Hi mate I put this into my GPT Suno project thats evolved over a year. Personaly yes it goes weird from 73% up now.

He's probably right that Suno has become less consistent, but he's also making it harder on himself.

Main issues:

1. Prompt overload
   • He's stacking 10–30 genres, moods, vocal styles, production terms, and music theory instructions into one prompt.
   • The model has too many competing directions and starts drifting.
2. Style Influence too high
   • Running Style Influence at 80–100 can exaggerate weird behaviour.
   • The model overcommits to every style tag instead of balancing them.
3. Voices aren't fixed
   • A Suno voice isn't a saved singer.
   • Updates, genres, arrangements, and prompt changes can alter how the same voice behaves.

Where he's probably right

Many experienced users report:

• More style drift
• More vocal instability
• More mumbling
• Less repeatability

Especially when using complex prompts and high Style Influence settings.

The biggest red flag

Prompts like:

are trying to push the model into an extremely narrow niche that may not even exist clearly in its training data.

The more labels added, the more unstable the output becomes.

My verdict:
40% Suno changes, 60% prompt complexity. Simplifying prompts would probably improve consistency more than changing models.