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Qwen Audio by Qwen

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Qwen Audio is an open-source language model by Qwen. Features: 8.4b LLM, VRAM: 16.7GB, Context: 2K, LLM Explorer Score: 0.26, ELO: 1331.

  Arxiv:2311.07919   Audio-text-to-text   Custom code   En   Qwen   Region:us   Safetensors   Sharded   Tensorflow   Zh
Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen-Audio 

Qwen Audio Benchmarks

LMSys ELO: 1331 vs 1272 (so35)4.6%
LLME Score: 0.25852
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen Audio (Qwen/Qwen-Audio)
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Qwen Audio Parameters and Internals

Model Type 
Multimodal, Audio understanding
Use Cases 
Areas:
Audio analysis, Sound understanding, Music appreciation, Speech editing
Primary Use Cases:
Multimodal understanding, Sound analysis, Multi-turn dialogues, Multi-language support
Additional Notes 
The model is designed to operate efficiently with diverse audio and text inputs, and aims to serve as a universal audio understanding model based on Alibaba Cloud's large model series.
Supported Languages 
languages_supported (/ languages: zh, en)
Training Details 
Methodology:
Multimodal and multi-task pre-training with a multi-task training framework.
Input Output 
Input Format:
Audio (FLAC format) and text inputs
Accepted Modalities:
Audio, Text
Output Format:
Text outputs
LLM NameQwen Audio
Repository 🤗https://huggingface.co/Qwen/Qwen-Audio 
Model Size8.4b
Required VRAM16.7 GB
Updated2026-05-11
MaintainerQwen
Model Typeqwen
Model Files  2.0 GB: 1-of-9   1.9 GB: 2-of-9   1.9 GB: 3-of-9   2.0 GB: 4-of-9   1.9 GB: 5-of-9   1.9 GB: 6-of-9   1.9 GB: 7-of-9   1.9 GB: 8-of-9   1.3 GB: 9-of-9
Supported Languageszh en
Model ArchitectureQWenLMHeadModel
Context Length2048
Model Max Length2048
Transformers Version4.32.0
Tokenizer ClassQWenTokenizer
Vocabulary Size155947
Torch Data Typebfloat16

Best Alternatives to Qwen Audio

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Context / RAM
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Qwen Audio Chat2K / 16.7 GB3046495

Rank the Qwen Audio 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  

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