What are the hardware requirements for AlphaMonarch 7B AWQ?

AlphaMonarch 7B AWQ requires approximately 4.2 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 AlphaMonarch 7B AWQ and how large is it?

AlphaMonarch 7B AWQ 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.

Where can I download or evaluate AlphaMonarch 7B AWQ?

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

AlphaMonarch 7B AWQ by mlabonne — VRAM 4.2GB, 32K context

Name: AlphaMonarch 7B AWQ
Author: mlabonne

AlphaMonarch 7B AWQ is an open-source language model by mlabonne. Features: 7b LLM, VRAM: 4.2GB, Context: 32K, License: cc-by-nc-4.0, Quantized, LLM Explorer Score: 0.12.

4-bit Autoquant Awq Base model:mlabonne/neuralmona... Base model:quantized:mlabonne/... Conversational Dpo En Endpoints compatible Lazymergekit Merge Mistral Model-index Quantized Region:us Rlhf Safetensors

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

AlphaMonarch 7B AWQ Parameters and Internals

Model Type

text-generation

Use Cases

Applications:

text generation, conversations, RP, storytelling

Primary Use Cases:

conversational tasks, storytelling, reasoning

Additional Notes

Performs well in reasoning and conversational tasks, has a formal style which can be modified through prompt engineering.

Training Details

Data Sources:

mlabonne/truthy-dpo-v0.1, mlabonne/distilabel-intel-orca-dpo-pairs, mlabonne/chatml-OpenHermes2.5-dpo-binarized-alpha

Context Length:

8000

Input Output

Input Format:

Chat template format

Accepted Modalities:

text

Output Format:

text generation output

Performance Tips:

Adjust inference parameters like temperature, top_k, and top_p for better results.

LLM Name	AlphaMonarch 7B AWQ
Repository 🤗	https://huggingface.co/mlabonne/AlphaMonarch-7B-AWQ
Base Model(s)	NeuralMonarch 7B mlabonne/NeuralMonarch-7B
Model Size	7b
Required VRAM	4.2 GB
Updated	2026-08-08
Maintainer	mlabonne
Model Type	mistral
Model Files	4.2 GB
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	MistralForCausalLM
License	cc-by-nc-4.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	float16

Rank the AlphaMonarch 7B 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

Best Alternatives to AlphaMonarch 7B AWQ

Best Alternatives	Context / RAM	Downloads	Likes
Mistral 7B Instruct V0.2 AWQ	32K / 4.2 GB	6	0
Mistral 7B Instruct V0.2 AWQ	32K / 4.2 GB	298182	52
Mistral 7B Instruct V0.3 AWQ	32K / 4.2 GB	5633	10
Mistral 7B Instruct V0.1 AWQ	32K / 4.2 GB	15461	2
Ghost 7B Alpha AWQ	32K / 4.2 GB	14	0
Tess 7B V2.0 AWQ	32K / 4.2 GB	1	1
...reeze 7B 32K Instruct V1.0 AWQ	32K / 4.7 GB	9	0
Breeze 7B Instruct V1.0 AWQ	32K / 4.6 GB	5	0
OpenHermes 2.5 Mistral 7B AWQ	32K / 4.2 GB	23691	21
NSFW DPO Noromaid 7B AWQ	32K / 4.2 GB	206	2

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