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L3.2 8X4B MoE V2 Dark Champion Inst 21B Uncen Ablit by DavidAU

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L3.2 8X4B MoE V2 Dark Champion Inst 21B Uncen Ablit is an open-source language model by DavidAU. Features: 20.9b LLM, VRAM: 83.3GB, Context: 128K, MoE, Instruction-Based, LLM Explorer Score: 0.18.

  128k context   8 experts   8 x 4b   Autotrain compatible   Brainstorm 5x   Conversational   Endpoints compatible   Fine tune   Instruct   Llama 3.2   Mixtral   Mixture of experts   Moe   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/DavidAU/L3.2-8X4B-MOE-V2-Dark-Champion-Inst-21B-uncen-ablit 

L3.2 8X4B MoE V2 Dark Champion Inst 21B Uncen Ablit Benchmarks

LLME Score: 0.1831
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
L3.2 8X4B MoE V2 Dark Champion Inst 21B Uncen Ablit (DavidAU/L3.2-8X4B-MOE-V2-Dark-Champion-Inst-21B-uncen-ablit)
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L3.2 8X4B MoE V2 Dark Champion Inst 21B Uncen Ablit Parameters and Internals

LLM NameL3.2 8X4B MoE V2 Dark Champion Inst 21B Uncen Ablit
Repository 🤗https://huggingface.co/DavidAU/L3.2-8X4B-MOE-V2-Dark-Champion-Inst-21B-uncen-ablit 
Model Size20.9b
Required VRAM83.3 GB
Updated2025-09-23
MaintainerDavidAU
Model Typemixtral
Instruction-BasedYes
Model Files  5.0 GB: 1-of-17   4.9 GB: 2-of-17   4.9 GB: 3-of-17   4.9 GB: 4-of-17   4.9 GB: 5-of-17   4.9 GB: 6-of-17   4.9 GB: 7-of-17   4.9 GB: 8-of-17   4.9 GB: 9-of-17   5.0 GB: 10-of-17   5.0 GB: 11-of-17   4.9 GB: 12-of-17   4.9 GB: 13-of-17   4.9 GB: 14-of-17   4.9 GB: 15-of-17   4.9 GB: 16-of-17   4.6 GB: 17-of-17
Model ArchitectureMixtralForCausalLM
Context Length131072
Model Max Length131072
Transformers Version4.46.2
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|begin_of_text|>
Vocabulary Size128256
Torch Data Typefloat32

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...nsored Abliterated 21B Q 6 MLX128K / 18.3 GB5193
Note: green Score (e.g. "73.2") means that the model is better than DavidAU/L3.2-8X4B-MOE-V2-Dark-Champion-Inst-21B-uncen-ablit.

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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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