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WizardLM 2 8x22B AWQ by MaziyarPanahi

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WizardLM 2 8x22B AWQ is an open-source language model by MaziyarPanahi. Features: 140.6b LLM, VRAM: 73.7GB, Context: 64K, MoE, Quantized, LLM Explorer Score: 0.13.

  4-bit   Awq Base model:microsoft/wizardlm-... Base model:quantized:microsoft...   Conversational   Finetuned   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/MaziyarPanahi/WizardLM-2-8x22B-AWQ 

WizardLM 2 8x22B AWQ Benchmarks

LLME Score: 0.12697
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
WizardLM 2 8x22B AWQ (MaziyarPanahi/WizardLM-2-8x22B-AWQ)
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WizardLM 2 8x22B AWQ Parameters and Internals

Model Type 
text-generation
Additional Notes 
The model is a quantized (AWQ) version, optimized for improved performance in text generation.
LLM NameWizardLM 2 8x22B AWQ
Repository 🤗https://huggingface.co/MaziyarPanahi/WizardLM-2-8x22B-AWQ 
Model NameWizardLM-2-8x22B-AWQ
Base Model(s)  microsoft/WizardLM-2-8x22B   microsoft/WizardLM-2-8x22B
Model Size140.6b
Required VRAM73.7 GB
Updated2026-04-11
MaintainerMaziyarPanahi
Model Typemixtral
Model Files  5.0 GB: 1-of-15   5.0 GB: 2-of-15   5.0 GB: 3-of-15   5.0 GB: 4-of-15   5.0 GB: 5-of-15   5.0 GB: 6-of-15   5.0 GB: 7-of-15   5.0 GB: 8-of-15   5.0 GB: 9-of-15   5.0 GB: 10-of-15   5.0 GB: 11-of-15   5.0 GB: 12-of-15   5.0 GB: 13-of-15   5.0 GB: 14-of-15   3.7 GB: 15-of-15
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMixtralForCausalLM
Context Length65536
Model Max Length65536
Transformers Version4.38.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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WizardLM 2 8x22B64K / 216.8 GB9545411
Mixtral 8x22B V0.164K / 221.6 GB3642237
Mixtral 8x22B V0.164K / 212 GB319671
Note: green Score (e.g. "73.2") means that the model is better than MaziyarPanahi/WizardLM-2-8x22B-AWQ.

Rank the WizardLM 2 8x22B 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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