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Speech is messy. You backtrack, you say “um”, you start a sentence three times before it lands. Cleanup runs your raw transcript through a language model that fixes it up before the text reaches your app — so what you meant to say is what gets typed. It’s optional and off until you pick a cleanup model. Turn it on under Settings → Models.

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What it does

Every cleanup level does the same core job: add punctuation and capitalization, drop filler words, and resolve the moments where you correct yourself mid-sentence. The difference is how far it goes beyond that.
When you retract something (“send it to marketing, actually no, to legal”), cleanup keeps only your final intent (“Send it to legal.”) — the abandoned wording is dropped, not left in the text.

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Cleanup intensity

Pick how aggressive the edit should be under Settings → Models.
No level translates your text or invents facts. Cleanup always keeps the same language and script you spoke in, and never adds content you didn’t say.

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List detection

At every level, when you dictate a sequence (“first… second… then…” or “one… two… three…”), cleanup formats it as a proper list instead of a run-on sentence. Ordered steps become numbered lists; plain item lists become bullets.

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Custom prompts

Need something specific — always draft in the third person, always output Markdown, always keep a certain tone? Choose Custom intensity, hit View / edit prompt, and write your own instructions.
Editing any built-in preset automatically switches you to Custom and seeds the editor with that preset’s text, so you can tweak from a solid starting point without overwriting the built-ins.

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Where cleanup runs

You can run cleanup on any of these, chosen under Settings → Models:
  • Freestyle Transcribe — transcription and cleanup in one fast pass.
  • A local LLM — runs on your device, nothing leaves your computer.
  • A cloud model — bring your own key for OpenAI, Anthropic, Google, Groq, or Mistral.
Cleanup also adapts to where you’re typing: if a format matches the active app, its instructions steer the rewrite (for example, a more formal register for email). See Formats for details.

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How it fits the pipeline

Cleanup is one stage in a larger flow. Roughly:
1

Vocabulary biases recognition

Your vocabulary terms are sent to the speech model so tricky names and jargon come through correctly.
2

Speech is transcribed

Your audio becomes raw text.
3

Cleanup rewrites the text

The language model tidies it up at your chosen intensity (this step).
4

Dictionary applies replacements

Your dictionary swaps exact phrases in the cleaned text. This runs even when cleanup is off.
If cleanup fails for any reason (a provider hiccup, an unsupported model), Freestyle falls back to your raw transcript rather than losing your words.