What are the hardware requirements for AlphaMonarch 7B 2bit HQQ?

AlphaMonarch 7B 2bit HQQ requires approximately 2.4 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 AlphaMonarch 7B 2bit HQQ and how large is it?

AlphaMonarch 7B 2bit HQQ 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 2bit HQQ?

AlphaMonarch 7B 2bit HQQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

AlphaMonarch 7B 2bit HQQ by mlabonne — VRAM 2.4GB, 32K context

Name: AlphaMonarch 7B 2bit HQQ
Author: mlabonne

AlphaMonarch 7B 2bit HQQ is an open-source language model by mlabonne. Features: 7b LLM, VRAM: 2.4GB, Context: 32K, License: cc-by-nc-4.0, Quantized, LLM Explorer Score: 0.12.

2bit Autoquant Base model:finetune:mlabonne/n... Base model:mlabonne/neuralmona... Conversational Dpo En Endpoints compatible Hqq Lazymergekit Merge Mistral Model-index Quantized Region:us Rlhf

Model Card on HF 🤗: https://huggingface.co/mlabonne/AlphaMonarch-7B-2bit-HQQ

AlphaMonarch 7B 2bit HQQ 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 2bit HQQ
Repository 🤗	https://huggingface.co/mlabonne/AlphaMonarch-7B-2bit-HQQ
Base Model(s)	NeuralMonarch 7B mlabonne/NeuralMonarch-7B
Model Size	7b
Required VRAM	2.4 GB
Updated	2026-05-04
Maintainer	mlabonne
Model Type	mistral
Model Files	2.4 GB
Supported Languages	en
Quantization Type	2bit
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 2bit HQQ 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

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Mistral 7B Instruct V0.2 8bit	32K / 7.6 GB	5	1
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Note: green Score (e.g. "73.2") means that the model is better than mlabonne/AlphaMonarch-7B-2bit-HQQ.