Processed locally
Local dictation sends no audio to a transcription server after the one-time model download.
In Local mode, Lamitype turns speech into text on your Mac. After the one-time model download, dictation works offline, with no account or app telemetry.
No saved recordings · No app telemetry · No word limits
Real Lamitype capture. Hold Right Option, speak an English coding prompt, then release to place the transcript at the cursor.
Local privacy, with clear boundaries
Local speech recognition runs on your Mac after the model download. The app is open source, and the ordinary dictation path does not save audio recordings.
Local dictation sends no audio to a transcription server after the one-time model download.
Audio is held in memory while Lamitype transcribes, then discarded instead of saved as a file.
The app contains no telemetry and its MIT-licensed source is public.
Lamitype pastes at the cursor in most editable Mac apps. If insertion is blocked, the transcript remains on the clipboard.
Destination apps have their own policies. Once text is pasted or sent elsewhere, that app handles it under its own privacy policy.
Cloud features are optional. They send audio to the provider you choose only when you enable them and supply the needed credentials.
How it works
Install the free app. Setup walks through microphone and Accessibility permissions.
Focus an editable text field, hold the shortcut, and speak naturally.
The transcript appears at the cursor. If an app blocks insertion, it remains on the clipboard.
Optional · Text Polish
Select a short passage in an editable app and double-tap Right Option. Text Polish attempts an in-place correction, then shows a diff of the result.
Limits stay visible
The small on-device model can miss issues or over-edit. Automatic polishing is off by default, and the raw transcript is inserted unchanged if it errors or times out.
Local model footprint
Model weights at the precisions shown, in MB.
≤ 2.1 GB maximum observed RAM. For the whole Lamitype process with the local model loaded, including the MLX idle cache. Unload the model from the menu with one click to release its weights and cached buffers; a small amount of app memory remains.
FAQ
Yes. Lamitype is free under the MIT license, with no account, subscription, app telemetry, or word limits. Optional cloud recognition uses your own provider API key, so provider charges may apply.
The one-time model download uses the network. After that, local speech recognition works offline. Update checks connect to GitHub only after you choose Check for Updates and confirm. Optional cloud features use the selected provider when enabled.
Local dictation holds each recording in memory while it transcribes, then discards it. Lamitype does not save ordinary dictation audio as files. The transcript is placed on the macOS clipboard, which can persist or sync according to your Mac settings.
Lamitype’s default local model has about 708 MB of model weights. The initial download may include additional files. Maximum observed RAM for the whole Lamitype process is ≤ 2.1 GB with the local model loaded, including the MLX idle cache. Unloading the model frees its weights and cached buffers.
Local mode runs Qwen3-ASR 0.6B as a 4-bit MLX quantization, about 708 MB of weights, executed in-process by native Swift on Apple Silicon with no Python runtime or local server. Qwen3-ASR handles mixed Chinese and English natively, and OpenCC guarantees Traditional Chinese output. You can also use your own key for OpenAI or Gemini cloud recognition.
Lamitype pastes the transcript at your cursor in most editable Mac apps. If an app blocks direct insertion, the transcript remains on the clipboard so you can paste it yourself.
Lamitype supports Apple Silicon Macs with M series chips running macOS 15 or later. Intel Macs are not supported because the local engine uses Apple's MLX framework.
On macOS 26 or later, Text Polish can use Apple Intelligence to attempt an in-place correction of a short selection, then show a diff of the result. It can miss issues or over-edit.
They are the same product. HushType was renamed Lamitype in 2026. The developer, codebase, and version history continue on GitHub.
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