Muesli

Local-first dictation & meeting transcription for macOS
100% on-device speech-to-text · Zero cloud costs · Privacy by default

What is Muesli?

Muesli is a lightweight native macOS app that combines WisprFlow-style dictation and Granola-style meeting transcription in one tool. All transcription runs locally on Apple Silicon — your audio never leaves your device unless you choose a cloud-backed meeting summary provider.

Dictation

Hold your hotkey (or double-tap for hands-free mode) → speak → release → transcribed text is pasted at your cursor. ~0.13 second latency via Parakeet TDT on the Apple Neural Engine.

Meeting Transcription

Start a meeting recording → Muesli captures your mic (You) and system audio (Others) simultaneously → VAD-driven chunked transcription happens during the meeting at natural speech boundaries → speaker diarization identifies individual remote speakers (Speaker 1, Speaker 2, etc.) → when you stop, the transcript is ready in seconds, not minutes. Generate structured meeting notes via OpenAI, free OpenRouter models, your ChatGPT Plus/Pro subscription, or local Ollama models.

Live meeting transcripts have two explicit modes. Nemotron 3.5 is a unified multilingual option: its continuous transcript is the normal final raw transcript before diarization and note generation, with the configured meeting model retained only for gap recovery. Parakeet Realtime EOU is a low-latency English preview: it powers the live floating transcript while a separately selected meeting model creates the final transcript. Settings always shows which model owns the final transcript.

Live transcription is off by default. Download Parakeet Realtime EOU or Nemotron 3.5 from Models, then select one under Settings → Meetings → Transcription. The waveform-hover preview can be enabled separately from the same section. Downloading a streaming model does not activate it automatically.

