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Lumosia MoE 4x10.7 GGUF by TheBloke

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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 Benchmarks

LLME Score: 0.13412
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Lumosia MoE 4x10.7 GGUF (TheBloke/Lumosia-MoE-4x10.7-GGUF)
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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 NameLumosia MoE 4x10.7 GGUF
Repository 🤗https://huggingface.co/TheBloke/Lumosia-MoE-4x10.7-GGUF 
Model NameLumosia MoE 4X10.7
Model CreatorSteel
Base Model(s)  Steelskull/Lumosia-MoE-4x10.7   Steelskull/Lumosia-MoE-4x10.7
Model Size10.7b
Required VRAM12 GB
Updated2025-09-14
MaintainerTheBloke
Model Typemixtral
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 QuantizationYes
Quantization Typegguf
Model ArchitectureAutoModel
Licenseapache-2.0

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

Rank the Lumosia MoE 4x10.7 GGUF Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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