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Qwen1.5 4B by Qwen

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Qwen1.5 4B is an open-source language model by Qwen. Features: 4b LLM, VRAM: 7.9GB, Context: 32K, License: other, HF Score: 57.1, LLM Explorer Score: 0.21, Arc: 48.5, HellaSwag: 71.6, MMLU: 56.5, TruthfulQA: 47.3, WinoGrande: 66.2, GSM8K: 52.2.

  Arxiv:2309.16609   Conversational   Deploy:azure   En   Endpoints compatible   Pretrained   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen1.5-4B 

Qwen1.5 4B Benchmarks

MMLU Pro: 16.22
GPQA: 3.58
MUSR: 4.82
BBH: 16.25
IFEval: 24.45 vs 88 (so35)-72.2%
ARC: 48.46 vs 96.7 (so35)-49.9%
HellaSwag: 71.58 vs 95.3 (gpt4)-24.9%
MMLU: 56.52 vs 88.3 (so35)-36%
TruthfulQA: 47.27 vs 59 (gpt4)-19.9%
WinoGrande: 66.22 vs 87.5 (gpt4)-24.3%
GSM8K: 52.24 vs 96.4 (so35)-45.8%
MATH Lvl 5: 5.29
LLME Score: 0.21347
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen1.5 4B (Qwen/Qwen1.5-4B)
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Qwen1.5 4B Parameters and Internals

Model Type 
transformer-based, decoder-only, language model
Additional Notes 
Significant improvements in the model include multilingual support and performance enhancements in chat models. It maintains stable support for 32K context length.
Supported Languages 
en (multilingual support)
LLM NameQwen1.5 4B
Repository 🤗https://huggingface.co/Qwen/Qwen1.5-4B 
Model Size4b
Required VRAM7.9 GB
Updated2026-04-03
MaintainerQwen
Model Typeqwen2
Model Files  4.0 GB: 1-of-2   3.9 GB: 2-of-2
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.37.0
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 Qwen/Qwen1.5-4B.

Rank the Qwen1.5 4B 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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