What are the hardware requirements for Lumosia MoE 4x10.7 GGUF?

Lumosia MoE 4x10.7 GGUF requires approximately 12 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Lumosia MoE 4x10.7 GGUF and how large is it?

Lumosia MoE 4x10.7 GGUF is developed by TheBloke, a model with 10.7b 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 Lumosia MoE 4x10.7 GGUF?

Lumosia MoE 4x10.7 GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Lumosia MoE 4x10.7 GGUF by TheBloke — VRAM 12GB

Name: Lumosia MoE 4x10.7 GGUF
Author: TheBloke

Lumosia MoE 4x10.7 GGUF is an open-source language model by TheBloke. Features: 10.7b LLM, VRAM: 12GB, License: apache-2.0, MoE, Quantized, LLM Explorer Score: 0.11.

Base model:quantized:steelstor... Base model:steelstorage/lumosi... Conversational Dopeornope/solarc-m-10.7b Gguf Jeonsworld/carbonvillain-en-10... Kyujinpy/sakura-solar-instruct Lazymergekit Maywell/pivot-10.7b-mistral-v0... Merge Mergekit Mixtral Moe Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/TheBloke/Lumosia-MoE-4x10.7-GGUF

Lumosia MoE 4x10.7 GGUF Parameters and Internals

Model Type

mixture of experts, text generation

Use Cases

Areas:

research

Additional Notes

This is a very experimental model made with Mixture of Experts (MoE) technique.

Training Details

Data Sources:

DopeorNope/SOLARC-M-10.7B, maywell/PiVoT-10.7B-Mistral-v0.2-RP, kyujinpy/Sakura-SOLAR-Instruct, jeonsworld/CarbonVillain-en-10.7B-v1

Methodology:

Mixture of Experts ensemble made with multiple Solar models

Context Length:

16000

Model Architecture:

Mixture of Experts (MoE)

Input Output

Input Format:

### System: ### USER:{prompt} ### Assistant:

Accepted Modalities:

text

Output Format:

text generation

LLM Name	Lumosia MoE 4x10.7 GGUF
Repository 🤗	https://huggingface.co/TheBloke/Lumosia-MoE-4x10.7-GGUF
Model Name	Lumosia MoE 4X10.7
Model Creator	Steel
Base Model(s)	Steelskull/Lumosia-MoE-4x10.7 Steelskull/Lumosia-MoE-4x10.7
Model Size	10.7b
Required VRAM	12 GB
Updated	2026-07-09
Maintainer	TheBloke
Model Type	mixtral
Model Files	12.0 GB 15.8 GB 15.7 GB 15.6 GB 20.3 GB 20.4 GB 20.3 GB 24.8 GB 24.9 GB 24.8 GB 29.6 GB 38.4 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel
License	apache-2.0

Rank the Lumosia MoE 4x10.7 GGUF 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 Lumosia MoE 4x10.7 GGUF

Best Alternatives	Context / RAM	Downloads	Likes
Nous Hermes 2 SOLAR 10.7B GGUF	0K / 4.5 GB	4865	113
SOLAR 10.7B Instruct V1.0 GGUF	0K / 4.5 GB	1522	84
Tess 10.7B V1.5B GGUF	0K / 4 GB	242	7
Sensualize Solar 10.7B GGUF	0K / 4.5 GB	488	10
OPEN SOLAR KO 10.7B GGUF	0K / 4.1 GB	104	1
CarbonVillain En 10.7B V4 GGUF	0K / 4.5 GB	504	6
...VoT 10.7B Mistral V0.2 RP GGUF	0K / 4.5 GB	665	9
LMCocktail 10.7B V1 GGUF	0K / 4.5 GB	296	5
Solar 10.7B SLERP GGUF	0K / 4.5 GB	339	13
Frostwind 10.7B V1 GGUF	0K / 4.5 GB	266	4

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Lumosia-MoE-4x10.7-GGUF.