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HomeLLMsAce Step1.5

Ace Step1.5

by ACE-Step

Open source · 48k downloads · 716 likes

3.6
(716 reviews)AudioAPI & Local
About

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.

Documentation

ACE-Step 1.5

Pushing the Boundaries of Open-Source Music Generation

Project | Hugging Face | ModelScope | Space Demo | Discord Tech Report

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Model Details

🚀 ACE-Step v1.5 is a highly efficient open-source music foundation model designed to bring commercial-grade music generation to consumer hardware.

Key Features

  • 💰 Commercial-Ready: Unlike many models trained on ambiguous datasets, ACE-Step v1.5 is designed for creators. You can strictly use the generated music for commercial purposes.
  • 📚 Safe & Robust Training Data: The model is trained on a massive, legally compliant dataset consisting of:
    • Licensed Data: Professionally licensed music tracks.
    • Royalty-Free / No-Copyright Data: A vast collection of public domain and royalty-free music.
    • Synthetic Data: High-quality audio generated via advanced MIDI-to-Audio conversion.
  • ⚡ Extreme Speed: Generates a full song in under 2 seconds on an A100 and under 10 seconds on an RTX 3090.
  • 🖥️ Consumer Hardware Friendly: Runs locally with less than 4GB of VRAM.

Technical Capabilities

🌉 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. 🎸

  • Developed by: [ACE-STEP]
  • Model type: [Text2Music]
  • Language(s): [50+ languages]
  • License: [MIT]

Evaluation

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🏗️ Architecture

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🦁 Model Zoo

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DiT Models

DiT ModelPre-TrainingSFTRLCFGStepRefer audioText2MusicCoverRepaintExtractLegoCompleteQualityDiversityFine-TunabilityHugging Face
acestep-v15-base✅❌❌✅50✅✅✅✅✅✅✅MediumHighEasyLink
acestep-v15-sft✅✅❌✅50✅✅✅✅❌❌❌HighMediumEasyLink
acestep-v15-turbo✅✅❌❌8✅✅✅✅❌❌❌Very HighMediumMediumLink
acestep-v15-turbo-rl✅✅✅❌8✅✅✅✅❌❌❌Very HighMediumMediumTo be released

LM Models

LM ModelPretrain fromPre-TrainingSFTRLCoT metasQuery rewriteAudio UnderstandingComposition CapabilityCopy MelodyHugging Face
acestep-5Hz-lm-0.6BQwen3-0.6B✅✅✅✅✅MediumMediumWeak✅
acestep-5Hz-lm-1.7BQwen3-1.7B✅✅✅✅✅MediumMediumMedium✅
acestep-5Hz-lm-4BQwen3-4B✅✅✅✅✅StrongStrongStrong✅

🙏 Acknowledgements

This project is co-led by ACE Studio and StepFun.

📖 Citation

If you find this project useful for your research, please consider citing:

BibTeX
@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}
}
Capabilities & Tags
transformersdiffuserssafetensorsacestepfeature-extractionaudiomusictext2musictext-to-audiocustom_code
Links & Resources
Specifications
CategoryAudio
AccessAPI & Local
LicenseOpen Source
PricingOpen Source
Rating
3.6

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