What are the hardware requirements for Qwen2 0.5B?

Qwen2 0.5B requires approximately 1 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2 0.5B and how large is it?

Qwen2 0.5B is developed by Qwen, a model with 0.5b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Qwen2 0.5B perform on standard benchmarks?

Qwen2 0.5B has the following published scores: MMLU 45.17. Compare against reference models on this page or on the LLM Explorer leaderboards.

Qwen2 0.5B by Qwen — VRAM 1GB, 128K context

Name: Qwen2 0.5B
Rating: 3.14 (7 reviews)
Author: Qwen

Qwen2 0.5B is an open-source language model by Qwen. Features: 0.5b LLM, VRAM: 1GB, Context: 128K, License: apache-2.0, LLM Explorer Score: 0.29, Arc: 31.9, HellaSwag: 48.7, MMLU: 45.2, GSM8K: 35.7.

Conversational Deploy:azure En Endpoints compatible Eval-results Pretrained Qwen2 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen2-0.5B

Qwen2 0.5B Parameters and Internals

Model Type

text generation

LLM Name	Qwen2 0.5B
Repository 🤗	https://huggingface.co/Qwen/Qwen2-0.5B
Model Size	0.5b
Required VRAM	1 GB
Updated	2026-07-15
Maintainer	Qwen
Model Type	qwen2
Model Files	1.0 GB
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.40.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2 0.5B 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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