Fully Offline Voice to Text: No Cloud, No Subscriptions, No Compromises
Fully Offline Voice to Text: No Cloud, No Subscriptions, No Compromises
Every mainstream dictation tool sends your voice to the cloud. Windows Voice Typing, Otter, Dragon (in most configurations), even “Hey Siri” on your Mac. Your audio leaves your device, gets processed on someone else’s server, and comes back as text.
For most people, that’s fine. For some people, it’s a dealbreaker.
Who actually needs offline dictation?
This isn’t a theoretical privacy concern. These are real use cases where cloud-based transcription is either risky or prohibited:
Legal professionals. Attorney-client privilege means client conversations can’t be routed through third-party cloud services. A lawyer dictating case notes needs to know, with certainty, that the audio never leaves their machine. “We encrypt it in transit” isn’t good enough when the standard is “it never left.”
Healthcare workers. HIPAA compliance gets complicated fast when patient information is being sent to cloud APIs. Even if the cloud provider is HIPAA-compliant, the dictation app routing audio through them needs a BAA (Business Associate Agreement). Most consumer dictation tools don’t offer one.
Security-conscious organizations. Air-gapped environments exist for a reason. Government contractors, defense firms, and security research teams often work on machines with no network access. Dictation needs to work without a connection, period.
Anyone on unreliable internet. Planes, trains, rural areas, coffee shops with terrible WiFi. Cloud dictation fails when the connection drops. Offline dictation works the same whether you’re in a data center or a national park.
People who just value privacy. You don’t need a legal or compliance reason to not want your voice recorded on someone else’s infrastructure. “I’d rather not” is a perfectly valid reason.
How offline voice-to-text actually works
The technology that makes this possible is Whisper, OpenAI’s open-source speech recognition model. Released in 2022 and continuously improved since, Whisper runs entirely on your local hardware.
Two things matter for local Whisper:
Model size determines accuracy. The tiny model (39MB) is fast but makes more mistakes. The base model (74MB) is a good balance. The large model (~1.5GB) is the most accurate but needs serious hardware. For real-time dictation, you want something in the middle.
Your hardware determines speed. Modern CPUs handle the smaller models fine. A decent GPU makes everything faster. Apple Silicon Macs are particularly good at this, the Neural Engine was designed for exactly these workloads.
The practical setup
There are a few ways to get fully offline dictation working:
Option 1: Raw Whisper (free, requires terminal comfort)
Install Whisper, record audio with any tool, run it through the model. This works but it’s not real-time dictation. You record, process, get text. Good for batch transcription (interviews, lectures), not for “I’m dictating an email right now.”
Option 2: Whisper-based desktop apps
Several apps wrap Whisper in a usable interface. The quality varies dramatically. Some are Electron bloat that barely works. Some are genuinely good.
Option 3: Finch Privacy Mode
Finch’s Privacy Mode is a single toggle that cuts all network connectivity. Zero cloud. Audio is processed by a local Whisper model (Speed mode at 31MB or Quality mode at 190MB), transcribed on your device, and the audio is never saved to disk.
The workflow: press your hotkey, speak, release, clean text appears. Same as the cloud mode, just running locally. The latency is slightly higher (local processing vs. cloud API), but on any modern machine it’s well under a second for most utterances.
What you give up in Privacy Mode: the AI text cleanup that normally runs through Claude or GPT to remove filler words and fix grammar. The local Whisper model does the transcription, but the polish step requires an LLM. You get raw (but accurate) transcription instead of cleaned-up text.
For most offline use cases, that’s the right tradeoff. The transcription is accurate enough that light manual editing is faster than the cloud round-trip you’re trying to avoid.
Performance expectations
Honest numbers from real hardware:
| Hardware | Model | Latency (10-second clip) |
|---|---|---|
| M1 MacBook Air | Speed (31MB) | ~0.8 seconds |
| M4 Mac Mini | Quality (190MB) | ~0.5 seconds |
| Intel i7 12th gen (no GPU) | Speed (31MB) | ~1.2 seconds |
| Intel i7 + RTX 3060 | Quality (190MB) | ~0.4 seconds |
These are real-world numbers, not benchmarks. Your mileage varies with ambient noise, speaking speed, and what else your machine is doing.
The Speed model (31MB) is good enough for everyday dictation. Clear speech, reasonable pace, not too much background noise. The Quality model (190MB) handles accents, technical terms, and noisy environments better.
What offline dictation can’t do (yet)
Being honest about the limitations:
Accuracy ceiling. Local models are very good but not quite as accurate as the best cloud APIs (Groq’s hosted Whisper, Deepgram’s Nova). The gap is small and shrinking, but it exists. If you need 99%+ accuracy on medical terms, the cloud APIs are still better.
AI cleanup offline. Removing filler words, fixing grammar, and reformatting text requires an LLM. Running a local LLM for this is possible (Ollama + a small model) but adds complexity and latency. Most people use cloud LLMs for cleanup and local Whisper for transcription, getting privacy for the audio while using cloud for text processing only.
Vocabulary adaptation. Cloud services learn from corrections over time. Local models are static. Finch’s personal dictionary helps (teach it your name, company names, technical terms), but it’s not the same as a model that adapts.
The privacy spectrum
Not everyone needs full offline. There’s a spectrum:
- Full cloud (Otter, cloud Dragon): Audio goes to cloud, text comes back. Convenient, least private.
- BYOK cloud (Finch default mode): Audio goes to a provider YOU choose. You pick Groq, Deepgram, or OpenAI. You read their privacy policy. The app doesn’t see your audio.
- Local transcription, cloud cleanup (Finch with local Whisper + cloud LLM): Audio never leaves your device. Only the resulting text goes to a cloud LLM for cleanup. Good middle ground.
- Full offline (Finch Privacy Mode): Nothing leaves your device. Zero network. Maximum privacy, slight accuracy tradeoff.
Pick the level that matches your actual risk. Most people are fine with BYOK cloud. If you’re handling privileged information, start at level 3 or 4.
Getting started with offline dictation
If you want to try fully offline voice-to-text:
- Download Finch ($49 once, 30-day money-back guarantee)
- Skip the API key setup during onboarding
- Enable Privacy Mode in settings
- Choose your local model (Speed for fast, Quality for accurate)
- Press your hotkey and start talking
No account needed. No API key needed. No internet needed. Your voice stays on your machine.
The technology for private, offline dictation exists today. It’s good. It’s getting better every few months. And there’s no reason to send your voice to someone else’s cloud if you’d rather not.