ACE Step – AI Model for Blazing-Fast, High-Quality Music Generation

ACE Step is a novel open-source foundation model for text-to-music generation jointly developed by ACE Studio and StepFun ([GitHub][1]). At its core, ace step integrates diffusion-based generation with a Deep Compression Autoencoder (DCAE) and a lightweight linear transformer to bridge the gap between speed, coherence, and controllability in AI music models ([Hugging Face][2]). Unlike LLM-based approaches that excel at lyric alignment but suffer from slow inference, ace step achieves full-song synthesis of up to four minutes in just 20 seconds on an A100 GPU, making it roughly 15× faster than traditional baselines ([Hugging Face][2]).

By preserving fine-grained acoustic details and supporting natural-language descriptions, ace step enables creators to generate, remix, and edit music across genres—everything from mellow jazz tunes to energetic electronic tracks—without sacrificing quality or speed ([Medium][3]). Released under the Apache-2.0 license, ace step is free for commercial use and invites contributions from the open-source community to extend its capabilities through techniques like LoRA and ControlNet ([blog.comfy.org][4]).