OpenWhispr
The open-source and free alternative to WisprFlow and Granola.
Privacy-first voice-to-text dictation with AI agents, meeting transcription, and notes. Cross-platform for macOS, Windows, and Linux.
Website · Docs · Download · API · Changelog
OpenWhispr turns your voice into text, notes, and actions from your desktop. Press a hotkey, speak, and your words appear at your cursor. Choose between fully private offline transcription with local speech-to-text models like Orukeet, Whisper, NVIDIA Parakeet, and Cohere Transcribe — where your audio never leaves your device — or cloud processing for speed. No data collection, no telemetry, fully open source.
Download
| Platform | Download |
|---|---|
| macOS (Apple Silicon) | .dmg |
| macOS (Intel) * | .dmg |
| Windows | .exe |
| Linux | .AppImage / .deb / .rpm / .tar.gz |
* On Intel Macs, live speaker identification and voice fingerprinting are unavailable: they depend on ONNX Runtime, which stopped shipping macOS x86_64 binaries in 1.24. Meetings still record and transcribe normally, and notes search falls back to keyword matching instead of semantic search.
Features
- Voice dictation — global hotkey to dictate into any app with automatic pasting
- Dictation translation — dedicated hotkey to dictate in one language and paste the text in another
- AI agent — talk to GPT-5, Claude, Gemini, Groq, Tinfoil, OpenRouter, or local models with a named voice assistant
- Voice Assistant hotkey — dedicated hotkey that sends what you say straight to your AI assistant as a command, no wake word needed and no cleanup pass; highlighted text is edited in place. With auto-paste enabled, answers paste at a focused text cursor or stream into a floating panel and copy to the clipboard when no writable cursor is available. You can also opt in to sending a screenshot of your current screen as context
- Meeting transcription — auto-detect Zoom, Teams, and FaceTime calls with live speaker diarization, voice fingerprinting, and Google, Microsoft, or Apple Calendar integration
- Local speaker diarization — on-device speaker labelling with voice fingerprint recognition across meetings, no cloud required
- Notes — create, organize, and search notes with folders, semantic search, cloud sync, and AI actions
- Team spaces & sharing — free for signed-in users; share notes on the web with link, domain, or invite-only visibility, and collaborate in team spaces with roles, invitations, and server-enforced membership
- Audio import — transcribe existing audio and video: drag in files, batch-upload, or paste a YouTube/audio URL, with optional speaker detection
- Local or cloud — your choice — all core features (transcription, AI reasoning, speaker diarization, semantic search) work with local models or cloud providers — including GPU-accelerated local Whisper on Metal, CUDA, and Vulkan (AMD/Intel)
- Enterprise controls — enforce organization policy, company SSO and SCIM, and centrally managed Amazon Bedrock or Azure OpenAI access without distributing cloud keys
- Public API & MCP — manage notes and transcriptions programmatically or connect your AI assistant via the MCP server
Quick start
git clone https://github.com/OpenWhispr/openwhispr.git
cd openwhispr
npm install
npm run devRequires Node.js 24+. See the full documentation for setup guides, platform-specific instructions, and build details.
The commands above run the desktop application, which remains at the repository root. The Expo mobile application lives in openwhispr-mobile with its own dependencies, lockfile, build configuration, and release process. See the mobile README for its setup instructions.
Documentation
Visit docs.openwhispr.com for:
- Getting started
- Platform guides (macOS, Windows, Linux)
- API reference
- MCP server setup
- Troubleshooting
Repo examples:
- Custom ASR shim for Self-Hosted transcription against non-OpenAI-compatible ASR APIs
Tech stack
React 19, TypeScript, Tailwind CSS v4, Electron 41, better-sqlite3, whisper.cpp, sherpa-onnx, shadcn/ui
Star History
Sponsors
Neon is the serverless Postgres platform powering OpenWhispr Cloud.
Contributing
We welcome contributions. Fork the repo, create a feature branch, and open a pull request. See the contributing guide for development setup and guidelines.
License
MIT — free for personal and commercial use.
Acknowledgments
- OpenAI Whisper — speech recognition model powering local and cloud transcription
- whisper.cpp — high-performance C++ implementation for local processing
- NVIDIA Parakeet — fast multilingual ASR model
- sherpa-onnx — cross-platform ONNX runtime for Parakeet inference
- Hugging Face — model hub hosting Whisper, Parakeet, and embedding model weights
- llama.cpp — local LLM inference for AI text processing
- Electron — cross-platform desktop framework
- React — UI component library
- shadcn/ui — accessible components built on Radix primitives
- Neon — serverless Postgres powering OpenWhispr Cloud
