by ACE-Step
Open source · 48k downloads · 716 likes
ACE Step1.5 is an open-source, groundbreaking AI model designed for music generation, delivering professional-grade performance on consumer-grade hardware. It stands out for its ability to produce complete tracks in just seconds, even on modest GPUs, while ensuring secure commercial use thanks to training on legally compliant data. The model excels in precise stylistic control and offers advanced features like creating covers, modifying existing tracks, or converting vocals into music—all while adhering to prompts in over 50 languages. Its innovative architecture, combining a language-model-based planner and an optimized audio generator, enables unprecedented musical creativity tailored for artists, producers, and content creators. Unlike other solutions, it eliminates external biases through intrinsic reinforcement learning, delivering superior quality and reliability.
Project | Hugging Face | ModelScope | Space Demo | Discord Tech Report

🚀 ACE-Step v1.5 is a highly efficient open-source music foundation model designed to bring commercial-grade music generation to consumer hardware.
🌉 At its core lies a novel hybrid architecture where the Language Model (LM) functions as an omni-capable planner: it transforms simple user queries into comprehensive song blueprints—scaling from short loops to 10-minute compositions—while synthesizing metadata, lyrics, and captions via Chain-of-Thought to guide the Diffusion Transformer (DiT). ⚡ Uniquely, this alignment is achieved through intrinsic reinforcement learning relying solely on the model's internal mechanisms, thereby eliminating the biases inherent in external reward models or human preferences. 🎚️
🔮 Beyond standard synthesis, ACE-Step v1.5 unifies precise stylistic control with versatile editing capabilities—such as cover generation, repainting, and vocal-to-BGM conversion—while maintaining strict adherence to prompts across 50+ languages. This paves the way for powerful tools that seamlessly integrate into the creative workflows of music artists, producers, and content creators. 🎸



| DiT Model | Pre-Training | SFT | RL | CFG | Step | Refer audio | Text2Music | Cover | Repaint | Extract | Lego | Complete | Quality | Diversity | Fine-Tunability | Hugging Face |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
acestep-v15-base | ✅ | ❌ | ❌ | ✅ | 50 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | Medium | High | Easy | Link |
acestep-v15-sft | ✅ | ✅ | ❌ | ✅ | 50 | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ | High | Medium | Easy | Link |
acestep-v15-turbo | ✅ | ✅ | ❌ | ❌ | 8 | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ | Very High | Medium | Medium | Link |
acestep-v15-turbo-rl | ✅ | ✅ | ✅ | ❌ | 8 | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ | Very High | Medium | Medium | To be released |
| LM Model | Pretrain from | Pre-Training | SFT | RL | CoT metas | Query rewrite | Audio Understanding | Composition Capability | Copy Melody | Hugging Face |
|---|---|---|---|---|---|---|---|---|---|---|
acestep-5Hz-lm-0.6B | Qwen3-0.6B | ✅ | ✅ | ✅ | ✅ | ✅ | Medium | Medium | Weak | ✅ |
acestep-5Hz-lm-1.7B | Qwen3-1.7B | ✅ | ✅ | ✅ | ✅ | ✅ | Medium | Medium | Medium | ✅ |
acestep-5Hz-lm-4B | Qwen3-4B | ✅ | ✅ | ✅ | ✅ | ✅ | Strong | Strong | Strong | ✅ |
This project is co-led by ACE Studio and StepFun.
If you find this project useful for your research, please consider citing:
@misc{gong2026acestep,
title={ACE-Step 1.5: Pushing the Boundaries of Open-Source Music Generation},
author={Junmin Gong, Yulin Song, Wenxiao Zhao, Sen Wang, Shengyuan Xu, Jing Guo},
howpublished={\url{https://github.com/ace-step/ACE-Step-1.5}},
year={2026},
note={GitHub repository}
}