximately 4.6 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 NeuralMonarch 7B GPTQ and how large is it?

NeuralMonarch 7B GPTQ is developed by LoneStriker, a model with 7b 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 NeuralMonarch 7B GPTQ?

NeuralMonarch 7B GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

NeuralMonarch 7B GPTQ by LoneStriker — VRAM 4.6GB, 32K context

Name: NeuralMonarch 7B GPTQ
Author: LoneStriker

NeuralMonarch 7B GPTQ is an open-source language model by LoneStriker. Features: 7b LLM, VRAM: 4.6GB, Context: 32K, License: cc-by-nc-4.0, Quantized, LLM Explorer Score: 0.11.

4-bit Base model:mlabonne/monarch-7b Base model:quantized:mlabonne/... Conversational Dpo En Endpoints compatible Gptq Lazymergekit Merge Mistral Quantized Region:us Rlhf Safetensors

Model Card on HF 🤗: https://huggingface.co/LoneStriker/NeuralMonarch-7B-GPTQ

NeuralMonarch 7B GPTQ Parameters and Internals

Model Type

DPO, text generation

Use Cases

Areas:

research, commercial

Primary Use Cases:

instruction following, reasoning tasks

Considerations:

I recommend using it with the Mistral Instruct chat template.

Supported Languages

language (en)

Training Details

Data Sources:

mlabonne/truthy-dpo-v0.1, mlabonne/distilabel-intel-orca-dpo-pairs

Context Length:

8000

LLM Name	NeuralMonarch 7B GPTQ
Repository 🤗	https://huggingface.co/LoneStriker/NeuralMonarch-7B-GPTQ
Base Model(s)	Monarch 7B mlabonne/Monarch-7B
Model Size	7b
Required VRAM	4.6 GB
Updated	2026-05-25
Maintainer	LoneStriker
Model Type	mistral
Model Files	4.6 GB
Supported Languages	en
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	MistralForCausalLM
License	cc-by-nc-4.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.37.2
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	float16

Rank the NeuralMonarch 7B GPTQ 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 NeuralMonarch 7B GPTQ

Best Alternatives	Context / RAM	Downloads	Likes
...enHermes 2.5 Mistral 7B Marlin	32K / 4.1 GB	6	2
Zephyr 7B Beta Marlin	32K / 4.1 GB	16	0
Mistral 7B Instruct V0.3 GPTQ	32K / 4.2 GB	113881	1
...ral 7B Instruct V0.3 GPTQ 4bit	32K / 4.2 GB	2946	18
...ral 7B Instruct V0.3 GPTQ 4bit	32K / 4.2 GB	2658	25
...istral 7B Pruned50 GPTQ Marlin	32K / 4 GB	5	0
Mistral 7B Instruct V0.2 GPTQ	32K / 4.2 GB	6743	56
Mistral 7B Unsloth Gptq 8bit	32K / 7.7 GB	7	0
Cosmosage V2	32K / 4.2 GB	8	4
...phyr 7B Beta Assistant V1 Gptq	32K / 4.2 GB	2	1

Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/NeuralMonarch-7B-GPTQ.