Model reference · open weights
YuE-s1-anneal-en-cot is an open-weight language model from m-a-p. YuE-s1-7B-anneal-en-cot (BF16) weighs 12.4 GB; the smallest configuration that runs it is RTX 4060 Ti 16 GB.
For self-hosting, compare this build's requirements below with the GPU you plan to rent.
Summary of the m-a-p/YuE-s1-7B-anneal-en-cot model card, 2026-10-01
What it is
| Released by | m-a-p |
|---|---|
| Released | 2025-01-26 |
| Parameters | 6.2B |
| VRAM | 12.4 GB for the weights |
What it runs on
| Card | Requests at once | Context max | Memory |
|---|---|---|---|
| 8K each | |||
| RTX 3060 12 GB | 11.6 GB | ||
| RTX 4060 Ti 16 GB | 4 | all 16K | 15.4 GB |
| RTX 3090 24 GB | 19 | all 16K | 23.4 GB |
| RTX 4090 24 GB | 19 | all 16K | 23.4 GB |
| RTX 5090 32 GB | 33 | all 16K | 31.0 GB |
| L40S 48 GB | 57 | all 16K | 44.0 GB |
| A100 80 GB | 121 | all 16K | 78.2 GB |
| H100 80 GB | 114 | all 16K | 78.1 GB |
| RTX PRO 6000 Blackwell 96 GB | 143 | all 16K | 93.8 GB |
| DGX Spark (GB10) 128 GB unified | 168 | all 16K | 107 GB |
| H200 141 GB | 225 | all 16K | 138 GB |
| B200 180 GB | 296 | all 16K | 176 GB |
| 2× RTX 3060 12 GB tensor parallel | 17 | all 16K | 11.6 GB a card |
| 2× RTX 4060 Ti 16 GB tensor parallel | 31 | all 16K | 15.4 GB a card |
| Requests at once | 8K tokens each |
|---|---|
| 1 | 13.7 GB |
| 5 | 15.8 GB |
| 8 | 17.4 GB |
| 16 | 21.7 GB |
| 32 | 30.3 GB |
| 64 | 47.5 GB |
One card, with vLLM's small-card settings.
From the model card
Our model's name is YuE (乐). In Chinese, the word means "music" and "happiness." Some of you may find words that start with Yu hard to pronounce. If so, you can just call it "yeah." We wrote a song with our model's name.
YuE is a groundbreaking series of open-source foundation models designed for music generation, specifically for transforming lyrics into full songs (lyrics2song). It can generate a complete song, lasting several minutes, that includes both a catchy vocal track and accompaniment track. YuE is capable of modeling diverse genres/languages/vocal techniques. Please visit the Demo Page for amazing vocal performance.
Pop:Quiet Evening Metal: Step Back
2025.03.12 🔥 Paper Released🎉: We now release YuE technical report!!! We discuss all the technical details, findings, and lessons learned. Enjoy, and feel free to cite us~
2025.03.11 🫶 Now YuE supports incremental song generation!!! See YuE-UI by joeljuvel. YuE-UI is a Gradio-based interface supporting batch generation, output selection, and continuation. You can flexibly experiment with audio prompts and different model settings, visualize your progress on an interactive timeline, rewind actions, quickly preview audio outputs at stage 1 before committing to refinement, and fully save/load your sessions (JSON format). Optimized to run smoothly even on GPUs with just 8GB VRAM using quantized models.
2025.02.17 🫶 Now YuE supports music continuation and Google Colab! See YuE-extend by Mozer.
2025.02.07 🎉 Get YuE for Windows on pinokio.
2025.01.30 🔥 Inference Update: We now support dual-track ICL mode! You can prompt the model with a reference song, and it will generate a new song in a similar style (voice cloning demo by @abrakjamson, music style transfer demo by @cocktailpeanut, etc.). Try it out! 🔥🔥🔥 P.S. Be sure to check out the demos first—they're truly impressive.
2025.01.30 🔥 Announcement: A New Era Under Apache 2.0 🔥: We are thrilled to announce that, in response to overwhelming requests from our community, YuE is now officially licensed under the Apache 2.0 license. We sincerely hope this marks a watershed moment—akin to what Stable Diffusion and LLaMA have achieved in their respective fields—for music generation and creative AI. 🎉🎉🎉
2025.01.29 🎉: We have updated the license description. we ENCOURAGE artists and content creators to sample and incorporate outputs generated by our model into their own works, and even monetize them. The only requirement is to credit our name: YuE by HKUST/M-A-P (alphabetic order).
2025.01.28 🫶: Thanks to Fahd for creating a tutorial on how to quickly get started with YuE. Here is his demonstration.
2025.01.26 🔥: We have released the YuE series.
Please check our github for easy quickstart.
The project is co-lead by HKUST and M-A-P (alphabetic order). Also thanks moonshot.ai, bytedance, 01.ai, and geely for supporting the project. A friendly link to HKUST Audio group's huggingface space.
We deeply appreciate all the support we received along the way. Long live open-source AI!
If you find our paper and code useful in your research, please consider giving a star :star: and citation :pencil: :)
@misc{yuan2025yuescalingopenfoundation,
title={YuE: Scaling Open Foundation Models for Long-Form Music Generation},
author={Ruibin Yuan and Hanfeng Lin and Shuyue Guo and Ge Zhang and Jiahao Pan and Yongyi Zang and Haohe Liu and Yiming Liang and Wenye Ma and Xingjian Du and Xinrun Du and Zhen Ye and Tianyu Zheng and Yinghao Ma and Minghao Liu and Zeyue Tian and Ziya Zhou and Liumeng Xue and Xingwei Qu and Yizhi Li and Shangda Wu and Tianhao Shen and Ziyang Ma and Jun Zhan and Chunhui Wang and Yatian Wang and Xiaowei Chi and Xinyue Zhang and Zhenzhu Yang and Xiangzhou Wang and Shansong Liu and Lingrui Mei and Peng Li and Junjie Wang and Jianwei YuQuoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.