Features

Native macOS architecture — Swift, AppKit, and SwiftUI app code with in-process CoreML/ANE, Metal, and LiteRT-LM inference.
Multiple ASR models — Parakeet TDT and Nemotron 3.5 (Neural Engine), Cohere Transcribe 2B (mixed precision CoreML), multilingual Whisper Tiny/Small/Large Turbo (CoreML/ANE via WhisperKit), Qwen3 ASR, SenseVoice Small, Indic ASR, and experimental Gemma 4 E2B.
Hold-to-talk & hands-free — Hold hotkey for quick dictation, or double-tap for sustained recording.
Meeting recording — Captures mic + system audio (including Bluetooth/AirPods) with a CoreAudio process tap by default and ScreenCaptureKit fallback. System audio from Zoom, Teams, and other call clients stays on the Others side of the transcript.
Live meeting transcript — Choose Nemotron 3.5 for one multilingual live-and-final transcript, or Parakeet Realtime EOU for an English live preview paired with a separate final meeting model.
VAD-driven chunk rotation — Silero VAD detects natural speech boundaries in real-time, splitting mic audio at pauses instead of fixed intervals. No mid-sentence cuts.
Speaker diarization — Identifies individual speakers in system audio (Speaker 1, Speaker 2, etc.) using FluidAudio's pyannote-based CoreML diarization model.
Camera-based meeting detection — Detects when your webcam + mic activate in a recognized meeting app (Zoom, Chrome, Teams, FaceTime, Slack, WhatsApp). Camera alone (e.g. Photo Booth) won't trigger false positives.
Join & Record — Extracts meeting URLs from calendar events (Zoom, Google Meet, Teams, Webex, Chime, FaceTime). Split-button notification: "Join & Record" opens the meeting + starts recording, "Join Only" opens without recording, "Record Only" starts recording without joining. Platform icons (Zoom, Meet) in the notification panel.
Google Calendar integration — Connect your Google Calendar to see upcoming meetings in the Coming Up section and status bar. Choose whether Muesli watches today, two days, or three days of upcoming events. Event-driven notifications via EKEventStoreChangedNotification for instant calendar change detection. Pre-meeting countdowns via Marauder's Map easter egg.
Import Audio — Import m4a, mp4, wav, or mp3 files for offline transcription, speaker diarization, title generation, summaries, and saved meeting history.
Meeting export — Export meeting notes or transcripts as PDF (paginated US Letter) or Markdown. Format picker in the save panel, auto-opens the exported file.
Meeting templates — Built-in and custom templates for meeting notes. Choose a template before or after recording — re-summarize any meeting with a different template.
Dismiss calendar events — Hide irrelevant events from Coming Up, status bar, and menu bar. Dismissed events are pruned automatically.
iCloud Text Sync & iPhone Bridge — Privately sync dictation text, meeting transcripts, notes, summaries, and manual notes with Muesli for iPhone through iCloud. Audio recordings are never synced.
Filler word removal — Automatically strips "uh", "um", "er", "hmm" and verbal disfluencies.
AI meeting notes — BYOK with OpenAI or OpenRouter, sign in with your ChatGPT Plus/Pro subscription (no API key needed), or use local Ollama models. Auto-generated meeting titles. Re-summarize any meeting.
ChatGPT OAuth — Sign in with your existing ChatGPT subscription via browser-based OAuth (PKCE). Tokens stored in the app support directory with owner-only file permissions.
Computer Use planner — Optional voice-driven planner that can execute local app and browser actions from dictated commands with configurable model and timeout settings.
Post-meeting hooks — Run a user-supplied executable after completed meetings. Hooks receive a JSON payload on stdin and log results in the app support directory.
Personal dictionary — Add custom words, phrase matches, and replacement pairs. Jaro-Winkler fuzzy matching auto-corrects transcription output.
Model management — Download, delete, and switch between models from the Models tab. Background downloads that don't block the app.
Configurable hotkeys — Choose any modifier key (Cmd, Option, Ctrl, Fn, Shift) for dictation.
Onboarding — First-launch wizard with model selection, real OS permission verification, hotkey configuration, smoother Accessibility handoff, live dictation test to verify the full pipeline works, and optional summary setup for ChatGPT, OpenAI, OpenRouter, or Ollama. Progress saved on every step — survives crashes and manual quits.
Launch at Login — Start Muesli automatically with macOS login items, with approval-state refresh in Settings.
Dark & light mode — Adaptive theme with toggle in sidebar.
SwiftUI dashboard — Dictation history, meeting notes (Notes-style split view), meeting folders, dictionary, models, shortcuts, settings, about page.
Floating indicator — Frosted glass pill with dynamic waveform, accent color customization, and click-to-stop for meetings.

Install

Download (recommended)

Download the latest .dmg from Releases, open it, and drag Muesli to Applications — or double-click to install automatically.

Homebrew

brew install --cask muesli

Current Homebrew also resolves brew install muesli to the official cask; the --cask form is shown to make the app install explicit.

Build from source

Requirements: macOS 14.2+, Xcode 16+

# Clone
git clone https://github.com/Muesli-HQ/muesli.git
cd muesli

# Build and install to /Applications
./scripts/build_native_app.sh

# Contributor dev build without the maintainer Developer ID certificate
MUESLI_SKIP_SIGN=1 ./scripts/dev-test.sh

Release builds are signed by the maintainer Developer ID certificate. External contributors can use the unsigned dev build for local testing; it installs MuesliDev.app with a separate bundle ID and app data directory. See CONTRIBUTING.md for the full local development workflow.

The selected transcription model downloads on demand (~450 MB for the recommended Parakeet v3). The app bundle also includes the arm64 LiteRT-LM runtime (~61 MB) for experimental Gemma 4 support; its ~2.6 GB model weights download only when Gemma is selected.

Agent CLI

Muesli bundles an agent-friendly local CLI inside the app bundle:

Installed path: /Applications/Muesli.app/Contents/MacOS/muesli-cli
Dev path: native/MuesliNative/.build/arm64-apple-macosx/debug/muesli-cli
Future Homebrew alias: muesli once the official cask exposes the bundled binary as a command

The CLI is designed for coding agents such as Codex and Claude Code. It exposes meetings, dictations, raw transcripts, stored notes, and local audio-file transcription. Existing data commands return stable JSON so an agent can analyze them with its own model and write notes back without requiring a user-supplied OpenAI or OpenRouter key. transcribe prints plain transcript text by default so it works naturally in shell pipelines.

