ACE-Step 1.5▌
ACE-Step 1.5 is a highly efficient open-source music foundation model that delivers commercial-grade music generation on consumer hardware. It supports lightweight personalization and runs locally with less than 4GB of VRAM.
Details
- organization
- ACE Music
- license
- MIT
- website
- https://acemusic.ai
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About this listing
ACE-Step 1.5 is in the explainx.ai LLM directory. ACE-Step 1.5 is a highly efficient open-source music foundation model that delivers commercial-grade music generation on consumer hardware. It supports lightweight personalization and runs locally with less than 4GB of VRAM.. It is labeled open-weights / public artifacts, with publisher field ACE Music and license MIT. Structured FAQs below clarify source, weights, and benchmark data. Canonical URL: /llms/ace-step-1-5.
FAQ
- What is ACE-Step 1.5?
- ACE-Step 1.5 — ACE-Step 1.5 is a highly efficient open-source music foundation model that delivers commercial-grade music generation on consumer hardware. It supports lightweight personalization and runs locally with less than 4GB of VRAM. It appears in the explainx.ai LLM marketplace as a discoverability aid. Reported specs on explainx.ai include type: generative-media; scale: 4B. Links and license data should be verified with the publisher before production use.
- Who created or publishes ACE-Step 1.5?
- On this listing, the organization or lab field is “ACE Music” (sourced from the directory import or editor). That usually matches the publisher; confirm on the official model card or vendor site.
- Is ACE-Step 1.5 open source or closed source?
- The listing is categorized as open-weights or publicly downloadable where the publisher allows it; the recorded license is “MIT”. Closed or gated releases can still appear on Hugging Face—always read the license on the publisher’s page.
- Where can I download weights or find model files for ACE-Step 1.5?
- A weights or artifact URL is linked on this profile (https://github.com/ACE-Step/ACE-Step-1.5). Always confirm license and terms on the publisher’s site before downloading or deploying.
- What do Arena leaderboard numbers mean for ACE-Step 1.5?
- This profile does not include Arena benchmark rows yet. You can still use organization, license, and outbound links to evaluate the model.
- Is explainx.ai the publisher of this model?
- No. explainx.ai hosts directory listings for discovery. The publisher is the organization or project behind the linked Hugging Face repo, API, or website. Pricing, safety, and terms are always set by that publisher.
- How does this page help AI search visibility?
- Structured FAQs, FAQPage JSON-LD, breadcrumbs, and answer-first copy follow SEO and GEO (Generative Engine Optimization) practices so search engines and citation-style assistants can summarize this listing accurately.
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Readme
We present ACE-Step v1.5, a highly efficient open-source music foundation model that brings commercial-grade generation to consumer hardware. On commonly used evaluation metrics, ACE-Step v1.5 achieves quality beyond most commercial music models while remaining extremely fast—under 2 seconds per full song on an A100 and under 10 seconds on an RTX 3090. The model runs locally with less than 4GB of VRAM, and supports lightweight personalization: users can train a LoRA from just a few songs to capture their own style.
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.
Listing on explainx.ai. Information may change; verify with the publisher.