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Karasu Mixtral 8x22B V0.1 AWQ by lightblue

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Karasu Mixtral 8x22B V0.1 AWQ is an open-source language model by lightblue. Features: 140.6b LLM, VRAM: 73.7GB, Context: 64K, MoE, Quantized, Merged, LLM Explorer Score: 0.13.

  Merged Model   4-bit   Awq   Conversational   Endpoints compatible   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/lightblue/Karasu-Mixtral-8x22B-v0.1-AWQ 

Karasu Mixtral 8x22B V0.1 AWQ Benchmarks

LLME Score: 0.1258
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Karasu Mixtral 8x22B V0.1 AWQ (lightblue/Karasu-Mixtral-8x22B-v0.1-AWQ)
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Karasu Mixtral 8x22B V0.1 AWQ Parameters and Internals

Model Type 
Causal Language Model
Additional Notes 
Quantized using AutoAWQForCausalLM with 4-bit configuration, zero_point enabled, q_group_size of 128, and version GEMM.
LLM NameKarasu Mixtral 8x22B V0.1 AWQ
Repository 🤗https://huggingface.co/lightblue/Karasu-Mixtral-8x22B-v0.1-AWQ 
Merged ModelYes
Model Size140.6b
Required VRAM73.7 GB
Updated2026-05-02
Maintainerlightblue
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</s>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than lightblue/Karasu-Mixtral-8x22B-v0.1-AWQ.

Rank the Karasu Mixtral 8x22B 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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