What agents should do

Discover the CLI:

command -v muesli-cli || echo "/Applications/Muesli.app/Contents/MacOS/muesli-cli"

Inspect the command contract:

/Applications/Muesli.app/Contents/MacOS/muesli-cli spec

Transcribe a local audio file:

/Applications/Muesli.app/Contents/MacOS/muesli-cli transcribe file.mp3

Homebrew users should eventually be able to use:

muesli transcribe file.mp3

List recent meetings or dictations:

/Applications/Muesli.app/Contents/MacOS/muesli-cli meetings list --limit 10
/Applications/Muesli.app/Contents/MacOS/muesli-cli dictations list --limit 10

Fetch a full record:

/Applications/Muesli.app/Contents/MacOS/muesli-cli meetings get 125
/Applications/Muesli.app/Contents/MacOS/muesli-cli dictations get 42

Summarize or analyze locally in the agent.

Write improved meeting notes back:

cat notes.md | /Applications/Muesli.app/Contents/MacOS/muesli-cli meetings update-notes 125 --stdin

Commands

muesli-cli spec
muesli-cli info
muesli-cli transcribe <file> [--format text|json|markdown] [--model parakeet-v3|parakeet-v2|parakeet-eou-320ms|sensevoice|qwen3-asr|nemotron35|whisper-tiny|whisper-tiny-english|whisper-small|whisper-small-english|whisper-medium-english|whisper-large-turbo] [--dictionary PATH] [--summarize] [--save-meeting] [--title TITLE] [--output PATH]
muesli-cli meetings list [--limit N] [--folder-id ID]
muesli-cli meetings get <id>
muesli-cli meetings update-notes <id> (--stdin | --file <path>)
muesli-cli dictations list [--limit N]
muesli-cli dictations get <id>

Audio transcription

Supported input files: .mp3, .mp4, .m4a, and .wav.

Default output is transcript text only:

muesli-cli transcribe interview.mp3

Agent-friendly JSON output uses the normal CLI envelope:

muesli-cli transcribe interview.m4a --format json

{
  "ok": true,
  "command": "muesli-cli transcribe",
  "data": {
    "transcript": "Raw transcript text...",
    "summary": null,
    "durationSeconds": 123.4,
    "wordCount": 420,
    "model": "parakeet-v3",
    "warnings": [],
    "savedMeetingID": null,
    "title": "interview"
  },
  "meta": {
    "schemaVersion": 1,
    "generatedAt": "2026-07-08T00:00:00Z",
    "dbPath": "/Users/example/Library/Application Support/Muesli/muesli.db",
    "warnings": []
  }
}

Generate markdown notes with the configured API/local summary backend when available:

muesli-cli transcribe interview.mp4 --summarize --format markdown --output notes.md

--summarize uses configured OpenAI, OpenRouter, Ollama, LM Studio, or Custom LLM settings. If the configured backend is unavailable in headless CLI mode, Muesli keeps the transcript and reports a warning instead of discarding the transcription.

Save the import into Muesli as source = audio_import:

muesli-cli transcribe interview.wav --save-meeting --title "Customer Interview"

Dictionary import and export

The app's Dictionary tab supports importing and exporting the personal dictionary as JSON. Import merges entries by match word, updates an existing match when the imported definition differs, and appends new words. Export produces the same portable format accepted by muesli-cli --dictionary:

[
  {
    "word": "museli",
    "replacement": "muesli",
    "matching_threshold": 0.85
  }
]

The CLI also accepts an app config.json directly when it contains a custom_words array:

muesli-cli transcribe interview.wav --dictionary ~/Library/Application\ Support/Muesli/config.json

parakeet-eou-320ms is available for batch file transcription. The CLI chunks the audio internally and returns the completed transcript; it does not expose streaming partials for file transcription.

