LLM EXPLORER 63,529 MODELS INDEXED

Qwen2.5 0.5B Instruct by Qwen

By Qwen · 6324790 downloads
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Qwen2.5 0.5B Instruct is an open-source language model by Qwen. Features: 0.5b LLM, VRAM: 1GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.31.

  Arxiv:2407.10671 Base model:finetune:qwen/qwen2...   Base model:qwen/qwen2.5-0.5b   Chat   Conversational   Deploy:azure   En   Endpoints compatible   Instruct   Qwen2   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct 

Qwen2.5 0.5B Instruct Parameters and Internals

Model Type 
Causal Language Model
Use Cases 
Areas:
Chat applications, Multilingual text generation
Applications:
Role-play chatbots, Long text generation
Primary Use Cases:
Coding, Mathematics
Limitations:
Limited understanding of unsupported languages
Supported Languages 
English (High), Chinese (High), French (Medium), Spanish (Medium), Portuguese (Medium), German (Medium), Italian (Medium), Russian (Medium), Japanese (Medium), Korean (Medium), Vietnamese (Medium), Thai (Medium), Arabic (Medium)
Training Details 
Methodology:
Pretraining & Post-training
Context Length:
32768
Model Architecture:
Transformers with RoPE, SwiGLU, RMSNorm, Attention QKV bias and tied word embeddings
Input Output 
Input Format:
Chat template with system and user roles
Accepted Modalities:
text
Output Format:
Text
Performance Tips:
Use the latest `transformers` library for optimal performance.
LLM NameQwen2.5 0.5B Instruct
Repository 🤗https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct 
Base Model(s)  Qwen/Qwen2.5-0.5B   Qwen/Qwen2.5-0.5B
Model Size0.5b
Required VRAM1 GB
Updated2026-08-03
MaintainerQwen
Model Typeqwen2
Instruction-BasedYes
Model Files  1.0 GB
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.43.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

Quantized Models of the Qwen2.5 0.5B Instruct

Model
Likes
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VRAM
Math Slm Qwen2.5 0.5B V419810 GB
Soulbox Cbt Therapy 0.5B0810 GB
Flowscribe Qwen2.5 0.5B V20550 GB
...0.5B Instruct Unsloth Bnb 4bit6327280 GB
Qwen2.5 0.5B Instruct AWQ11220400 GB
Qwen2.5 0.5B Instruct Bnb 4bit4145980 GB
...wen2.5 0.5B Instruct GPTQ Int4919010 GB
...wen2.5 0.5B Instruct GPTQ Int8105590 GB

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Context / RAM
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Qwen2 0.5B Abyme Merge3128K / 1.3 GB321
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Note: green Score (e.g. "73.2") means that the model is better than Qwen/Qwen2.5-0.5B-Instruct.