Talk naturally. Paste perfectly.
Free, on-device AI dictation and speech-to-text for macOS.
Powered by Apple Silicon. No cloud, no account, your voice never leaves your Mac.
ew-demo-tmp.mp4 #
EnviousWispr is a free AI dictation app for macOS that runs entirely on-device. It uses Whisper and Parakeet speech-to-text models on Apple Silicon to transcribe your voice locally, polishes the output with an optional LLM, and pastes clean text into whatever app you're working in. Transcription is sub-second; with optional AI polish, the full hotkey-to-paste flow typically lands in around a second and a half.
No cloud. No account required. No subscription. No audio ever leaves your Mac. Works fully offline.
It is open source under the GPLv3, actively maintained, and built to be a tool you can rely on every day.
| EnviousWispr | Cloud dictation services | |
|---|---|---|
| Privacy | ||
| 100% on-device transcription | Audio uploaded to servers | |
| Speed | ||
| Sub-second transcription, paste-on-stop | Network round-trip latency | |
| Models | ||
| Parakeet v3 (NVIDIA NeMo) + WhisperKit (OpenAI Whisper) | Single vendor model | |
| Polish | ||
| Optional. Fully on-device (EG-1, Apple Intelligence, Ollama) or bring-your-own-key cloud (GPT, Gemini) | Cloud polish, included in subscription | |
| Cost | ||
| Free. No account, no subscription | Monthly subscription | |
| Works offline | ||
| Yes, fully functional without internet | No |
Press hotkey --> Record --> Transcribe --> Polish (optional) --> Paste
~0ms live ~400-800ms ~200-500ms instant
Press your hotkey from any app. Push-to-talk, toggle, or hands-free (double-press to lock for long-form), your choice.Speak naturally. Silero VAD detects when you stop talking and ends recording automatically.On-device transcription. Choose Parakeet v3 (fastest, 25 European languages) or WhisperKit (99 languages, with automatic language detection).AI polish(optional). Clean up grammar, punctuation, and formatting. Runs fully on-device with EG-1 (our own custom model), Apple Intelligence (macOS 26+), or Ollama, or in the cloud via OpenAI or Gemini with your own API key.Text lands in your clipboard and optionally auto-pastes into the active app.
See the full interactive pipeline demo at
[enviouswispr.com/how-it-works]
Dictation is only useful if you can trust it mid-sentence, every time. EnviousWispr keeps the critical path (record, transcribe, paste) deliberately separate from every optional enhancement, so a hiccup in a "nice to have" can never swallow your words. When an optional step cannot run, you simply get your raw transcribed text instead of an error.
| What we hardened | What it means for you |
|---|---|
| Delivery survives non-critical failures | |
| If saving to your history cannot complete (full disk, permissions), your dictation is still pasted. The save is best-effort and never blocks delivery. | |
| Paste that actually lands | |
| A multi-step delivery path tries the fastest reliable method first and falls back automatically, so text lands even in apps that resist the usual paste (Word, Excel, Pages, Numbers, and more). | |
| Onboarding that won't leave you half-set-up | |
| Setup won't let you start until Accessibility is granted, and it re-checks if you later revoke permission. | |
| Clear answers when AI polish has a problem | |
| If a cloud or local model fails (OpenAI, Gemini, Ollama), you get a specific, plain-language message, and your raw text still arrives. | |
| Deterministic cleanup before AI | |
| For English, numbers, dates, and money are formatted by a fixed, predictable step, even when AI polish is off or unavailable. | |
| Fast recovery after idle | |
| After the app sits idle, it re-wakes in a fraction of a second so your next press, and its first word, are not lost. | |
| Privacy-safe diagnostics | |
| Crash reports carry counts and context, never your transcript or audio, and are redacted before they are sent. | |
| Hardened releases | |
| Every build is signed, notarized, and Gatekeeper-checked before it ships. |
| Model | Best for | Languages | Disk space | Runs on |
|---|---|---|---|---|
| Parakeet TDT v3 | ||||
| Fastest dictation (default) | 25 European languages | ~460 MB | Apple Neural Engine | |
| WhisperKit (Whisper Large v3 Turbo) | ||||
| Broadest language coverage and automatic language detection | 99 languages | ~1.6 GB | Apple GPU |
Both models run entirely on-device on Apple Silicon using CoreML. Parakeet runs on the Apple Neural Engine, which is what makes the default engine near-instant; WhisperKit runs on the GPU for broad-language accuracy. First launch downloads and compiles the model; subsequent launches are instant.