Direct app-bundle fallback path:

/Applications/Muesli.app/Contents/MacOS/muesli-cli transcribe file.mp3

JSON contract

Data commands return JSON on stdout. transcribe returns plain text by default; pass --format json to use the envelope below.

Success shape:

{
  "ok": true,
  "command": "muesli-cli meetings get",
  "data": {},
  "meta": {
    "schemaVersion": 1,
    "generatedAt": "2026-03-17T00:00:00Z",
    "dbPath": "/Users/example/Library/Application Support/Muesli/muesli.db",
    "warnings": []
  }
}

Failure shape:

{
  "ok": false,
  "command": "muesli-cli meetings get 999",
  "error": {
    "code": "not_found",
    "message": "No meeting exists with id 999.",
    "fix": "Run `muesli-cli meetings list` to find a valid ID."
  },
  "meta": {
    "schemaVersion": 1,
    "generatedAt": "2026-03-17T00:00:00Z",
    "dbPath": "",
    "warnings": []
  }
}

Important meeting fields:

rawTranscript
formattedNotes
notesState
calendarEventID
micAudioPath
systemAudioPath

notesState values:

missing
raw_transcript_fallback
structured_notes

Notes for agent authors

The CLI is JSON-first and intended to be machine-consumed.
transcribe is text-first by default; use --format json for structured agent workflows.
formattedNotes is the only write-back surface in v1.
rawTranscript is read-only and should be treated as source material.
If notesState is missing or raw_transcript_fallback, agents should prefer summarizing from rawTranscript.
Use --db-path or --support-dir only when the default Muesli data location is wrong.

Models

Model	Backend	Runtime	Size	Languages	Latency
Parakeet v3 (recommended)	FluidAudio	CoreML / Neural Engine	~450 MB	25 languages	~0.13s
Parakeet v2	FluidAudio	CoreML / Neural Engine	~450 MB	English only	~0.13s
Parakeet Realtime EOU	FluidAudio	CoreML / Neural Engine	~430 MB	English only	Live preview
Cohere Transcribe 2B	CoreML	FP16 encoder + INT8 decoder	~3.8 GB	14 languages	~1s
Nemotron 3.5 Multilingual	FluidInference	CoreML / Neural Engine	~665 MB	100+ locales	Live + final
SenseVoice Small	FluidAudio	INT8 CoreML / Neural Engine	~240 MB	50+ languages	~1s
Qwen3 ASR	FluidAudio	CoreML / Neural Engine	~1.3 GB	52 languages	~2-3s
Indic ASR	CoreML	RNNT	~618 MB	7 Indian languages	Experimental
Gemma 4 E2B	LiteRT-LM	Metal GPU decoder + CPU audio encoder	~2.6 GB	Multilingual	Experimental
Whisper Tiny Multilingual	WhisperKit	CoreML / Neural Engine	~153 MB	Multilingual	Fastest Whisper option
Whisper Tiny English	WhisperKit	CoreML / Neural Engine	~153 MB	English only	Fastest English Whisper option
Whisper Small Multilingual	WhisperKit	CoreML / Neural Engine	~250 MB	Multilingual	~1-2s
Whisper Small English	WhisperKit	CoreML / Neural Engine	~250 MB	English only	~1-2s
Whisper Medium English	WhisperKit	CoreML / Neural Engine	~1.5 GB	English only	Slower, more accurate English option
Whisper Large Turbo Multilingual	WhisperKit	CoreML / Neural Engine	~626 MB	Multilingual	~2-4s

Whisper's Tiny and Small sizes are available as either multilingual or English-only downloads. The multilingual variants auto-detect the spoken language by default and also let you pin a language; the English variants stay focused on English and therefore do not show a language control. Medium English is available when English accuracy matters more than download size and speed, while Large Turbo is the strongest multilingual choice for accents, background noise, and mixed-language audio. Every variant can be downloaded, deleted, and downloaded again from the Models tab.

