acestep-v15-base
Will it run on your hardware?
Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest
Need an exact figure for your context length? Use the VRAM calculator.
Run it locally
Copy-paste - running in under a minute
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Deep dive
Notes, sources, and the full write-up
acestep-v15-base is an open-weight audio and music generation model from ACE-Step, published on Hugging Face in January 2026. It has 2.4B parameters and is released under the mit license.
HardwareLink to this section
At full FP16 precision the weights need about 5 GB of memory; 8-bit quantization brings that to roughly 3 GB. Check the VRAM tiers above to see which GPUs fit it.
PopularityLink to this section
acestep-v15-base had 5,974 downloads on Hugging Face in the last month and has 71 likes.
Run it locallyLink to this section
The weights are on Hugging Face and load with Hugging Face Transformers. Follow the model card for the exact setup and license terms.
Frequently asked
Quick answers to common questions
How much VRAM does acestep-v15-base need?
acestep-v15-base with 2.4B parameters needs approximately 1 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.
Is acestep-v15-base better than other ACE-Step models?
acestep-v15-base has 2.4B parameters with 32,768 context - a strong choice for audio-generation, music-generation.
What license is acestep-v15-base under?
acestep-v15-base is released under the mit license, making it suitable for most commercial and personal projects.
What hardware runs acestep-v15-base well?
With 2.4B parameters, acestep-v15-base requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.
What is the best quantization for acestep-v15-base?
Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~2 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.
How long can acestep-v15-base's context window handle?
acestep-v15-base supports a 32,768-token context window - enough for most medium-length documents and conversations. Real-world usable context may vary by implementation.
What models compete with acestep-v15-base?
acestep-v15-base competes with other models in its class. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.
Nearby options
Similar models and compatible hardware by spec