What are the hardware requirements for Nyanade Stunna Maid 7B?

Nyanade Stunna Maid 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 Nyanade Stunna Maid 7B and how large is it?

Nyanade Stunna Maid 7B is developed by Nitral-AI, 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 Nyanade Stunna Maid 7B perform on standard benchmarks?

Nyanade Stunna Maid 7B has the following published scores: MMLU 64.44. Compare against reference models on this page or on the LLM Explorer leaderboards.

Nyanade Stunna Maid 7B by Nitral-AI — VRAM 14.4GB, 32K context

Name: Nyanade Stunna Maid 7B
Author: Nitral-AI

Nyanade Stunna Maid 7B is an open-source language model by Nitral-AI. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: other, Quantized, Merged, LLM Explorer Score: 0.13, Arc: 66.1, HellaSwag: 85.3, MMLU: 64.4, GSM8K: 51.6.

Merged Model Base model:chaoticneutrals/nya... Base model:quantized:chaoticne... Endpoints compatible Gguf Mistral Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Nitral-AI/Nyanade_Stunna-Maid-7B

Nyanade Stunna Maid 7B Parameters and Internals

Model Type

multimodal

Additional Notes

Quants thanks to Lewdiculus: [Nyanade_Stunna-Maid-7B-GGUF-IQ-Imatrix](https://huggingface.co/Lewdiculous/Nyanade_Stunna-Maid-7B-GGUF-IQ-Imatrix)

LLM Name	Nyanade Stunna Maid 7B
Repository 🤗	https://huggingface.co/Nitral-AI/Nyanade_Stunna-Maid-7B
Base Model(s)	Nitral-AI/Nyanade-Maid-7B Nyan Stunna 7B Nitral-AI/Nyanade-Maid-7B Nitral-AI/Nyan-Stunna-7B
Merged Model	Yes
Model Size	7b
Required VRAM	14.4 GB
Updated	2025-12-07
Maintainer	Nitral-AI
Model Type	mistral
Model Files	0.6 GB 2.0 GB: 1-of-8 1.9 GB: 2-of-8 1.9 GB: 3-of-8 2.0 GB: 4-of-8 1.9 GB: 5-of-8 1.9 GB: 6-of-8 1.9 GB: 7-of-8 0.9 GB: 8-of-8
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	MistralForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Nyanade Stunna Maid 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

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MegaBeam Mistral 7B 300K Gguf	282K / 5 GB	35	3
MegaBeam Mistral 7B 300K Gguf	282K / 5 GB	34	3
Mistral 7B Instruct V0.2.gguf	32K / 14.5 GB	17	3
Backrooms Mistral 7B 10e	32K / 14.5 GB	128	0
Mistral 7B Instruct V0.2 GGUF	32K / 4.4 GB	26	2
...andle Mistral 7B Instruct V0.2	32K / 14.4 GB	67	0
...andle Dolphin 2.2.1 Mistral 7B	32K / 14.4 GB	83	0
Boptruth Agatha 7B	32K / 14.4 GB	129	0
Mahou 1.2a Mistral 7B	32K / 14.4 GB	33	7
Tamil Mistral 7B Instruct V0.1	32K / 14.8 GB	350	14

Note: green Score (e.g. "73.2") means that the model is better than Nitral-AI/Nyanade_Stunna-Maid-7B.