Mixtral 11Bx2 MoE 19B 8.0bpw H8 EXL2 by LoneStriker

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Mixtral 11Bx2 MoE 19B 8.0bpw H8 EXL2 Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtral 11Bx2 MoE 19B 8.0bpw H8 EXL2 (LoneStriker/Mixtral_11Bx2_MoE_19B-8.0bpw-h8-exl2)
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Mixtral 11Bx2 MoE 19B 8.0bpw H8 EXL2 Parameters and Internals

Model Type 
MoE, causalLM
Additional Notes 
Model is a mixture of experts (MoE) derived from two large models and can run on both CPU and GPU.
Training Details 
Data Sources:
kyujinpy/Sakura-SOLAR-Instruct, jeonsworld/CarbonVillain-en-10.7B-v1
Input Output 
Input Format:
text
Accepted Modalities:
text
Output Format:
text
Performance Tips:
For improved performance, use GPU with specified settings.
LLM NameMixtral 11Bx2 MoE 19B 8.0bpw H8 EXL2
Repository ๐Ÿค—https://huggingface.co/LoneStriker/Mixtral_11Bx2_MoE_19B-8.0bpw-h8-exl2 
Model Size19b
Required VRAM19.4 GB
Updated2025-09-23
MaintainerLoneStriker
Model Typemixtral
Model Files  8.6 GB: 1-of-3   8.6 GB: 2-of-3   2.2 GB: 3-of-3
Quantization Typeexl2
Model ArchitectureMixtralForCausalLM
Licensecc-by-nc-4.0
Context Length4096
Model Max Length4096
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token<s>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/Mixtral_11Bx2_MoE_19B-8.0bpw-h8-exl2.

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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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124