AI music exports often fail for predictable reasons. Naming the problem keeps you from treating every issue as a mastering problem or regenerating tracks that only need a controlled finish.
Quick answer
Regenerate or rewrite when the performance, lyrics, or arrangement are broken. Master when the song works but tone, dynamics, stereo translation, or peaks need control. Stem-aware processing helps when vocal and instrumental problems need different treatment. Planetary Suno AI Mastering is built around these common AI-export artifacts.
Artifact map
Harsh or fizzy highs
What you hear: tiring cymbals, sibilant vocals, glassy top end.
Usually: generation EQ and harmonic content stacking in the upper band.
Try first: softer style prompt language; reduce bright descriptors; de-ess in a DAW if you have one.
Mastering role: gentle high-shelf or dynamic high-frequency control without dulling air completely.
Muddy low mids
What you hear: boxy vocals, unclear kick and bass, small-speaker mess.
Usually: stacked mid-bass energy from multiple generated layers.
Try first: simpler arrangement language in the style prompt; fewer simultaneous low instruments.
Mastering role: controlled low-mid cleanup and bass focus so the track translates on phones.
Soft or smeared drums
What you hear: kicks and snares that lack attack.
Usually: generation and heavy limiting in the source.
Try first: regenerate with clearer drum direction; avoid already-smashed references in the prompt.
Mastering role: careful transient emphasis and section balance—not infinite clipper gain.
Synthetic or watery vocals
What you hear: digital sheen, unstable consonants, phasey doubles.
Usually: model vocal artifacts and imperfect stem separation.
Try first: clearer vocal tags and lyric structure; see Suno meta tags.
Mastering role: de-essing, gentle resonance control; Ultra-style stem splits only when the split is clean enough to help.
Section loudness jumps
What you hear: quiet verse, exploding chorus, or the reverse.
Usually: arrangement dynamics without gain riding.
Try first: rewrite arrangement cues; regenerate unbalanced sections when possible.
Mastering role: section leveling and controlled compression so the story stays intact.
Narrow or unstable stereo
What you hear: mono collapse, sides that disappear, or wide but hollow mixes.
Usually: generated width tricks that fail on mono systems.
Mastering role: safe width, mono checks, and leaving the center solid.
Already clipped source
What you hear: hard distortion on peaks before you touch a limiter.
Action: do not add more limiting. Fix or re-export the source. Mastering cannot un-clip printed distortion.
Decision tree
- Is the lyric or performance wrong? → rewrite / regenerate
- Is the arrangement unfinished? → structure and prompt work first
- Is the source clipped or collapsed? → new export
- Does the song work but sound fatiguing or uneven? → mastering
- Do vocal and instrumental problems need opposite treatments? → consider stem-aware mastering
How this maps to Planetary tools
- Diagnosis and DIY path: How to master a Suno song for release
- Managed finish: Suno AI Mastering (Standard full-mix; Ultra separates voice and music when appropriate)
- Writing and structure: prompt and lyric guide, meta tags
- Full release path: Suno to Spotify checklist
Truth notes
Platform loudness targets are approximate playback-normalization references. They are not a single number you must hit for upload. Master for the song and leave headroom for encoding.
No mastering service can guarantee chart placement or streams. Honest finishing improves translation and fatigue; it does not replace songwriting and promotion.