Transcription gets your words down. AI polish cleans them up: it drops filler, fixes grammar and punctuation, and structures rambling speech into readable text. This step is optional, and by default it never leaves your Mac.
| Polish engine | What it is | Runs on | Extra download |
|---|---|---|---|
| EG-1 (recommended) | |||
| Our own model, custom fine-tuned for dictation cleanup | On-device, macOS 14+ | ~2.9 GB (optional) | |
| Apple Intelligence | |||
| Apple's on-device model, no extra download | On-device, macOS 26+ | none | |
| Ollama | |||
| Bring your own local model (3B or larger recommended) | On-device | varies | |
| OpenAI / Gemini | |||
| Bring-your-own-key cloud polish, text only | Cloud (your key) | none |
EG-1 is our own AI model, fine-tuned specifically for dictation cleanup and optimized for Apple Silicon. It runs entirely on your Mac with no internet required, and it closes the gaps a general on-device model leaves: reliably turning a spoken list into a real list, splitting a wall of speech into clean paragraphs, and keeping only the corrected version when you fix yourself mid-sentence. Because it is our own model rather than Apple's, it works across the full supported range (macOS 14 and later), not just macOS 26. EG-1 is distributed under its own model license, not the GPLv3 that covers the app code (see License).
On our own benchmark of 1,890 real dictation-cleanup cases, EG-1 passed 93.7%, ahead of both GPT-5.4-mini (83.8%) and Gemini 3.5 Flash (92.6%) on the same cases with the same judge. This is our own benchmark, not an independent review. The eval harness and the exact prompts are public in scripts/eval/ so you can inspect or rerun them; the test cases are personal dictations and stay private.
- 🎙️ Dual ASR engines withParakeet v3(NVIDIA NeMo) andWhisperKit(OpenAI Whisper) - ✨ AI polish that respects your words: strips filler words and false starts, fixes grammar and punctuation, formats numbers, dates, and URLs, and honors your custom vocabulary, all in your spoken language (never translated or rewritten) - 🔒 Polish that can stay private: run it fully on-device with EG-1 (our own custom model), Apple Intelligence (macOS 26+), or Ollama, or in the cloud via OpenAI GPT / Google Gemini with your own API key - 🌍 Multilingual with automatic language detection: speak in any supported language and EnviousWispr detects it, then offers to lock it in for faster, more accurate transcription - 😀 Speak an emoji: say the emoji's name followed by "emoji" (like "thumbs up emoji") and the glyph drops right in - ✋ Voice Activity Detection via Silero VAD that stops recording automatically when you stop talking - 📚 Custom vocabulary and vocabulary packs for names, brands, and technical terms the ASR might miss, plus one-tap import of names from your Contacts (which never leave your Mac) - ⌨️ Global hotkey with push-to-talk, toggle, and hands-free modes (double-press to lock for long-form dictation) - 📋 Auto-paste directly into the active app, or just copy to clipboard - 🕘 Transcript history for browsing, searching, and reviewing past dictations - 🧭 Menu bar native with minimal footprint - 🔄 Auto-updates via Sparkle
EnviousWispr ships often. A few of the user-facing improvements from recent releases:
Pasting lands in more apps. Text now reliably reaches apps that previously said "Copied" but never pasted (Word, Excel, Pages, Numbers, OneNote, and others). (v2.1.4)Vocabulary packs and Contacts import. Turn on a pack for brands and jargon, or import the names of people you know in one tap, so hard-to-spell names come out right. Your contacts never leave your Mac. (v2.1.3)No swallowed first word after a break. After idling, the engine re-wakes in a fraction of a second and captures your words, including the very first one. (v2.1.2 and v2.1.3)Soft and distant speech captured. Quiet, whispered, or far-from-the-mic speech is now transcribed instead of dropped. (v2.1.2)Automatic update checks. The app looks for new versions on its own, with a clear "Check for Updates" control in Settings. (v2.1.2)Clearer AI polish errors. Cloud and local polish failures (OpenAI, Gemini, Ollama) now show a specific, actionable message, and your raw text still arrives.
