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Mixtral 8x7B Instruct V0.1 AWQ by TheBloke

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Mixtral 8x7B Instruct V0.1 AWQ is an open-source language model by TheBloke. Features: 6.5b LLM, VRAM: 24.7GB, Context: 32K, License: apache-2.0, MoE, Quantized, Instruction-Based, LLM Explorer Score: 0.15.

  4-bit   Autotrain compatible   Awq Base model:mistralai/mixtral-8... Base model:quantized:mistralai...   Conversational   De   En   Es   Fr   Instruct   It   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/TheBloke/Mixtral-8x7B-Instruct-v0.1-AWQ 

Mixtral 8x7B Instruct V0.1 AWQ Benchmarks

LLME Score: 0.14848
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtral 8x7B Instruct V0.1 AWQ (TheBloke/Mixtral-8x7B-Instruct-v0.1-AWQ)
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Mixtral 8x7B Instruct V0.1 AWQ Parameters and Internals

Model Type 
Sparse Mixture of Experts, Generative Model
Use Cases 
Areas:
Research, Commercial Applications
Limitations:
The model does not have any moderation mechanisms.
Additional Notes 
Model cannot (yet) be instantiated with Hugging Face's ecosystem.
Supported Languages 
fr (high), it (high), de (high), es (high), en (high)
Training Details 
Data Sources:
VMware Open Instruct
Methodology:
Fine-tuning techniques used
Model Architecture:
Sparse Mixture of Experts
Input Output 
Input Format:
[INST] {prompt} [/INST]
Accepted Modalities:
text
Output Format:
text
LLM NameMixtral 8x7B Instruct V0.1 AWQ
Repository 🤗https://huggingface.co/TheBloke/Mixtral-8x7B-Instruct-v0.1-AWQ 
Model NameMixtral 8X7B Instruct v0.1
Model CreatorMistral AI_
Base Model(s)  mistralai/Mixtral-8x7B-Instruct-v0.1   mistralai/Mixtral-8x7B-Instruct-v0.1
Model Size6.5b
Required VRAM24.7 GB
Updated2025-10-22
MaintainerTheBloke
Model Typemixtral
Instruction-BasedYes
Model Files  10.0 GB: 1-of-3   10.0 GB: 2-of-3   4.7 GB: 3-of-3
Supported Languagesfr it de es en
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.36.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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...xtral Instruct AWQ Clone Dec2332K / 24.7 GB60
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Mixtral 8x7B Instruct V0.1 AWQ32K / 24.7 GB716
...nstruct V0.1 AQLM 2Bit 1x16 Hf32K / 13.1 GB1119
...uct V0.1 OmniQuantv1 W4a16g12832K / 24.7 GB51

Rank the Mixtral 8x7B Instruct V0.1 AWQ 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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