Rate my song
Drop your track for a 0-100 score
or click to browse · MP3, WAV, M4A
20 free credits
AI song rater for tracks you actually want to release.
Upload a track and get a 0–100 score, 3 concrete fixes, and a V2 comparison so you know if the next version improved.
You've already tried asking AI to rate your song.
Upload the same track to a general AI tool and you get a polite opinion. Rate My Song listens for the musical problems that actually change the score.
"Your song has excellent production quality! The mix sounds clean and professional with a good balance between instruments. I'd rate it an 8/10. The tempo feels like around 120 BPM and the key appears to be C major. Great work!"
Can't hear audio. Guessing from your text prompt. Actual BPM is 92, key is E minor.
"This is a really solid track! I'd give it a 78/100. The production is impressive, great stereo separation and the mix feels professional. The melody is catchy and the vocal sits nicely. Minor note: the bridge could use more dynamic contrast. Overall, great work!"
Can hear audio, but defaults to flattery. Same song, different prompt, different score every time.
63/100. Low-end buildup below 200Hz is masking the kick in the chorus. Vocal sits 2–3dB behind the synth lead from 1:42–2:18. Pre-chorus transition at 1:15 drops energy instead of building it. Hook melody resolves too early, payoff lands on beat 1 instead of sustaining through beat 2.
Analyzed from the actual waveform. Same file, same score, every time.
ChatGPT can't hear audio. It guesses BPM, key, and loudness from your text and gets them wrong. Gemini can listen, but defaults to flattery: everything scores 75–90 regardless of quality. Both are inconsistent. Same song, different prompt, different score. Neither remembers your previous versions.
Rate My Song AI runs your waveform through an ML pipeline trained on real music data. Same file, same score, every time. If the low-end is muddy or the hook is weak, it says so, because it's measuring, not generating a polite response.
How it works
Upload any song
Drag and drop an MP3, WAV, or M4A. Works with demos, finished masters, generator exports, and DAW bounces. If it is audio, it works.
Get your score in 30 seconds
Our ML pipeline analyzes the raw audio waveform, not metadata, not your filename, and returns a 0–100 score with a four-factor breakdown: Sound Quality, Hit Potential, Broad Appeal, and Overall.
See what to fix in the next version
AI feedback breaks your song into segments (intro, verse, chorus, bridge, outro) and gives you your top 3 prioritized fixes. Revise, re-upload, and watch the number move.
What you get back
0–100 Score: Is This Generation Worth Keeping?
One number that tells you where your track stands. The overall score combines four factors: Sound Quality measures production, mix, and mastering. Hit Potential evaluates catchiness and genre competitiveness. Broad Appeal scores how wide an audience your track could reach. Overall is the composite. Stop guessing whether generation 3 or generation 7 is better. Now you know.
Segment-by-Segment AI Feedback
Your song gets analyzed section by section. The AI listens to your intro, verses, choruses, bridge, and outro individually and tells you what's working and what isn't. You'll see specific observations about instrumentation, arrangement, vocal treatment, energy flow, and transitions, not generic platitudes. The feedback references actual timestamps so you can jump to the exact moment it's talking about.
Top 3 Fixes
After analyzing your track, the AI prioritizes the three changes that would have the biggest impact on your score. These aren't abstract suggestions like "improve the mix." They're concrete and actionable: tighten the low-end below 200 Hz, add a pre-chorus build, bring the vocal forward 2 dB in the chorus. Use them to revise the mix, arrangement, lyrics, or prompt.
Revision Tracking: Revise, Re-upload, Re-score
Changed the mix, lyrics, arrangement, or prompt? Upload the new version and see exactly how the score moved. Rate My Song AI tracks your revision history and shows you a score trajectory across versions, so you can see if your changes are actually working.
Upload. Score. Revise. Repeat.
The feedback loop for music creators. Every version is tracked. Every change is measured.
Questions
You upload an MP3, WAV, or M4A file. Our ML pipeline analyzes the raw audio waveform and scores it across four factors: Sound Quality (production, mix, mastering), Hit Potential (catchiness and genre competitiveness), Broad Appeal (how wide an audience it could reach), and an Overall composite. On top of that, an AI model analyzes your song segment by segment (intro, verse, chorus, bridge, outro) and gives you specific, actionable feedback on what's working and what to fix. The whole process takes about 30 seconds.
Yes. ChatGPT can't hear audio at all. It guesses BPM, key, and loudness from your text prompt and frequently gets them wrong. Gemini can listen to audio, but it defaults to flattery: inflated scores, overconfident praise, and vague feedback that doesn't help you improve. Both are inconsistent: the same song gets different scores depending on how you phrase the prompt. Rate My Song AI analyzes the actual audio waveform with ML models trained on real music data. Scores are repeatable, grounded in measurable audio features, and honest.
Your overall score (0–100) reflects how your track compares across four factors: Sound Quality (production, mix, mastering), Hit Potential (catchiness and genre competitiveness), Broad Appeal (how wide an audience it could reach), and an Overall composite. A score in the 30s–40s is typical for a first upload. Scores above 60 indicate strong production and composition. The breakdown shows exactly which factors are pulling the score up or down, so you know where to focus your effort.
The scoring pipeline doesn't rate "how AI-generated" your track sounds. It evaluates the audio on the same dimensions that matter whether a human or an AI made it: sound quality, hook strength, broad listener appeal, and overall competitiveness. A track with muddy low-end scores lower on Sound Quality than one with a clean mix, regardless of how it was made. The ML models are trained on real music data and measure actual audio properties from the waveform, not metadata about the creation process.
You get 20 free credits when you sign up, no credit card required. Full Review costs 5 credits. Mixing and Songwriting / Structure cost 3 credits. Revisions cost 1 credit. After your free credits, Free Lite keeps a small weekly Fast allowance available, or you can add more credits.
Most "AI song raters" are thin wrappers around ChatGPT: they send your filename or a text description to an LLM and return a generic response. They can't actually hear your music. Rate My Song AI runs your audio through a dedicated ML pipeline that produces consistent, repeatable scores from the actual waveform. You also get segment-by-segment analysis, prioritized fixes, and revision tracking so you can upload a new version and see exactly how your score changed. No other tool does this.
Guides and score research
See what the score means, what strong songs share, and how to decide which version is worth keeping.
AI Song Feedback
A clear outside read on hook, structure, production, and what to try next. Built for any audio file you want to improve.
Score to Streams
A public validation note showing how RateMySong score bands map to real Spotify plays, playlists, and artist-popularity context.
What Scores Mean
The four signals behind your score: production quality, catchiness, distinctiveness, and genre competitiveness.
Compare Versions
See why version history matters and how real improvement shows up when you score each pass instead of guessing.
Find out before you upload to Spotify.
Get a real score in 30 seconds. 20 free credits, no credit card.
Drop your track here
or click to browse · MP3, WAV, M4A