Mixtral 7Bx2 MoE GPTQ by TheBloke

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Mixtral 7Bx2 MoE GPTQ is an open-source language model by TheBloke. Features: 12.9b LLM, VRAM: 7.1GB, Context: 32K, License: cc-by-nc-4.0, MoE, Quantized, LLM Explorer Score: 0.11.

  4-bit Base model:cloudyu/mixtral 7bx... Base model:quantized:cloudyu/m...   Gptq   Mixtral   Moe   Quantized   Region:us   Safetensors

Mixtral 7Bx2 MoE GPTQ Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtral 7Bx2 MoE GPTQ (TheBloke/Mixtral_7Bx2_MoE-GPTQ)
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Mixtral 7Bx2 MoE GPTQ Parameters and Internals

Model Type 
mixtral
LLM NameMixtral 7Bx2 MoE GPTQ
Repository ๐Ÿค—https://huggingface.co/TheBloke/Mixtral_7Bx2_MoE-GPTQ 
Model NameMixtral 7Bx2 MoE
Model Creatorhai
Base Model(s)  Mixtral 7Bx2 MoE   cloudyu/Mixtral_7Bx2_MoE
Model Size12.9b
Required VRAM7.1 GB
Updated2026-03-29
MaintainerTheBloke
Model Typemixtral
Model Files  7.1 GB
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureMixtralForCausalLM
Licensecc-by-nc-4.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token<s>
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Mixtral_7Bx2_MoE-GPTQ.

Rank the Mixtral 7Bx2 MoE GPTQ 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  
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Code Generation  
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Release v20260328a