See the full release history for every version.
Install with Homebrew:
brew install --cask saurabhav88/tap/enviouswispr
Or download manually:
- Download EnviousWispr.dmgfrom the latest release - Drag to Applications, launch
- Grant Microphone,** Accessibility**, and (on first paste fallback)** Automation**permissions when prompted - Set your preferred hotkey in Settings > Shortcuts
- Start talking
Optional: Turn on AI polish in Settings > AI Polish. Keep it fully on-device with Apple Intelligence (macOS 26+) or Ollama, or add an OpenAI or Gemini API key.
- macOS 14 (Sonoma) or later
- Apple Silicon (M1 or newer)
Core dictation works across the full supported range. The built-in Apple Intelligence polish option requires macOS 26 or later; on earlier versions dictation works normally and you can use Ollama or a cloud key for polish instead.
git clone https://github.com/saurabhav88/EnviousWispr.git
cd EnviousWispr
swift build # compiles the Swift packages (dependencies resolve via SPM)
The runnable .app
is assembled by the Xcode build engine via Tuist, not by swift build
. Use ./scripts/build-dev-app.sh
for a local dev build, or the release path below. First build takes several minutes as ML models compile.
For a distributable .app
bundle and DMG:
./scripts/build-release-dmg.sh <version>
The release build runs on the Xcode engine via Tuist, so it requires full Xcode (26+) plus mise and Tuist; set CODESIGN_IDENTITY
to sign. Running the app itself requires macOS 14+.
The app follows a pipeline state machine: idle --> recording --> transcribing --> polishing --> complete.
Key design choices:
Swift 6 strict concurrency with full actor isolationDual pipeline architecture with deliberately separate Parakeet and WhisperKit backends (isolation is a feature, not tech debt)Heart & Limbs pattern where the critical path (audio, ASR, paste) never fails, and features (polish, custom words, filler removal) degrade gracefullyLocal-first with LLM polish as an opt-in enhancement using your own keys
Contributions are welcome. EnviousWispr is open source under the GPLv3. Please open an issue to discuss significant changes before submitting a PR.
This project uses conventional commits: feat(scope):
, fix(scope):
, refactor(scope):
.
EnviousWispr is built on a simple principle: your voice is yours.
- Audio is captured, transcribed, and discarded locally. Nothing is uploaded, stored, or shared.
- LLM polish (if enabled) can run entirely on your Mac with EG-1 (our own model), Apple Intelligence, or a local Ollama model, so the polish step makes no network call. If you pick a cloud provider (OpenAI or Gemini), only text is sent (your transcript plus the polish instructions) using your own API key. Audio is never sent.
- Anonymous product analytics (PostHog) can be disabled in Settings.
- Crash reporting (Sentry) contains no transcript content, audio, or personal data.
Website:enviouswispr.com** X:@EnviousLabs Email:**hello@enviouswispr.com
Built by Envious Labs
EnviousWispr is open source under the GNU General Public License v3 (GPLv3), an OSI-approved license. You can read, build, modify, and redistribute the code under the terms of the GPL, including for commercial purposes; distributed derivative works must also be licensed under the GPLv3 with their source available.
Copyright (C) 2024-2026 Envious Labs LLC.
The EG-1 model is not open source. The GPLv3 covers the EnviousWispr application code only. EG-1's model weights are not part of this repository; they download separately and are distributed under the EG-1 Community Model License. You are free to download and use EG-1 within EnviousWispr, but you may not redistribute, re-host, mirror, or bundle the model into other products, or use the model, or outputs generated by it at scale, to train, fine-tune, or distill another model intended for commercial distribution. EG-1 is a fine-tuned derivative of Qwen3-4B-Instruct-2507 (Apache-2.0); this license applies to the fine-tuned weights.
The EnviousWispr name and logo are trademarks of Envious Labs and are not covered by the GPL.