The app and muesli-cli share Nemotron 3.5's model cache at ~/.cache/muesli/models/nemotron35-multilingual-2240ms; downloading it in one surface makes it available to the other without a second copy.

Cohere Transcribe is a 2B parameter model (#1 on Open ASR Leaderboard) running in mixed precision — FP16 FastConformer encoder on the Neural Engine with INT8 quantized decoders. Includes VAD-gated silence detection to prevent hallucination. Best for high-accuracy multilingual dictation.

Gemma 4 E2B is an experimental multimodal LiteRT-LM backend for direct transcription or on-device transcript cleanup. It is not an ASR-tuned model, so assistant-style outputs are rejected and Parakeet remains the recommended transcription backend. Gemma cannot be selected for ASR and cleanup at the same time.

Meeting echo cancellation uses LocalVQE by default. Release builds ship the bundled localvqe-v1.2-1.3M-f32.gguf model plus the LocalVQE shared libraries, so users do not need to download an AEC model before their first meeting transcription. DTLN remains available as the fallback AEC path when LocalVQE cannot load.

Source/dev builds need the LocalVQE runtime built once with ./scripts/build_localvqe.sh (the model is committed; the dylibs under native/MuesliNative/LocalVQE/lib/ are not). Without that step, packaging warns and the app falls back to DTLN. See CONTRIBUTING.md.

Models download on demand from HuggingFace. Manage them from the Models tab in the dashboard.

Permissions

Muesli needs these macOS permissions (guided during onboarding):

Permission	Why
Microphone	Record audio for dictation and meetings
System Audio Recording	Capture call audio from Zoom/Meet/Teams
Accessibility	Simulate Cmd+V to paste transcribed text
Input Monitoring	Detect hotkey presses globally
Camera (implicit)	Detect webcam activation for meeting detection
Calendar (optional)	Show upcoming meetings from Google Calendar

Tech Stack

Component	Technology
App	Swift, AppKit, SwiftUI
Primary ASR	FluidAudio and FluidInference models (Parakeet TDT, Nemotron 3.5, SenseVoice Small, and Qwen3 ASR on CoreML/ANE)
Cohere ASR	Cohere Transcribe (FP16 encoder + INT8 decoder on CoreML)
Indic ASR	AI4Bharat IndicConformer RNNT CoreML backend
Gemma ASR / cleanup	Google LiteRT-LM with Gemma 4 E2B (Metal GPU decoder + CPU audio encoder)
Whisper ASR	WhisperKit (CoreML/ANE)
Voice activity	Silero VAD via FluidAudio (streaming, event-driven)
Speaker diarization	pyannote via FluidAudio (CoreML on ANE)
Camera detection	CoreMediaIO property listeners (event-driven)
System audio	CoreAudio process tap by default; ScreenCaptureKit (`SCStream`) fallback
Meeting notes	OpenAI / OpenRouter (BYOK), ChatGPT subscription (OAuth), or Ollama
Calendar	Google Calendar API (OAuth 2.0)
Sync	CloudKit private database for text-only iCloud sync
Automation	Computer Use planner and post-meeting executable hooks
Export	PDF (NSPrintOperation, paginated US Letter) + Markdown
Word correction	Jaro-Winkler similarity (native Swift)
Storage	SQLite (WAL mode)
Signing	Developer ID + hardened runtime (notarization ready)

Contributing

Contributions welcome! To get started:

git clone https://github.com/Muesli-HQ/muesli.git
cd muesli
swift build --package-path native/MuesliNative -c release
swift test --package-path native/MuesliNative
./scripts/test_packaged_cli.sh

1,148 tests covering model configuration, custom word and phrase matching, filler removal, transcription routing, data persistence, CLI contract/path-resolution logic, speaker diarization alignment, token consolidation, camera-based meeting detection, CoreAudio system capture, ChatGPT OAuth logic, Ollama summaries, update-flow policy, launch at login, paste/clipboard safety, meeting export, meeting navigation, upcoming-meeting window behavior, and Google Calendar URL extraction.

