Suno Audio Input: Giving the Model a Melody Instead of Describing One
Every prompting problem in Suno comes back to the same limitation: you are describing music in words, and words are a low-bandwidth way to specify a melody. Audio input removes that constraint. You hum the hook, upload it, and the thing you could not describe is simply present. v6 extends this to images and video as well, and adds a fourth slider that only appears once you use it.
- Uploading audio replaces description with demonstration. A melody you cannot write down in words is fully specified the moment you hum it into your phone.
- v6 accepts text, audio, images and video as starting material, and can combine several sources in one request — Suno's own launch examples include building from a photo, an audio clip and a written note together.
- A fourth Creative Slider, Audio Influence, appears only when an Audio Upload is in play. It governs how strongly your recording steers the result, and most users never see it because it is hidden without an upload.
- Recording quality matters less than rhythmic and pitch clarity. A phone voice memo with a clear, confident melody outperforms a well-recorded hesitant one.
- This is a different feature from covers and from Extend. Audio input starts a new song from your material; a cover reinterprets an existing track; Extend continues one you already have.
- Your own melody does not make the output human. The rendered file is still AI-generated audio and is screened as such — raw AI tracks were rejected 50 of 50 by DistroKid in our benchmark.
Suno audio input solves a problem that no amount of prompt engineering can. Every other guide on this site is ultimately about describing music in words — and words are a narrow channel for specifying a melody. You can write "a rising four-note hook with a syncopated feel" and get back ten different things, none of them the one in your head.
Upload four seconds of yourself humming it, and the ambiguity is gone. The melody is not described. It is present.
That is the whole case for this feature, and it is why the users reporting the best v6 results are disproportionately the ones feeding it their own material.
What v6 accepts
With v6, starting material is no longer limited to text. Suno's launch announcement describes creating with text, audio, images and video — starting from a written idea, a voice memo, a visual or a video and turning it into music — and combining several sources in a single request. Their own worked example asks for a song based on an image, an audio clip and a journal entry together.
The practical cases, in rough order of how often they actually help:
- A hummed or sung melody. The hook you cannot notate. This is the highest-value use by a distance.
- A played riff. Guitar, piano, anything with clear pitch and rhythm.
- A rhythmic reference. A clapped or beatboxed groove when the feel matters more than the notes.
- A spoken idea. Less precise, but it carries phrasing and cadence that written lyrics lose.
The slider you have never seen
There is a control most Suno users have never encountered, because it does not exist until you upload something.
Suno's Creative Sliders documentation lists Weirdness and Style Influence, then adds one line: if you are using an Audio Upload, you also get a third slider, Audio Influence.
That control governs how hard your recording steers the result. Turned up, the output stays close to what you played. Turned down, your upload becomes a loose suggestion the model may wander away from. It is the single most consequential setting in this workflow and it is invisible until you are already in it.
It also interacts with a control that catches people out elsewhere. Suno's v6 FAQ states that the Variety slider works by adjusting and updating your style prompts, and that reducing it to 0 retains full control of your style tags. If you are trying to run a controlled comparison between uploads, a non-zero Variety setting is changing your text between runs while you are trying to measure your audio. Our creative sliders guide covers all four controls against the documentation.
What makes an upload work
The instinct is to worry about recording quality. That is mostly the wrong worry.
What the model needs is a legible performance — steady tempo, clear pitch, and enough confidence that the melodic intent is unambiguous. A phone voice memo of a hook you know cold will beat a well-recorded take of something you are still working out, every time. Hesitation, drifting tempo and uncertain pitch are what degrade the result, not the microphone.
Practical guidance that holds up:
- Sing or play it like you mean it. Commitment reads as intent; tentativeness reads as noise.
- Keep it short. A few seconds of the actual hook beats a minute of searching for it.
- Give it a clear start. Leading silence or a false start muddies where the model thinks the phrase begins.
- One idea per upload. Two competing melodic fragments produce an average of both.
