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Qwen3 30B A3B Instruct 2507 AWQ 4bit by cpatonn

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Qwen3 30B A3B Instruct 2507 AWQ 4bit is an open-source language model by cpatonn. Features: 30b LLM, VRAM: 18.1GB, Context: 256K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.27.

  Arxiv:2505.09388   4bit   Autotrain compatible   Awq Base model:quantized:qwen/qwen... Base model:qwen/qwen3-30b-a3b-...   Compressed-tensors   Conversational   Endpoints compatible   Instruct   Quantized   Qwen3 moe   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/cpatonn/Qwen3-30B-A3B-Instruct-2507-AWQ-4bit 

Qwen3 30B A3B Instruct 2507 AWQ 4bit Benchmarks

LLME Score: 0.27435
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen3 30B A3B Instruct 2507 AWQ 4bit (cpatonn/Qwen3-30B-A3B-Instruct-2507-AWQ-4bit)
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Qwen3 30B A3B Instruct 2507 AWQ 4bit Parameters and Internals

LLM NameQwen3 30B A3B Instruct 2507 AWQ 4bit
Repository 🤗https://huggingface.co/cpatonn/Qwen3-30B-A3B-Instruct-2507-AWQ-4bit 
Base Model(s)  Qwen3 30B A3B Instruct 2507   Qwen/Qwen3-30B-A3B-Instruct-2507
Model Size30b
Required VRAM18.1 GB
Updated2025-10-28
Maintainercpatonn
Model Typeqwen3_moe
Instruction-BasedYes
Model Files  5.0 GB: 1-of-4   5.0 GB: 2-of-4   5.0 GB: 3-of-4   3.1 GB: 4-of-4
AWQ QuantizationYes
Quantization Typeawq|4bit
Model ArchitectureQwen3MoeForCausalLM
Licenseapache-2.0
Context Length262144
Model Max Length262144
Transformers Version4.56.0.dev0
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than cpatonn/Qwen3-30B-A3B-Instruct-2507-AWQ-4bit.

Rank the Qwen3 30B A3B Instruct 2507 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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