Current test scope:

Covered by tests: CLI command contract generation, CLI path-resolution logic, SQLite read/write behavior, note-state classification, meeting/dictation retrieval/update flows, update-flow policy, CoreAudio cleanup, paste/clipboard safety, launch at login, Ollama summary routing, and Computer Use planner foundations.
Not covered by Swift unit tests: app-bundle packaging and copying muesli-cli into /Applications/Muesli.app/Contents/MacOS.
Packaging is verified by scripts/test_packaged_cli.sh, which builds an isolated app bundle, checks that Contents/MacOS/muesli-cli exists and is executable, and runs muesli-cli spec from the packaged path.

Please open an issue before submitting large PRs.

Support

If Muesli saves you time, consider supporting development:

Acknowledgements

Muesli has been possible because of the generosity of companies such as:

FluidAudio — CoreML speech models for Apple devices (Parakeet TDT, Qwen3 ASR, Silero VAD, speaker diarization)
localai-org/LocalVQE — on-device acoustic echo cancellation for meeting transcription
WhisperKit — Swift Whisper inference on CoreML/ANE
Core Audio by Apple — system audio process taps
ScreenCaptureKit by Apple — system audio fallback capture
NVIDIA Parakeet — FastConformer TDT speech recognition model
Cohere Transcribe — 2B parameter autoregressive ASR (#1 Open ASR Leaderboard)
Qwen3-ASR — Multilingual speech recognition (52 languages)
AI4Bharat IndicASR — IndicConformer multilingual ASR model for Indian languages
Google LiteRT-LM — Native on-device Gemma runtime with Swift APIs and Metal acceleration
Gemma 4 E2B LiteRT-LM — Experimental multimodal transcription and cleanup model
pyannote — Speaker diarization (via FluidAudio CoreML conversion)

License

MIT — free and open source.

Resources

Apple Neural Engine speech-to-text on Mac — how Muesli uses Apple Silicon, CoreML, and local ASR for fast dictation.
Local speech-to-text glossary — ASR, VAD, diarization, acoustic echo cancellation, Parakeet, Whisper, and Qwen3 ASR.
Best dictation apps for Mac — a practical comparison of Mac dictation tools.
Offline dictation for Mac — why local-first voice typing matters.
Local meeting transcription for Mac — meeting notes without adding a bot.

Name		Name	Last commit message	Last commit date
Latest commit History 1,261 Commits
.cursor		.cursor
.github		.github
.openhands/microagents		.openhands/microagents
Context		Context
assets		assets
design-system		design-system
docs		docs
native/MuesliNative		native/MuesliNative
scripts		scripts
skills		skills
.gitignore		.gitignore
AGENTS.md		AGENTS.md
CLAUDE.md		CLAUDE.md
CONTRIBUTING.md		CONTRIBUTING.md
DCO		DCO
LICENSE		LICENSE
README.md		README.md
REVIEW.md		REVIEW.md
vercel.json		vercel.json

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Muesli

What is Muesli?

Dictation

Meeting Transcription

Features

Install

Download (recommended)

Homebrew

Build from source

Agent CLI

What agents should do

Commands

Audio transcription

Dictionary import and export

JSON contract

Notes for agent authors

Models

Permissions

Tech Stack

Contributing

Support

Acknowledgements

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Muesli

What is Muesli?

Dictation

Meeting Transcription

Features

Install

Download (recommended)

Homebrew

Build from source

Agent CLI

What agents should do

Commands

Audio transcription

Dictionary import and export

JSON contract

Notes for agent authors

Models

Permissions

Tech Stack

Contributing

Support

Acknowledgements

License

Resources

Star History

About

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Resources

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