- Avoid heavy background noise, but do not re-record for a slightly noisy floor. It matters less than the performance.
How to tell whether it is actually helping
The claim that "your own audio produces better results" is widely repeated in v6's first week and worth testing rather than trusting, because it is the kind of claim that feels true regardless of whether it is.
Run the same brief twice. Write your style prompt, set Variety to 0 so your text stays fixed, and generate once from text alone. Then generate again with the identical prompt plus your uploaded melody, leaving everything else untouched. Compare.
What you are looking for is not "which is better" — it is which one is more like the song you meant. Those are different questions, and audio input tends to win the second decisively while the first stays a matter of taste. If the text-only version is perfectly good but generic, and the upload version is rougher but recognisably yours, the feature is doing its job.
A worked comparison
The value of this feature is easiest to see by running one brief two ways.
Take the same style prompt both times. Something ordinary: a mid-tempo indie folk song, acoustic guitar, brushed drums, warm male vocal. Set Variety to 0 so your text is not edited between runs.
Run one: text only. You get a competent indie folk song. The melody is whatever the model reached for — probably pleasant, almost certainly not the one you had in mind, because you never told it.
Run two: identical prompt, plus a four-second voice memo of you humming the chorus hook. The arrangement is built around your shape. The contour of the melody, where it rises, how it resolves, are all yours.
The honest result is that run one is often smoother. Model-chosen melodies tend to be conventional in a way that sounds professionally inoffensive. Run two will have rougher edges.
It will also be your song. That is the trade, and it is why the test to apply is "which is closer to what I meant" rather than "which sounds better". If you cannot tell them apart, your upload was probably too hesitant or too long — shorten it, commit to it, and run it again.
What to keep constant while testing
| Setting | While testing uploads | Why |
|---|---|---|
| Style prompt | Identical both runs | Otherwise you are measuring two things |
| Variety | 0 | Documented to rewrite style prompts between runs |
| Audio Influence | Note the value each run | The control you are actually testing |
| Upload length | A few seconds | Longer uploads dilute the hook |
| Upload content | One melodic idea | Two ideas average into neither |
Three features that all take audio
Audio input gets confused with two neighbours, and reaching for the wrong one wastes generations.
Audio input seeds a new song with your material. The output is original; your recording is the starting idea.
Cover reinterprets an existing song, keeping its structure and melody while changing the performance and production. The output is a version of something that already exists.
Extend continues a track you already have, covered on our Suno extend feature page. The output is more of the same song.
If your sentence starts "I have an idea for a hook", you want audio input. If it starts "I have a song and I want it to sound different", you want a cover. If it starts "I have a song and I want more of it", you want Extend.
One thing not to upload
Upload your own performances only.
Suno's v6 announcement describes safeguards introduced to screen uploaded audio files and lyrics for unauthorised use, arriving alongside the licensing partnerships with Warner Music Group, BMG and Believe. Practically, that means attempts to seed a generation with commercial recordings are increasingly likely to be blocked at upload.
The deeper reason is that it does not solve anything even when it works. Material you do not have rights to creates a rights problem in everything generated from it, and that problem follows the track to distribution. Our AI music copyright page covers where ownership actually lands.
Your melody, the model's audio
There is a misconception worth addressing directly, because it costs people money at the distribution stage.
Starting from your own hummed hook feels like it should make the output less artificial, and in a creative sense it does — the idea is genuinely yours. But the file is not a recording of you. It is audio the model rendered, carrying the same generation artifacts as any other v6 output, and distributor screening examines the file rather than its provenance story.
So the numbers do not move. In our benchmark on raw, unprocessed AI tracks: DistroKid rejected 50 of 50, TuneCore 47 of 50 and CD Baby 42 of 50, against approximate thresholds of 0.78, 0.82 and 0.85. A track seeded by your own melody sits in exactly the same position as one seeded by a text prompt.
