What are the hardware requirements for DreadMix?

DreadMix requires approximately 16.1 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 DreadMix and how large is it?

DreadMix is developed by BoltMonkey, a model with 8b 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 DreadMix?

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

DreadMix by BoltMonkey — VRAM 16.1GB, 8K context

Name: DreadMix
Author: BoltMonkey

DreadMix is an open-source language model by BoltMonkey. Features: 8b LLM, VRAM: 16.1GB, Context: 8K, Merged, LLM Explorer Score: 0.22.

Merged Model Dreadpoor/eunoia vespera-8b-li... Dreadpoor/promissum mane-8b-li... Llama Model-index Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/BoltMonkey/DreadMix

DreadMix Parameters and Internals

Model Type

merge

Additional Notes

DreadMix is a merge of two models using LazyMergekit, which is configured with specific parameters and merge methods.

Training Details

Methodology:

LazyMergekit

LLM Name	DreadMix
Repository 🤗	https://huggingface.co/BoltMonkey/DreadMix
Base Model(s)	Eunoia Vespera 8B LINEAR ...ssum Mane 8B LINEAR Lorablated DreadPoor/Eunoia_Vespera-8B-LINEAR DreadPoor/Promissum_Mane-8B-LINEAR-lorablated
Merged Model	Yes
Model Size	8b
Required VRAM	16.1 GB
Updated	2026-10-09
Maintainer	BoltMonkey
Model Type	llama
Model Files	5.0 GB: 1-of-4 5.0 GB: 2-of-4 4.9 GB: 3-of-4 1.2 GB: 4-of-4
Model Architecture	LlamaForCausalLM
Context Length	8192
Model Max Length	8192
Transformers Version	4.44.2
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the DreadMix capabilities

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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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