ACE Step

What if music generation could be as fast and flexible as Stable Diffusion, but for sound?

RecommendedACE-Step is a groundbreaking open-source music foundation model that delivers exceptional speed and quality, offering a flexible platform for music creation and AI research.

ACE-Step is an open-source foundation model for music generation that integrates diffusion-based generation with Sana's Deep Compression AutoEncoder (DCAE) and a lightweight linear transformer. It aims to bridge the gap between generation speed, musical coherence, and controllability, offering a fast, general-purpose, and efficient architecture for music AI. The latest version, ACE-Step v1.5, pushes boundaries by bringing commercial-grade generation to consumer hardware with high efficiency and support for lightweight personalization.

Visit ACE Step

Visit ACE Step

Key Features:

State-of-the-art music generation quality with superior musical coherence and lyric alignment.
High generation speed: up to 4 minutes of music in 20 seconds on an A100 GPU (v1.0), under 2 seconds on A100 (v1.5).
Advanced control mechanisms: voice cloning, lyric editing, remixing, track generation (lyric2vocal, singing2accompaniment).
Open-source foundation model with a novel hybrid architecture (LM as planner, Diffusion Transformer).
Supports lightweight personalization (LoRA training from a few songs) and runs locally with low VRAM (under 4GB for v1.5).

Pros

Music artists and producers looking for a fast and controllable music generation tool.
Content creators needing quick and high-quality background music or sound effects.
Developers and researchers interested in an open-source, efficient, and flexible music AI foundation model.

Cons

Requires some technical setup for local deployment, especially for the open-source model.
While fast, performance can vary based on hardware (e.g., A100 vs. RTX 3090).
The model is still under active development, with new features and improvements continuously being released.

Pricing

open_sourceFree tier

Starting at:free

Free tier:Open-source music generation model with linked GitHub, Hugging Face model, paper, and demo resources.

Price verified on the live site 2026-07-12 · pricing page

Categories:

Audio & Speech AI Infrastructure

Tags:

music generation AI open-source foundation model diffusion audio lyrics vocal instrumental

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Quick Decision

Try if: You are a music creator or developer looking for a powerful, fast, and open-source music generation tool with advanced control and personalization capabilities, especially if you have access to a capable GPU.

Skip if: You prefer a fully managed, no-setup required music generation service, or if you are not comfortable with local model deployment and potential technical configurations.

Not for: Users who prefer a fully managed, cloud-based music generation service without local setup.; Those seeking a simple, one-click music generator without any technical involvement.

Trust Signals

Team Size
small

Tech Details

Platforms

webapi

AI Model
Diffusion-based generation with Sana's Deep Compression AutoEncoder (DCAE) and a lightweight linear transformer (v1.0); Hybrid architecture with Language Model as planner and Diffusion Transformer (DiT) (v1.5).

Open Source

Yes

Support

Company

Name
ACE Studio

ACE Studio is involved in the development of ACE-Step, an open-source foundation model for music generation.

FAQ

What is ACE-Step and how does it differ from other music generation models?

ACE-Step is an open-source foundation model for music generation that combines diffusion-based generation with a Deep Compression AutoEncoder and a lightweight linear transformer. It differentiates itself by offering superior speed (up to 15x faster than LLM-based models) and state-of-the-art quality in musical coherence and lyric alignment, addressing limitations of existing approaches.

Can ACE-Step be used on consumer-grade hardware?

Yes, ACE-Step v1.5 is designed to bring commercial-grade generation to consumer hardware. It can run locally with less than 4GB of VRAM and generate a full song in under 10 seconds on an RTX 3090 GPU.

What kind of control and customization options does ACE-Step offer?

ACE-Step provides advanced control mechanisms including voice cloning, lyric editing, remixing, and track generation (e.g., lyric2vocal, singing2accompaniment). ACE-Step v1.5 also supports lightweight personalization, allowing users to train a LoRA from just a few songs to capture their own style.

Use Cases

Music artists and producers looking for a fast and controllable music generation tool.
Content creators needing quick and high-quality background music or sound effects.
Developers and researchers interested in an open-source, efficient, and flexible music AI foundation model.