What are the hardware requirements for Kunoichi Lemon Royale 7B 8.0bpw H8 EXL2?

Kunoichi Lemon Royale 7B 8.0bpw H8 EXL2 requires approximately 7.4 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Kunoichi Lemon Royale 7B 8.0bpw H8 EXL2 and how large is it?

Kunoichi Lemon Royale 7B 8.0bpw H8 EXL2 is developed by grimjim, 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 Kunoichi Lemon Royale 7B 8.0bpw H8 EXL2?

Kunoichi Lemon Royale 7B 8.0bpw H8 EXL2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Kunoichi Lemon Royale 7B 8.0bpw H8 EXL2 by grimjim — VRAM 7.4GB, 8K context

Name: Kunoichi Lemon Royale 7B 8.0bpw H8 EXL2
Author: grimjim

Kunoichi Lemon Royale 7B 8.0bpw H8 EXL2 is an open-source language model by grimjim. Features: 7b LLM, VRAM: 7.4GB, Context: 8K, License: cc-by-nc-4.0, Quantized, LLM Explorer Score: 0.12.

Arxiv:2306.01708 Arxiv:2311.03099 Base model:finetune:grimjim/ku... Base model:grimjim/kunoichi-le... Endpoints compatible Exl2 Mistral Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/grimjim/kunoichi-lemon-royale-7B-8.0bpw_h8_exl2

Kunoichi Lemon Royale 7B 8.0bpw H8 EXL2 Parameters and Internals

Model Type

text-generation

Additional Notes

Model has a tendency to reveal character interiority in narratives; experimental and may reveal context.

Training Details

Methodology:

DARE TIES merge method using multiple pre-trained models

Context Length:

8000

Model Architecture:

Merge of multiple pre-trained models

Input Output

Accepted Modalities:

text

LLM Name	Kunoichi Lemon Royale 7B 8.0bpw H8 EXL2
Repository 🤗	https://huggingface.co/grimjim/kunoichi-lemon-royale-7B-8.0bpw_h8_exl2
Base Model(s)	Kunoichi Lemon Royale 7B grimjim/kunoichi-lemon-royale-7B
Model Size	7b
Required VRAM	7.4 GB
Updated	2026-08-05
Maintainer	grimjim
Model Type	mistral
Model Files	2.7 GB: 1-of-3 2.6 GB: 2-of-3 2.1 GB: 3-of-3
Quantization Type	exl2
Model Architecture	MistralForCausalLM
License	cc-by-nc-4.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Kunoichi Lemon Royale 7B 8.0bpw H8 EXL2 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 Kunoichi Lemon Royale 7B 8.0bpw H8 EXL2

Best Alternatives	Context / RAM	Downloads	Likes
...t 3.5 0106 128K 4.0bpw H6 EXL2	128K / 3.9 GB	4	1
...t 3.5 0106 128K 8.0bpw H8 EXL2	128K / 7.4 GB	1	1
...aude Sonnet Mistral 7B It V0.3	32K / 14.5 GB	7	2
Mistral 7B Instruct V0.2 Fp16	32K / 14.4 GB	26	0
Mistral 7B V0.3 Bnb 4bit	32K / 4.1 GB	381323	22
Mistral 7B Instruct V0.2 4bit	32K / 4.3 GB	79	1
...tral 7B Instruct V0.3 Bnb 4bit	32K / 4.1 GB	34633	42
Mistral 7B Instruct V0.2 8bit	32K / 7.6 GB	5	1
...tral 7B Instruct V0.2 Bnb 4bit	32K / 4.1 GB	7160	35
Mixtral V0.3 Full 16bit	32K / 14.5 GB	12	0

Note: green Score (e.g. "73.2") means that the model is better than grimjim/kunoichi-lemon-royale-7B-8.0bpw_h8_exl2.