Dictation for your Mac that never touches the internet. Hold the fn key, talk, release, and clean text appears wherever your cursor is. Every part of it (speech recognition, AI cleanup, your dictionary, your history) runs on your Mac's own silicon.
I built this because I loved what Wispr Flow could do but didn't love sending my voice to a server to do it. Turns out Apple Silicon is fast enough that you don't have to.
- Hold fn and talk. Live transcript streams into a floating glass pill while you speak. Release and it pastes. On an M-series Mac the paste lands in well under a second for typical dictations.
- AI polish, on-device. Fillers removed, self-corrections applied ("ship friday actually monday" becomes "ship on Monday"), spoken lists formatted, tone matched to the app you're in. Casual in Messages, proper in Mail. Runs on Apple Intelligence, with a local Qwen fallback.
- Command mode. Select any text, hold fn, and say what to do with it: "make this shorter", "fix the grammar". The selection gets replaced in place.
- It learns your words. Add names and jargon to your dictionary (or import a CSV), and when you fix a word right after a paste, Plynn notices and learns the correction on its own.
- Snippets. Say "my email" and your actual email comes out.
- History and stats, stored in a local SQLite file you can open yourself.
- Spoken punctuation, "new line", "press enter" to auto-send, secure-field detection so it never types into password boxes.
Grab it at plynn.vercel.app, or grab Plynn.dmg from Releases, drag Plynn to Applications, and launch. The app is notarized, so there's nothing to bypass. Onboarding asks for microphone and accessibility permissions, and the speech models (about 1 GB) download in the background while Apple's built-in engine covers your first dictations.
Requires macOS 26 (Tahoe) on Apple Silicon. Enable Apple Intelligence in System Settings to get the best polish engine.
git clone https://github.com/31Carlton7/plynn.git
cd plynn
./scripts/make-app.shYou'll need Xcode 26 with the Metal toolchain component (xcodebuild -downloadComponent MetalToolchain). The build uses xcodebuild rather than plain swift build because the MLX Metal shaders require it. swift test runs the 80+ unit tests.
Speech recognition is Parakeet TDT running on the Neural Engine via FluidAudio, streaming partials as you speak. A deterministic rules pass handles spoken punctuation instantly, then a small on-device language model does the heavier cleanup, but only when the transcript actually needs it. Clean short dictations skip the model entirely and paste immediately. A latency gate, basically.
Your dictionary, snippets, and history live in one SQLite file at ~/Library/Application Support/Plynn/. Nothing is sent anywhere, ever. There's no account, no telemetry, and no server to go down.
See ROADMAP.md for what's next, including swappable polish models.
MIT. See LICENSE.