Qwen2-Audio-7B-Instruct by Qwen: Open-Weight Model

Runs On

What it takes to serve Qwen2-Audio-7B-Instruct (8.4B parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

Precision	Weights	Memory needed	Cheapest setup	Per hour	Also fits
16-bit	16.8 GB	20.2 GB	1x MI300X (192 GB) Vultr	$1.85	1x H100 $1.99 · 1x MI325X $2.00
8-bit	8.4 GB	10.1 GB	1x MI300X (192 GB) Vultr	$1.85	1x H100 $1.99 · 1x MI325X $2.00
4-bit	4.2 GB	5.0 GB	1x MI300X (192 GB) Vultr	$1.85	1x H100 $1.99 · 1x MI325X $2.00

Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Sep 18, 2026.

SAVRN's Notes on Qwen2-Audio-7B-Instruct

Audio in, text out, nothing else. Qwen2-Audio-7B-Instruct is the chat-tuned half of a pair; the publisher released a pretrained Qwen2-Audio-7B beside it. It carries 8.4 billion parameters and 16.8 GB of bfloat16 weights in 15 files. In use it needs 20.2 GB at 16-bit, 10.1 GB at 8-bit and 5.0 GB at 4-bit, so the whole thing lands on a single mid-size card, and the MI300X at $1.85 an hour that heads our cheapest-setup table is more machine than it needs.

Apache 2.0 allows commercial use, modification and redistribution, with the duty to keep the license, copyright and NOTICE files and state significant changes, plus a patent grant, so an audio analysis service built on it owes the publisher nothing further. The number to check is context: 8,192 tokens, which caps how much audio and conversation fit in one turn, even though the configuration also lists a 32,768 token sliding window. Released July 31, 2024, last touched January 12, 2025; the papers are arXiv:2407.10759 and arXiv:2311.07919.

SAVRN Research, 2026-09-18

Model Card

By Qwen, published under apache-2.0, revision 0a095220c30b.

Introduction

Qwen2-Audio is the new series of Qwen large audio-language models. Qwen2-Audio is capable of accepting various audio signal inputs and performing audio analysis or direct textual responses with regard to speech instructions. We introduce two distinct audio interaction modes:

voice chat: users can freely engage in voice interactions with Qwen2-Audio without text input;
audio analysis: users could provide audio and text instructions for analysis during the interaction;

We release Qwen2-Audio-7B and Qwen2-Audio-7B-Instruct, which are pretrained model and chat model respectively.

For more details, please refer to our Blog, GitHub, and Report.

Requirements

The code of Qwen2-Audio has been in the latest Hugging face transformers and we advise you to build from source with command pip install git+https://github.com/huggingface/transformers, or you might encounter the following error:

KeyError: 'qwen2-audio'

Quickstart

Read the full model card (736 words)

Configuration

Architecture: Qwen2AudioForConditionalGeneration
Context length (tokens): 8,192
Feed-forward size: 11,008
Vocabulary size: 156,032
Sliding window (tokens): 32,768
RoPE base: 10,000
Stored precision: bfloat16
Model type: qwen2_audio

Identity and Version

Repository: Qwen/Qwen2-Audio-7B-Instruct
Publisher: Qwen
Task: Audio text to text
Modality: Other
Library: transformers
Parameters: 8.4B parameters
Languages: en
Revision: 0a095220c30b7b31434169c3086508ef3ea5bf0a
First published: 2024-07-31
Last updated: 2025-01-12

Files and Weights

15 files, 16.8 GB in total. The weights are 5 files totalling 16.8 GB in safetensors.

Weights5 files · 16.8 GB

Configuration4 files · 80.4 KB

Tokenizer4 files · 12.1 MB

Documentation1 file · 8.7 KB

Repository1 file · 1.5 KB

Every file

File	Type	Size	SHA-256
model-00001-of-00005.safetensors	Weights	3.9 GB	383de5b5b06f
model-00002-of-00005.safetensors	Weights	4.0 GB	610e59a23cdf
model-00003-of-00005.safetensors	Weights	4.0 GB	b9ea76e97226
model-00004-of-00005.safetensors	Weights	3.6 GB	d68dee591619
model-00005-of-00005.safetensors	Weights	1.3 GB	a447dab3e72f
config.json	Configuration	853 B	—
generation_config.json	Configuration	230 B	—
model.safetensors.index.json	Configuration	79.0 KB	—
preprocessor_config.json	Configuration	342 B	—
README.md	Documentation	8.7 KB	—
.gitattributes	Repository	1.5 KB	—
merges.txt	Tokenizer	1.7 MB	—
tokenizer.json	Tokenizer	7.0 MB	—
tokenizer_config.json	Tokenizer	638.3 KB	—
vocab.json	Tokenizer	2.8 MB	—

License and Download

License: apache-2.0
Access: Open weights, no gate
Download size: 16.8 GB

Download from Qwen

Released by Qwen through ModelScope. Read the license.

Built From

Described by arXiv:2311.07919
Described by arXiv:2407.10759

Memory Requirements

Precision	Weights in memory
As published	16.8 GB
16-bit	16.8 GB
8-bit	8.4 GB
4-bit	4.2 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About Qwen2-Audio-7B-Instruct

How much GPU memory does Qwen2-Audio-7B-Instruct need?

About 20.2 GB at 16-bit and 5 GB at 4-bit: the weights (8.4B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run Qwen2-Audio-7B-Instruct on?

At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

Can I use Qwen2-Audio-7B-Instruct commercially?

Yes. Qwen2-Audio-7B-Instruct is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.

What is Qwen2-Audio-7B-Instruct's context length?

8,192 tokens, from the maximum position embeddings in its published configuration.

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