What are the hardware requirements for Qwen2.5 0.5B Instruct AWQ?

Qwen2.5 0.5B Instruct AWQ requires approximately 0.7 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2.5 0.5B Instruct AWQ and how large is it?

Qwen2.5 0.5B Instruct AWQ 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.

Where can I download or evaluate Qwen2.5 0.5B Instruct AWQ?

Qwen2.5 0.5B Instruct AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 0.5B Instruct AWQ by Qwen — VRAM 0.7GB, 32K context

Name: Qwen2.5 0.5B Instruct AWQ
Author: Qwen

Qwen2.5 0.5B Instruct AWQ is an open-source language model by Qwen. Features: 0.5b LLM, VRAM: 0.7GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.19.

Arxiv:2407.10671 4-bit Awq Base model:quantized:qwen/qwen... Base model:qwen/qwen2.5-0.5b-i... Chat Conversational En Endpoints compatible Instruct Quantized Qwen2 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct-AWQ

Qwen2.5 0.5B Instruct AWQ Parameters and Internals

Model Type

Causal Language Models

Additional Notes

Supports long-context input up to 128K tokens and can generate output up to 8K tokens. Multilingual support for over 29 languages.

Supported Languages

languages_supported (en), proficiency_level (English and Multilingual Support)

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:

apply_chat_template

Accepted Modalities:

text

Output Format:

text

LLM Name	Qwen2.5 0.5B Instruct AWQ
Repository 🤗	https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct-AWQ
Base Model(s)	Qwen/Qwen2.5-0.5B-Instruct Qwen/Qwen2.5-0.5B-Instruct
Model Size	0.5b
Required VRAM	0.7 GB
Updated	2026-07-24
Maintainer	Qwen
Model Type	qwen2
Instruction-Based	Yes
Model Files	0.7 GB
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.41.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	float16
Errors	replace

Rank the Qwen2.5 0.5B Instruct AWQ capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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

Best Alternatives to Qwen2.5 0.5B Instruct AWQ

Best Alternatives	Context / RAM	Downloads	Likes
...wen2.5 Coder 0.5B Instruct AWQ	32K / 0.7 GB	392	3
Qwen2 0.5B Instruct AWQ	32K / 0.7 GB	78	5
Pgabl Ft Nama Siswa	32K / 1 GB	253	0
Legal Rag Qwen Sft	32K / 1 GB	204	0
Atomight V2.2 UltraThink 0.5B	32K / 1 GB	54	1
...mmanuel Siagian Exp1 Lr2e5 R16	32K / 1 GB	11	0
BoyBarley Sparky	32K / 1 GB	17	0
...0.5B Instruct Unsloth Bnb 4bit	32K / 0.5 GB	35360	6
Qwen2.5 0.5B Instruct 4bit	32K / 0.3 GB	15769	7
Qwen2.5 0.5B Instruct Bnb 4bit	32K / 0.5 GB	14598	4

Note: green Score (e.g. "73.2") means that the model is better than Qwen/Qwen2.5-0.5B-Instruct-AWQ.