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Mixtral 34Bx2 MoE 60B 8.0bpw H8 EXL2 by LoneStriker

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Mixtral 34Bx2 MoE 60B 8.0bpw H8 EXL2 is an open-source language model by LoneStriker. Features: 60b LLM, VRAM: 61.3GB, Context: 195K, License: cc-by-nc-4.0, MoE, Quantized, LLM Explorer Score: 0.11.

  Endpoints compatible   Exl2   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/LoneStriker/Mixtral_34Bx2_MoE_60B-8.0bpw-h8-exl2 

Mixtral 34Bx2 MoE 60B 8.0bpw H8 EXL2 Benchmarks

LLME Score: 0.11411
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtral 34Bx2 MoE 60B 8.0bpw H8 EXL2 (LoneStriker/Mixtral_34Bx2_MoE_60B-8.0bpw-h8-exl2)
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Mixtral 34Bx2 MoE 60B 8.0bpw H8 EXL2 Parameters and Internals

Model Type 
MoE, causal language model
Use Cases 
Areas:
research, non-commercial applications
Applications:
text generation, multilingual applications
Primary Use Cases:
creative writing, storytelling, education
Limitations:
commercial applications
Supported Languages 
English (high), Chinese (high)
Input Output 
Input Format:
text prompt
Accepted Modalities:
text
Output Format:
generated text
Performance Tips:
For better performance, use a GPU with CUDA support.
LLM NameMixtral 34Bx2 MoE 60B 8.0bpw H8 EXL2
Repository 🤗https://huggingface.co/LoneStriker/Mixtral_34Bx2_MoE_60B-8.0bpw-h8-exl2 
Model Size60b
Required VRAM61.3 GB
Updated2026-04-01
MaintainerLoneStriker
Model Typemixtral
Model Files  8.5 GB: 1-of-8   8.5 GB: 2-of-8   8.5 GB: 3-of-8   8.6 GB: 4-of-8   8.5 GB: 5-of-8   8.6 GB: 6-of-8   8.5 GB: 7-of-8   1.6 GB: 8-of-8
Quantization Typeexl2
Model ArchitectureMixtralForCausalLM
Licensecc-by-nc-4.0
Context Length200000
Model Max Length200000
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token<s>
Vocabulary Size64000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/Mixtral_34Bx2_MoE_60B-8.0bpw-h8-exl2.

Rank the Mixtral 34Bx2 MoE 60B 8.0bpw H8 EXL2 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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