What is local speech to text?

Local speech to text means your voice is transcribed directly on your computer, not on a remote server. The audio never leaves your device, which means faster results and complete privacy.

Is local speech to text as accurate as cloud-based transcription?

Yes. MumbleFlow uses whisper.cpp, a port of OpenAI's Whisper model. Combined with hardware acceleration (Metal on Mac) and local LLM text cleanup, accuracy is comparable to cloud services.

Does MumbleFlow need internet to work?

No. MumbleFlow works completely offline. All speech recognition and text cleanup happens on your device using whisper.cpp and llama.cpp.

What hardware do I need for local speech to text?

Any Mac from the last 3-4 years with Apple Silicon or a recent Intel chip will run MumbleFlow smoothly. It uses Metal acceleration on macOS for fast performance.

LOCAL SPEECH TO TEXT THAT STAYS ON YOUR DEVICE

Most speech-to-text tools send your audio to a server somewhere. MumbleFlow does the opposite: everything runs locally on your Mac. Your voice is transcribed in sub-second time, then the audio is discarded. No upload. No latency from network round-trips. Just fast, private transcription.

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WHAT DOES “LOCAL” ACTUALLY MEAN?

When you use a cloud-based speech to text service like Google Speech API, AWS Transcribe, or even Apple's enhanced dictation, your audio gets sent over the internet to a data center. A server processes it, generates the text, and sends it back. This takes time, requires an internet connection, and means a third party has access to your audio.

Local speech to text flips that model. The speech recognition model lives on your computer. When you speak, the audio is processed right where it was recorded. Nothing goes over the wire. The transcription happens in milliseconds because there's no network hop, and the audio can be thrown away immediately because no external service needs it.

This used to be impractical. Running a high-quality speech model locally required expensive hardware and produced mediocre results. That changed with OpenAI's Whisper model and the whisper.cpp project, which made it possible to run Whisper efficiently on consumer hardware using CPU and GPU acceleration. MumbleFlow packages this into a clean desktop app that works like any other tool on your Mac.

CLOUD VS LOCAL: THE REAL TRADEOFFS

Factor	Local (MumbleFlow)	Cloud Services
Privacy	Audio never leaves your device	Audio uploaded to third-party servers
Speed	Sub-second (no network latency)	Depends on connection speed
Internet	Not required	Required for every transcription
Cost	$5 one-time	Monthly/per-minute billing
Accuracy	Whisper model + local LLM cleanup	Comparable (same model family)
Data retention	Zero. Audio discarded immediately	Varies. Often stored for training
Availability	Works on planes, subways, anywhere	Only where you have internet

WHY LOCAL PROCESSING MATTERS MORE THAN YOU THINK

YOUR VOICE IS BIOMETRIC DATA

Your voice is uniquely yours. It can identify you, reveal your emotional state, and even indicate health conditions. When you use a cloud speech service, you're handing over biometric data to a company whose data practices you likely haven't read. With local processing, that data stays exactly where it should: on your machine.

PROFESSIONAL CONFIDENTIALITY

If you work in law, healthcare, finance, or any field with confidentiality requirements, sending audio to a cloud service may violate compliance rules. Local transcription eliminates that risk entirely. What you dictate stays on your computer and nowhere else.

NO DEPENDENCY ON SERVERS

Cloud services go down. APIs get deprecated. Companies pivot or shut down. When your speech to text runs locally, none of that matters. MumbleFlow will keep working whether or not a server on the other side of the world is having a bad day.

HOW MUMBLEFLOW HANDLES LOCAL TRANSCRIPTION

Press your hotkey

Tap Fn (or your custom key) anywhere on your Mac. MumbleFlow starts listening instantly with a floating indicator.

whisper.cpp processes your speech

Your audio is fed directly to whisper.cpp running on your machine. Metal acceleration on Apple Silicon keeps it fast.

llama.cpp cleans up the text

A local language model handles punctuation, capitalization, and light grammar fixes. No cloud API calls.

Text appears at your cursor

The final text is pasted wherever you're typing. Works in every app: email, docs, Slack, code editors, anything.

Audio is discarded

The raw audio is thrown away immediately. It's never saved to disk, never uploaded, never logged.

FREQUENTLY ASKED QUESTIONS

Is local speech to text as accurate as cloud-based options?

Yes. MumbleFlow uses whisper.cpp, which runs the same Whisper model architecture that powers most modern transcription services. Combined with a local LLM for text cleanup, accuracy is on par with cloud solutions. The difference is that your audio never leaves your device.

What hardware do I need?

Any Mac from the last 3-4 years will work well. MumbleFlow uses Metal acceleration on Apple Silicon for the fastest performance. Intel Macs are also supported. Windows and Linux versions are coming soon.

What languages are supported?

MumbleFlow supports all 90+ languages that the Whisper model handles, with automatic language detection. You don't need to configure anything; just start speaking.

How does this compare to Apple's built-in dictation?

Apple's enhanced dictation sends audio to Apple's servers for processing. The basic offline mode is limited and less accurate. MumbleFlow uses a more capable model (Whisper) and adds local LLM-powered text cleanup, giving you better results without any cloud dependency.

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Comparison

KEEP YOUR VOICE LOCAL

Fast, accurate speech to text that never touches the cloud. $5 once.

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