What are the hardware requirements for Qwen3 4B AWQ?

Qwen3 4B AWQ requires approximately 2.7 GB of VRAM and supports a context window of 40K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3 4B AWQ and how large is it?

Qwen3 4B AWQ is developed by Qwen, a model with 4b 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 Qwen3 4B AWQ?

Qwen3 4B AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3 4B AWQ by Qwen — VRAM 2.7GB, 40K context

Name: Qwen3 4B AWQ
Author: Qwen

Qwen3 4B AWQ is an open-source language model by Qwen. Features: 4b LLM, VRAM: 2.7GB, Context: 40K, License: apache-2.0, Quantized, LLM Explorer Score: 0.27.

Arxiv:2309.00071 Arxiv:2505.09388 4-bit Awq Base model:quantized:qwen/qwen... Base model:qwen/qwen3-4b Conversational Endpoints compatible Quantized Qwen3 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen3-4B-AWQ

Qwen3 4B AWQ Parameters and Internals

LLM Name	Qwen3 4B AWQ
Repository 🤗	https://huggingface.co/Qwen/Qwen3-4B-AWQ
Base Model(s)	Qwen/Qwen3-4B Qwen/Qwen3-4B
Model Size	4b
Required VRAM	2.7 GB
Updated	2026-08-05
Maintainer	Qwen
Model Type	qwen3
Model Files	2.7 GB
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	40960
Model Max Length	40960
Transformers Version	4.51.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	float16
Errors	replace

Rank the Qwen3 4B AWQ 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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