
Minimax Music vs Acestep?
I’ve been working with Acestep for a long time for almost everything music-related. Over the years I’ve had my share of bugs, happy accidents, and some really unexpected magic. I started training my own loras 6 months ago using my original tracks (I’ve been making music for about 30 years), raw sounds from my hardware synths (Matrixbrute, Korg MS-2000), and piano recordings played by my son. I literally discovered what it was really capable of from that point.
Yesterday I learned about the release of a new music model and I asked OBO, my local AI “agent”, to install the Minimax Music workflow so I could run some tests with some prompts and a few lyrics in several languages, following the way I taught it to create them (some occasional weirdness included). The agent made every decision from the styles of the tracks to the video content (it created images, a few short clips and a script to assemble them with panning), all has been made autonomously and locally while I was sleeping.
I wouldn’t say Minimax is clearly better or worse than Acestep. With my custom loras, Acestep still sounds amazing to me and feels very personal. But some of the results I got from the base Minimax model were surprisingly impressive: very clean sound, some tracks had structural issues, track building could be smarter (SFT version?) but some tracks were definitely sounding good and different than the usual Acestep ones.
If you’re curious to hear what Minimax did for me with my prompts, here’s a video with a few examples (nothing commercial, just tests, some bad, some good, the sound is as it was generated, no postprocessing):
I’m really looking forward to training Minimax on my own material to see how far it can go and how it can be improved further.
Has anyone here spent time with both Acestep and Minimax? I’d love to hear about:
Your impressions on sound quality and “feel” if you could compare.
Any resources for custom training / loras / fine-tuning for minimax?
Any tracks or demos you’ve made that you’re willing to share.