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Qwen3.6 27B AWQ 4bit by Alennnndy

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Qwen3.6 27B AWQ 4bit is an open-source language model by Alennnndy. Features: 27b LLM, VRAM: 18.7GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.29.

  4bit   Awq Base model:quantized:qwen/qwen...   Base model:qwen/qwen3.6-27b   Compressed-tensors   Conversational   Llmcompressor   Quantized   Qwen   Qwen3.6   Qwen3 5   Region:us   Safetensors   Vllm
Model Card on HF 🤗: https://huggingface.co/Alennnndy/Qwen3.6-27B-AWQ-4bit 

Qwen3.6 27B AWQ 4bit Benchmarks

LLME Score: 0.2943
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen3.6 27B AWQ 4bit (Alennnndy/Qwen3.6-27B-AWQ-4bit)
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Qwen3.6 27B AWQ 4bit Parameters and Internals

LLM NameQwen3.6 27B AWQ 4bit
Repository 🤗https://huggingface.co/Alennnndy/Qwen3.6-27B-AWQ-4bit 
Base Model(s)  Qwen/Qwen3.6-27B   Qwen/Qwen3.6-27B
Model Size27b
Required VRAM18.7 GB
Updated2026-07-05
MaintainerAlennnndy
Model Typeqwen3_5
Model Files  18.7 GB
AWQ QuantizationYes
Quantization Typeawq|4bit
Model ArchitectureQwen3_5ForConditionalGeneration
Licenseapache-2.0
Model Max Length262144
Transformers Version5.10.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Errorsreplace

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Qwen3.6 27B NVFP40K / 26.4 GB111480195
Note: green Score (e.g. "73.2") means that the model is better than Alennnndy/Qwen3.6-27B-AWQ-4bit.

Rank the Qwen3.6 27B AWQ 4bit 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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