How to Run YuE2 on an 8 GB GPU
In September 2026, YuE2 became the first local AI music model to outscore a flagship cloud service on a public benchmark. That made a lot of people want to run it. Then they read the system requirements: Linux, Python 3.12, and an NVIDIA GPU with 24 GB of VRAM.
Twenty-four gigabytes. That's an RTX 3090, 4090, or a professional workstation card. The overwhelming majority of gaming PCs, even good ones, have 8 to 16 GB of video memory. For most people, the best local music model in the world may as well not exist.
This guide covers what the official requirement actually means, and how Song Creator Pro became one of the first apps anywhere to run the full YuE2 model on ordinary 8 GB NVIDIA cards, on Windows, with no command line involved.
Why YuE2 Is Worth the Trouble
A quick recap of why this model is worth running at all:
- On the WildSongBench benchmark, YuE2 scored 6.96 keeping the best of eight generations and 6.73 in its standard mode, which keeps the better of two takes. Suno's current v6 scores 6.56 with that same treatment. Every Suno model that scored higher has been retired.
- It plans each song as an editable musical score before rendering audio, so you can change the melody, chords, or lyrics and regenerate.
- It can cover existing songs in completely different styles while keeping the melody recognizable.
- It sings in English, Mandarin, and Japanese, and outputs 48kHz stereo.
For a complete overview of the model, see what YuE2 is. For the full comparison against Suno, see YuE2 vs. Suno.
What the Official Release Demands
The YuE2 repository is a research release, built by and for people with access to serious hardware. Running it as published means:
| Requirement | Official YuE2 release |
|---|---|
| Operating system | Linux |
| Environment | Python 3.12, manual setup |
| GPU | NVIDIA with 24 GB of VRAM |
| Interface | Command line |
The GPU line is the killer. Cards with 24 GB of VRAM start around the RTX 3090 and 4090, which sell for four figures and were never common outside enthusiast builds and workstations. Mainstream cards like the RTX 3060, 4060, and their Ti variants ship with 8 to 16 GB.
How Song Creator Pro Fits It into 8 GB
Song Creator Pro runs the full YuE2 model on NVIDIA GPUs with 8 GB of VRAM, with experimental support for AMD. It's among the first apps anywhere to manage this, and it gets there with a combination of techniques:
- Quantization. Model weights are stored and computed at reduced precision, cutting their memory footprint substantially with minimal effect on output quality.
- Memory offloading. Stages of the pipeline that aren't actively computing are moved out of VRAM and into system RAM, then brought back when needed.
- Optimized memory management. The pipeline is orchestrated so that peak VRAM usage stays within an 8 GB budget throughout generation.
Nothing is cut down to get there. Both YuE2 workflows are available: text-to-song, with score planning you can set to full, melody-only, or off, and Remix, which transcribes an existing song's lyrics (editable before you generate) and re-renders it in a new style. Batch generation works too, which matters because best-of-N is exactly the workflow that tops the benchmarks.
Have an 8 GB card? Song Creator Pro runs YuE2 on it, with unlimited generations and a free trial to test first.
What Hardware You Need
| Component | Requirement |
|---|---|
| GPU | NVIDIA with 8 GB+ of VRAM (RTX 3050 8 GB, 3060, 3060 Ti, 4060, or better); AMD with 8 GB+ is experimental |
| System RAM | 16 GB recommended (memory offloading uses system RAM) |
| OS | Windows |
If your card has less than 8 GB, or you'd rather not rely on experimental AMD support for YuE2, you're not locked out of the app: the ACE-Step 1.5 model runs on NVIDIA and AMD cards with 6 GB of VRAM, and can fall back to CPU-only generation (much slower). Our local AI music generator guide covers the full hardware picture for both models.
What to Expect
Honesty section: YuE2 is the heavier of Song Creator Pro's two models, and generation takes longer than with ACE-Step 1.5. How much longer depends on your card. The practical pattern most users settle into is queuing a batch of YuE2 candidates, letting them render, and picking the best take, the same best-of-N approach behind the model's top benchmark score. Since generation is local and unlimited, extra candidates cost nothing but time.
Getting Started
- Install Song Creator Pro from the Microsoft Store (free trial) or itch.io. The app handles model downloads and hardware detection itself.
- Select YuE2 as your model.
- Write a style description and lyrics, pick a planning mode, and generate. Or switch to Remix, drop in an existing song, describe the new style, and let it re-render.
To get the most out of your prompts, the YuE2 prompting guide covers the style tags, section labels, and lyric formatting the model responds to best.
Ready to run the benchmark leader on your own card? Two AI models including YuE2, unlimited generations, runs entirely on your Windows PC.
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Frequently Asked Questions
Not through the official release, which calls for an NVIDIA GPU with 24 GB of VRAM on Linux. Song Creator Pro is among the first apps to run the full YuE2 model on Windows with 8 GB NVIDIA GPUs (AMD support is experimental), using quantization and memory offloading to fit the pipeline into consumer hardware.
Any NVIDIA GPU with 8 GB of VRAM or more: an RTX 3050 8 GB, RTX 3060, RTX 3060 Ti, RTX 4060, or anything above those. AMD cards with 8 GB also work, though YuE2 support on AMD is experimental. Self-hosting the official release instead requires a 24 GB card such as an RTX 3090 or 4090.
Experimentally. Song Creator Pro supports NVIDIA and AMD GPUs, but AMD and CPU-only support for YuE2 is still experimental. The ACE-Step 1.5 model in the same app runs on AMD GPUs with 6 GB of VRAM or more, and can also run CPU-only (much slower) if you have no dedicated GPU at all.
No. Both YuE2 workflows are available: text-to-song with score planning, and Remix for restyling existing songs. Editable scores, editable lyric transcriptions in Remix, and batch generation all work the same way.