Undetectr works on Suno v6 output and is the tool in our benchmark that addresses that layer. It processes the audio signal across six layers — spectral artifact removal, temporal pattern normalisation, dynamic range processing, metadata sanitisation, and removal of embedded SynthID and C2PA provenance data. Those are the markers DistroKid, Spotify, Apple Music and Amazon Music scan on ingestion, and because the engine targets classes of artifact rather than a version-specific signature, v6 output is handled the same way v5 output was.
Hum it, build it, clean it, ship it. Our guide to uploading Suno tracks to Spotify covers the final step.
How we checked
The multimodal input capabilities and the upload safeguards are taken from Suno's v6 announcement of 9 September 2026, fetched 11 September. The Audio Influence slider and its upload-only condition come from Suno's Creative Sliders documentation, and the Variety slider behaviour from the v6 FAQ, both fetched the same day.
Community reports came from a structured pull of Reddit and YouTube discussion across 12 August to 11 September 2026: 25 Reddit threads carrying 782 upvotes and 1,351 comments, plus six YouTube videos with transcripts. v6 launched on 9 September, so direct v6 experience spans two days and several audio-input discussions in the pool predate the release.
Three caveats. The reported advantage of uploading your own audio is a community observation from v6's first days, which is why this page gives you a method to test it rather than asserting it as measured. Upload-screening behaviour is described by Suno but we have not tested its boundaries, and we would not encourage anyone to. And our distributor rejection figures describe a pre-v6 corpus; the v6 re-run is in progress and will be published when it completes.
Questions readers ask.
Yes. Suno accepts an audio upload as a starting point, and with v6 that expanded to images and video as well. Suno's own launch material describes creating from a written idea, a voice memo, a visual or a video, and combining several of those in one request. In practice the most useful case is the simplest: hum or play the melody you have in your head, upload it, and let the model build around material it can hear rather than material you have described.
It is a fourth Creative Slider that appears only when you are using an Audio Upload. Suno's Creative Sliders documentation lists it alongside Weirdness and Style Influence with that condition attached. It controls how strongly your uploaded recording steers the generation — higher keeps the result closer to what you played, lower treats your upload as a loose suggestion. Because it is hidden without an upload, most users never encounter it. Our Suno creative sliders guide covers the other three.
Less than you would expect. What matters is that the melody is rhythmically and harmonically legible — steady tempo, clear pitch, confident delivery. A phone voice memo of a hook you know well will outperform a studio-quality recording of something hesitant or drifting in tempo. Background noise is worth avoiding, but it is a smaller problem than an unclear performance. Sing or play it like you mean it and the fidelity is secondary.
No, and the distinction matters. Audio input uses your material as the seed for a new song. A cover reinterprets an existing track, keeping its structure and melody while changing the performance. Extend continues a song you already have. They overlap in that all three take audio as input, but they answer different questions — audio input is the one to reach for when the goal is something new built around your idea.
You should not, and it is increasingly likely to be blocked. Suno's v6 announcement describes safeguards that screen uploaded audio and lyrics for unauthorised use, introduced alongside the licensing partnerships with Warner Music Group, BMG and Believe. Beyond the platform question, uploading material you do not have rights to creates a rights problem in whatever you generate from it. Upload your own performances. Our AI music copyright page covers the ownership position in full.
No. This is the most common misconception about audio input. Distributor screening scans the rendered output file for the statistical fingerprint and embedded watermarks that generation leaves behind — it does not trace where the idea came from. A song built from your own hummed hook is still AI-generated audio and is screened identically. In our benchmark, raw AI tracks were rejected 50 of 50 by DistroKid, 47 of 50 by TuneCore and 42 of 50 by CD Baby. Undetectr works on Suno v6 output and removes those artifacts so the file clears Spotify, Apple Music and the rest.
The verdict, in one sentence: Undetectr.
A song built from your own hummed hook is still AI-generated audio, and distributor screening does not care where the idea started. Undetectr works on Suno v6 and removes the AI watermarks and spectral fingerprints that DistroKid, Spotify and Apple Music scan for. $39 one-time, roughly 90 seconds per track.