Model reference · open weights

AuK-Flash

Audio tencent Text→speech 1 build Open weights 129 dl/mo

AuK-Flash is an open-weight audio or speech model from tencent. AuK-Flash (BF16) weighs 6.8 GB; the smallest configuration that runs it is RTX 3060 12 GB.

For self-hosting, compare this build's requirements below with the GPU you plan to rent.

  • AuK-Flash is a 1.5B parameter speech generation and editing model developed by Tencent.
  • It is a distilled variant of the AuK foundation model designed for fast 4-step inference, supporting tasks such as zero-shot text-to-speech, content editing, and speech enhancement via a natural-language interface.
  • The model supports Chinese and English and is released under the MIT license.

Summary of the tencent/AuK-Flash model card, 2026-10-01

What it is

Released bytencent
Released2026-08-21
VRAM6.8 GB for the weights

What it runs on

Memory and cards for AuK-Flash (BF16)

6.8 GBweights, file size
1.6 GBruntime overhead
CardOne streamMemory
RTX 3060 12 GBfits11.6 GB
RTX 4060 Ti 16 GBfits15.4 GB
RTX 3090 24 GBfits23.4 GB
RTX 4090 24 GBfits23.4 GB
RTX 5090 32 GBfits31.0 GB
L40S 48 GBfits44.0 GB
A100 80 GBfits78.2 GB
H100 80 GBfits78.1 GB
RTX PRO 6000 Blackwell 96 GBfits93.8 GB
DGX Spark (GB10) 128 GB unifiedfits107 GB
H200 141 GBfits138 GB
B200 180 GBfits176 GB

From the model card

What tencent says about AuK-Flash

Read the model card

News

Contents

Introduction

AuK is a 1.5B foundation model for speech generation and editing. Trained on millions of hours of diverse audio data, AuK supports zero-shot and instruction-based TTS, content and acoustic editing, paralinguistic editing, speech enhancement, and source separation through a unified natural-language instruction interface. AuK has two variants:

ModelDescriptionWeight
AuKBase model for high-quality generation🤗 Hugging Face · 🤖 ModelScope
AuK-FlashDistilled model for fast 4-step inference🤗 Hugging Face · 🤖 ModelScope

This repository contains the official weights for AuK-Flash, the distilled variant with fast 4-step inference.

Performance

Model Architecture

Supported Tasks

AuK exposes every task through the same natural-language instruction interface. The table below groups the supported tasks by category, with a short description and a link to its section in the Cookbook, which provides instruction templates plus CLI and Python examples.

Download the weights

🤗 HuggingFace

pip install -U "huggingface_hub[cli]"

# AuK-Base
hf download tencent/AuK --local-dir ./ckpts/AuK

# AuK-Flash (4-step distilled)
hf download tencent/AuK-Flash --local-dir ./ckpts/AuK-Flash

# MLLM Encoder
hf download Qwen/Qwen2.5-Omni-3B  --local-dir ./ckpts/Qwen2.5-Omni-3B

🤖 ModelScope

pip install -U modelscope

# AuK-Base
modelscope download --model Tencent-Hunyuan/AuK --local_dir ./ckpts/AuK

# AuK-Flash (4-step distilled)
modelscope download --model Tencent-Hunyuan/AuK-Flash  --local_dir ./ckpts/AuK-Flash

# MLLM Encoder
modelscope download --model Qwen/Qwen2.5-Omni-3B --local_dir ./ckpts/Qwen2.5-Omni-3B

The expected directory structure is:

ckpts/
├── AuK/
├── AuK-Flash/          # optional
└── Qwen2.5-Omni-3B/

The model checkpoint contains the diffusion transformer and layer-fusion weights. The MLLM encoder and VAE are loaded from separate files at runtime, so missing text_encoder.* keys during checkpoint loading are expected.

For installation, inference, Gradio, ComfyUI, and fine-tuning, see the GitHub README and Cookbook.

Citation

Research using AuK can cite the following entry:

@misc{ma2026auktechnicalreportopensource,
  title={AuK Technical Report: An Open-Source Foundational Model for Speech Generation and Editing},
  author={Ziyang Ma and Zhikang Niu and Wenming Tu and Tianrui Wang and Ruiqi Yan and Junxi Liu and Yanru Huo and Nickk Huang and Yang Liu and Qicong Xie and Zeyu Xie and Hui Wang and Haitao Li and Zixuan Jiang and Yalin Li and Jie Fang and Yifan Duan and Zeyue Tian and Guangzheng Li and Haina Zhu and Shuyi Wang and Jinwen Wang and Mingyu Cui and Tian Tan and Auden and Sen Liang and Steve Yves and Shan Yang and Liefeng Bo and Zilong Zheng and Kai Yu and Eng-Siong Chng and Xie Chen},
  year={2026},
  eprint={2609.08936},
  archivePrefix={arXiv},
  primaryClass={cs.SD},
  url={https://arxiv.org/abs/2609.08936},
}

License

AuK is released under the MIT License. See LICENSE for the full terms.

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

How it works

How audio & music work

Audio or textinputAudio modelrecognise / synthesiseText or audiooutputSpeech-to-text turns audio into text; text-to-speech and music models turn text into audio.
© 2026 AxForge · EU-hosted AI infrastructure Pricing Docs Trust Privacy Terms