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As of 13 August 2026, AI can only partly mix your song.
This still needs a person who signs their name to it.
Can you do it?
15 minutesto a draft.
1 hourto something you’d act on.
Cost, all in£0
Skill neededpower-user
Who has to check ityou
What the alternative costsNo comparable human mixing service or price is supplied in the available tool information.
If this goes wrong: the song sounds harsh, muddy or unbalanced on other speakers and you have to revise the mix or pay someone else to finish it.
What to actually do
Hand it to a person
The route this page recommends
A person who owns the outcome does this end to end, worth it when the failure is dear.
Use a tool built for this
Second choiceDo it yourself
The distant thirdA chat interface, power-user skill, and roughly 1 hour until you can act on the result.
How to actually do it
- Open your digital audio workstation and create a new session using the song's original sample rate and bit depth.
- Export or gather separate, clearly named stems from the beginning of the song, including vocals, drums, bass, instruments and effects, and remove unwanted silence or clipping where you can.
- Use LALAL.AI only if you need to separate a finished stereo recording into provisional vocal and instrumental stems, then label those results as extracted and check them for artefacts.
- Write down the tempo, key if known, genre, intended mood, target platform, artistic priorities and a reference track, then paste these details and the stem list into the prompt.
- Attach the stems if the chatbot can access audio, or paste any available level, peak, loudness and plugin information, and ask it for the mixing plan.
- Apply one suggested change at a time in the session, keeping the unprocessed version available so you can compare the result at matched loudness.
- Check the mix in stereo and mono on headphones, speakers and quiet playback, then correct masking, phase, harshness, missing vocal detail and excessive bass before exporting a WAV mix.
- Compare the export against the reference at similar listening loudness and send it to an experienced musician or engineer if you cannot identify why it sounds different on another system.
Prompt
I am preparing a mix of my song and want an actionable mixing plan, not invented claims about what you can hear. I will provide the available stems, their names, sample rate, bit depth, tempo, genre, intended mood, target platform and one reference track description below. Song details: - Genre and mood: [insert] - Tempo and key, if known: [insert] - Intended platform or use: [insert] - Main artistic priorities: [insert] - Reference track and what I like about it: [insert] Stems: [paste the stem list, including any known recording or clipping problems] If audio files are attached, analyse only what you can actually access. If you cannot hear or measure a file, say so. Give me: 1. A proposed static balance and stereo image for each stem. 2. A practical order of operations for gain staging, high-pass or low-pass filtering, equalisation, compression, saturation, reverb and delay. 3. Starting settings as ranges rather than false precision, with the reason for each choice. 4. Likely masking, phase, noise and headroom problems to check. 5. Separate advice for the vocal, drums, bass, main instruments and effects returns where relevant. 6. A short listening checklist for mono, headphones, small speakers and quiet playback. 7. A final export checklist for a stereo mix, without claiming that it is release-ready. Do not rewrite the song, add parts, invent stem content or present subjective choices as facts. Ask only the most important clarifying questions before giving the plan.
Open it prefilled in ChatGPT or Claude, or copy it into Gemini, which takes no prefill link.
What it gets wrong
- AI cannot hear artistic intent that you have not described, so it cannot decide whether an imperfect balance is part of your sound.
- A chatbot cannot reliably operate your digital audio workstation, choose plugins available in your setup or make repeated listening decisions across different playback systems.
- It cannot know whether a vocal performance, drum sound or arrangement problem should be fixed in the mix or changed in the recording.
- It cannot guarantee that suggested settings will translate to cars, phones, headphones and speakers without you testing the result.
- It cannot replace an experienced mix engineer's judgement on competing priorities such as loudness, clarity, width and character.
What caps this at PARTLY: taste, judgement under ambiguity and verification cost.
How we scored this
Five axes, each scored nought to two by hand: ten means AI carries the task cleanly, and the thresholds that turn a total into YES, PARTLY or NO are published in the methodology. Each axis name links to its definition.
| Axis | Score (0–2) |
|---|---|
| Output | 1 |
| Inputs | 1 |
| Verification | 1 |
| Liability | 2 |
| Effort delta | 1 |
| Total | 6 / 10 |
The methodology and its thresholds are published in full.
FAQ
- Can ChatGPT mix my song?
- Partly. It can turn your stems, references and aims into a useful mixing plan, but it cannot reliably deliver a finished mix or make all the listening decisions for you.
- Can AI mix vocals and music together?
- AI can suggest ways to balance vocals against music and can help identify likely masking problems. You still need to apply the changes in your audio workstation and check whether the vocal remains clear on different playback systems.
- What files do I need to give AI to mix a song?
- Use separate stems that start at the same point, with their names and any known recording problems. Add the tempo, genre, intended mood, target use and a reference track, but do not assume a chatbot can hear an attachment unless it confirms that it can access it.
- Is AI good enough to mix a song for release?
- It can help you reach a workable draft, especially by organising decisions and suggesting checks. It cannot guarantee a release-ready result, so get an experienced second listener or mix engineer involved if you cannot verify the technical and creative choices yourself.
Nearby answers
Assessed by gpt-5.6-luna (gpt-5.6-luna) on 2026-08-13, second-checked by an independent model. Wrong somewhere? Email [email protected] and it gets re-checked.
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