ACE-Step

ACE-Step is a foundation model for music generation developed by ACE Studio and StepFun. It uses diffusion-based generation with a Deep Compression AutoEncoder (DCAE) and a lightweight linear transformer to achieve state-of-the-art speed and musical coherence.

Model Variants

ACE-Step (3.5B)

3.5B parameter diffusion model
DCAE encoder with linear transformer conditioning
27 or 60 inference steps recommended
Apache 2.0 license

Key Features

15x faster than LLM-based baselines (20 seconds for a 4-minute song on A100)
Full-song generation with lyrics and structure
Duration control for variable-length output
Music remixing and style transfer
Lyrics editing and vocal synthesis
Supports 16+ languages including English, Chinese, Japanese, Korean, French, German, Spanish, and more
Text-to-music from natural language descriptions

Hardware Requirements

RTX 3090: 12.76x real-time factor at 27 steps
RTX 4090: 34.48x real-time factor at 27 steps
NVIDIA A100: 27.27x real-time factor at 27 steps
Apple M2 Max: 2.27x real-time factor at 27 steps
Higher step counts (60) reduce speed by roughly half

Common Use Cases

Original music generation from text descriptions
Song remixing and style transfer
Lyrics-based music creation
Multi-language vocal music generation
Rapid music prototyping for content creators
Background music and soundtrack generation

Key Parameters

steps: Inference steps (27 for speed, 60 for quality)
duration: Target audio length in seconds (up to ~5 minutes)
lyrics: Song lyrics text input for vocal generation
prompt: Natural language description of desired music style and mood
seed: Random seed for reproducible generation (results are seed-sensitive)

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