What are the hardware requirements for NeuralMonarch 7B?

NeuralMonarch 7B requires approximately 14.4 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 and how large is it?

NeuralMonarch 7B is developed by mlabonne, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does NeuralMonarch 7B perform on standard benchmarks?

NeuralMonarch 7B has the following published scores: MMLU 64.41. Compare against reference models on this page or on the LLM Explorer leaderboards.

NeuralMonarch 7B by mlabonne — VRAM 14.4GB, 32K context

Name: NeuralMonarch 7B
Author: mlabonne

NeuralMonarch 7B is an open-source language model by mlabonne. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: cc-by-nc-4.0, LLM Explorer Score: 0.16, Arc: 73.2, HellaSwag: 89.1, MMLU: 64.4, GSM8K: 67.8.

Base model:finetune:mlabonne/m... Base model:mlabonne/monarch-7b Conversational Deploy:azure Dpo En Endpoints compatible Lazymergekit Merge Mistral Model-index Region:us Rlhf Safetensors Sharded Tensorflow

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

NeuralMonarch 7B Parameters and Internals

Model Type

text generation

Use Cases

Areas:

instruction following, reasoning tasks

Applications:

chat/RP models with strong reasoning abilities

Additional Notes

Special thanks to contributors Jon Durbin, Intel, and Argilla for the preference datasets. See the demo at Hugging Face Spaces.

Training Details

Data Sources:

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

Methodology:

DPO fine-tuning using preference datasets and LazyMergekit.

Context Length:

8000

Input Output

Performance Tips:

Use with the Mistral Instruct chat template for optimal performance.

LLM Name	NeuralMonarch 7B
Repository 🤗	https://huggingface.co/mlabonne/NeuralMonarch-7B
Base Model(s)	Monarch 7B mlabonne/Monarch-7B
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-08-08
Maintainer	mlabonne
Model Type	mistral
Model Files	4.9 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3
Supported Languages	en
Model Architecture	MistralForCausalLM
License	cc-by-nc-4.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.0.dev0
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	float16

Rank the NeuralMonarch 7B 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

Quantized Models of the NeuralMonarch 7B

Model	Likes	Downloads	VRAM
AlphaMonarch 7B 2bit HQQ	7	4	2 GB
AlphaMonarch 7B AWQ	1	6	4 GB
AlphaMonarch 7B GPTQ	3	6	4 GB
AlphaMonarch 7B AWQ	2	1	4 GB

Best Alternatives to NeuralMonarch 7B

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	8470	54
SpydazWeb AI HumanAI RP	512K / 14.4 GB	16	1
SpydazWeb AI HumanAI 002	512K / 14.4 GB	18	1
...daz Web AI ChatML 512K Project	512K / 14.5 GB	12	0
MegaBeam Mistral 7B 300K	282K / 14.4 GB	3779	16
MegaBeam Mistral 7B 300K	282K / 14.4 GB	8018	17
Hebrew Mistral 7B 200K	256K / 30 GB	23	15
Astral 256K 7B	250K / 14.4 GB	9	0
Astral 256K 7B V2	250K / 14.4 GB	8	0

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