LLM EXPLORER
 LLM Explorer: A Curated Large Language Model Directory and Analytics
Dark Theme
  Agents   Benchmarks   LLM  List    LLM Hosting    LLM Leaderboards    Blog    Newsfeed    Advertise

Mixtral 8x7B Instruct V0.1 AWQ by TheBloke

 »  All LLMs  »  TheBloke  »  Mixtral 8x7B Instruct V0.1 AWQ   URL Share it on

  1675   

Mixtral 8x7B Instruct V0.1 AWQ is an open-source language model by TheBloke. Features: 46.7b LLM, VRAM: 24.7GB, Context: 32K, License: apache-2.0, MoE, Quantized, Instruction-Based, LLM Explorer Score: 0.12.

  4-bit   Awq Base model:mistralai/mixtral-8... Base model:quantized:mistralai...   Conversational   De   Deploy:azure   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: 0.12226
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)
🌟 Advertise your project 🚀

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 Size46.7b
Required VRAM24.7 GB
Updated2026-05-15
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

Best Alternatives to Mixtral 8x7B Instruct V0.1 AWQ

Best Alternatives
Context / RAM
Downloads
Likes
Dolphin 2.7 Mixtral 8x7b AWQ32K / 24.7 GB353823
Mixtral 8x7B Instruct V0.1 AWQ32K / 24.7 GB50
Mixtral Instruct AWQ32K / 24.7 GB251143
...xtral Instruct AWQ Clone Dec2332K / 24.7 GB90
...ixtral Instruct 8x7b Zloss AWQ32K / 24.7 GB102
...0.1 LimaRP ZLoss DARE TIES AWQ32K / 24.7 GB113
...Instruct V0.1 LimaRP ZLoss AWQ32K / 24.7 GB81
Dolphin 2.6 Mixtral 8x7b AWQ32K / 24.7 GB10412
...utLM Mixtral 8x7B Instruct AWQ32K / 24.7 GB172
...1 Mixtral 8x7b Instruct V3 AWQ32K / 24.7 GB71
Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Mixtral-8x7B-Instruct-v0.1-AWQ.

Rank the Mixtral 8x7B Instruct V0.1 AWQ Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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  

What open-source LLMs or SLMs are you in search of? 54415 in total.

Email us: info@extractum.io. Our Privacy Policy  | Terms and Conditions  | Suggest an improvement.
Our Social Media →  
Original data from HuggingFace, OpenCompass and various public git repos.
Check out Ag3ntum — our secure, self-hosted AI agent for server management.
Release v20260328a
  Support LLM Explorer