What are the hardware requirements for Darkest Muse V1?

Darkest Muse V1 requires approximately 20.4 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 Darkest Muse V1 and how large is it?

Darkest Muse V1 is developed by sam-paech, a model with 9b 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 Darkest Muse V1?

Darkest Muse V1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Darkest Muse V1 by sam-paech — VRAM 20.4GB, 8K context

Name: Darkest Muse V1
Author: sam-paech

Darkest Muse V1 is an open-source language model by sam-paech. Features: 9b LLM, VRAM: 20.4GB, Context: 8K, License: apache-2.0, Merged, LLM Explorer Score: 0.25.

Merged Model Base model:finetune:lemon07r/g... Base model:lemon07r/gemma-2-at... Creative-writing Dataset:sam-paech/gutenberg3-g... Gemma2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/sam-paech/Darkest-muse-v1

Darkest Muse V1 Parameters and Internals

LLM Name	Darkest Muse V1
Repository 🤗	https://huggingface.co/sam-paech/Darkest-muse-v1
Base Model(s)	Gemma 2 Ataraxy V2 9B Delirium V1 Quill V1 lemon07r/Gemma-2-Ataraxy-v2-9B sam-paech/Delirium-v1 sam-paech/Quill-v1
Merged Model	Yes
Model Size	9b
Required VRAM	20.4 GB
Updated	2026-08-03
Maintainer	sam-paech
Model Type	gemma2
Model Files	5.0 GB: 1-of-5 5.0 GB: 2-of-5 4.9 GB: 3-of-5 5.0 GB: 4-of-5 0.5 GB: 5-of-5
Model Architecture	Gemma2ForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.45.2
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	bfloat16

Rank the Darkest Muse V1 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 Darkest Muse V1

Best Alternatives	Context / RAM	Downloads	Likes
G2 GSHT 32K	32K / 20.4 GB	8	1
SystemGemma2 9B It	32K / 18.6 GB	5	2
Gemma 2 9B It	8K / 18.6 GB	80757	11
GWQ 9B Preview2	8K / 18.6 GB	11	10
Gemma 2 9B It	8K / 18.6 GB	6	0
Gemma 2 9B It SimPO	8K / 18.6 GB	473	173
Gemma 2 9B It	8K / 18.6 GB	323635	837
Gemma 2 9B It Blend Rebase	8K / 20.4 GB	5	0
Gemma 2 9B JEE Socratic Final	8K / 18.6 GB	1118	0
Gemma 2 9B	8K / 37.1 GB	95888	717

Note: green Score (e.g. "73.2") means that the model is better than sam-paech/Darkest-muse-v1.