The best offline transcription software for Mac and Windows

Notta Privacy Mode: our top pick for offline transcription

Notta Desktop's Privacy Mode is our top pick because it handles the two jobs offline tools usually make you choose between: recording meetings and transcribing files. In Privacy Mode it records Zoom, Teams and Google Meet calls bot-free — no visible participant joining your call — and transcribes both those meetings and imported audio and video files with a local engine, with no minute limits while you're offline. The offline engine covers English, Japanese, Simplified Chinese and Cantonese (1 GB download, 4 GB RAM minimum), and an Apple Speech Analyzer engine adds 11 languages on macOS 26+. Cloud summaries are paused in this mode, so your audio and transcripts stay on your machine.

When a meeting isn't sensitive, the same app switches back to Notta's cloud workspace with AI summaries and search — a flexibility none of the purely offline tools offer. One thing to plan for: the app performs a periodic online licence check, so it needs occasional internet access even though transcription itself stays local. It runs on both Mac and Windows, which makes it the most practical option if you want local transcription without giving up a workspace for everything else.

Is it worth paying for a Mac transcription app?

MacWhisper's free version transcribes files on the Mac, on the device, with no upload. That alone makes it worth installing. The Pro licence (€65 once, not a subscription) is worth paying for if any of the following apply: you need speaker labels, because Nemotron diarization is a Pro feature; you transcribe in bulk, because batch transcription and watch folders are Pro; you want speed, because the faster Parakeet v2/v3 and Qwen3-ASR models are Pro; or you want to record meetings, because system-audio and meeting recording are Pro too. YouTube transcription is also Pro.

Two caveats. First, the free tier limits some models to Pro users — the developer notes that "some models are only fully available for Pro users" — so the free experience is real but not the whole catalogue. Second, MacWhisper offers optional cloud engines and AI services; if your goal is offline privacy, leave those switched off. With a 7-day refund window and a 25% discount for journalists, students and non-profits, the risk in trying Pro is low. If you're set on the Mac but want a one-time purchase without a subscription anywhere in the product, Aiko at $24 is the simpler alternative, at the cost of speaker labels.

What is the best offline transcription software for Windows?

There is no MacWhisper for Windows — it's a macOS-only app. The closest equivalents are both free. Buzz is the general-purpose Windows choice: an MIT-licensed app with a Windows installer that runs Whisper, whisper.cpp and Faster Whisper locally and exports TXT, SRT and VTT. Expect a SmartScreen warning when installing, because the installer is unsigned.

For interviews with several speakers, noScribe is the better Windows pick. It pairs faster-whisper with pyannote speaker separation, runs completely locally on your computer, and includes a built-in editor for checking the transcript against the audio — a workflow built for qualitative research and journalism rather than casual use.

If you want a Windows app that also handles meetings, Notta Desktop's Privacy Mode runs on Windows as well as Mac: it records calls bot-free and transcribes them with the local engine (English, Japanese, Simplified Chinese and Cantonese). Superwhisper also runs on Windows and adds dictation to file transcription. The one thing to check in any Windows tool is the local-versus-cloud engine setting — Buzz, for example, can use OpenAI's cloud API, and you need to turn that off to stay offline.

Which offline software labels who is speaking?

Speaker labels are the difference between a transcript you can quote and a wall of text. Here is what each offline tool offers:

For recorded interviews, noScribe's combination of pyannote labelling and a built-in audio-synced editor makes it the strongest free option for checking who said what. On the Mac, MacWhisper Pro's diarization works, though one reviewer found the beta could sometimes mistake one person for multiple speakers — so verify labels against the audio for anything you'll quote. For live meetings, Notta's Privacy Mode attributes speech to participants as it records, which is more reliable than post-hoc diarization when you know who is on the call. We cover this topic in more detail in our guide to transcription with speaker identification.

Can offline software record Zoom and Teams meetings?

Yes, and this is where the tools genuinely differ. MacWhisper Pro records system audio and named meeting apps, so you can capture a Zoom or Teams call and transcribe it locally afterwards. Buzz records the microphone, which works for in-person conversation but is a clunky way to capture a video call.

Notta Desktop's Privacy Mode is the strongest option if meetings are your main workload. It records Zoom, Teams and Google Meet calls bot-free — no visible participant, no "recording in progress" announcement from an outsider — and transcribes them with the local engine, with no minute limits while you're in Privacy Mode. Cloud summaries are paused in this mode, so nothing leaves your machine. When a meeting isn't sensitive, the same app switches back to Notta's cloud workspace for AI summaries and search, which is a flexibility none of the purely offline tools offer.

One thing to plan for: Notta performs a periodic online licence check, so the app needs to reach the internet occasionally even when transcription itself stays local. If you need step-by-step guidance on consent and workflow for confidential meetings, see our guide on how to transcribe audio locally, and for the recording mechanics, how to record a Zoom meeting.

How accurate are local Whisper models compared with cloud services?

A large Whisper model running on your own computer is close to the cloud engines on published benchmarks — but the gap depends on how the model is run. Artificial Analysis's speech-to-text leaderboard (read 29 October 2026) shows Whisper Large v3 scoring 4.1% word error rate hosted on fal.ai, 4.5% on Together AI, and 10.1% on Replicate. Same model, different setups: how an app runs Whisper matters as much as which model it uses.

Two practical takeaways. First, small models and weak hardware cost accuracy — if your machine can only run a small model, expect noticeably more errors, especially on names and numbers. Second, newer architectures are changing the speed equation: the Open ASR Leaderboard paper (arXiv 2510.06961) explains why Parakeet-style models with CTC and TDT decoders transcribe faster than Whisper's encoder-decoder approach, which is why MacWhisper Pro's Parakeet option and Vibe's Parakeet support matter for long files.

Real-world timing bears this out. MacStories transcribed a 34-minute file in 1:41 with MacWhisper's Large V3 Turbo and in 0:45 with Apple's SpeechAnalyzer on the same machine, with similar quality — and a reviewer reported a 17-minute video transcribed in about 90 seconds on an M4 Max Mac Studio. If most of your audio is English and you're on a recent Mac, the local-versus-cloud accuracy gap is small enough that privacy is rarely a quality sacrifice. For a broader comparison of cloud options, see our guide to the best transcription software.

What hardware do you need to transcribe offline?

An Apple-silicon Mac or a recent Windows laptop with 16 GB of RAM runs the large models comfortably; 8 GB limits you to smaller ones. MacWhisper's system note is explicit: "To use the Medium and Large models your Mac should have more than 8GB of RAM." Buzz now requires Apple silicon on the Mac (Intel Macs are supported up to version 1.4.5). At the other end of the scale, Notta's offline engine asks for a 1 GB download and a 4 GB RAM minimum, because it runs a smaller, dedicated local model rather than the full Whisper catalogue — a reasonable trade if you want meeting capture on a modest laptop rather than maximum accuracy on every language.

If you're buying a machine specifically for local AI work, our guides on how much RAM you need for a local LLM and what an NPU is cover the details. The short version: for Whisper-class transcription, RAM and memory bandwidth matter more than CPU core count, and Apple silicon's unified memory is why Macs punch above their weight here. Windows buyers should prioritize a recent laptop with 16 GB of RAM and a modern GPU or NPU if they plan to run large models regularly.

Is offline transcription fully private?

Mostly, with three things to check. First, licence checks: some apps phone home periodically even when transcription is local. Notta's Privacy Mode performs a periodic online licence check, so plan for occasional connectivity even though your audio stays on the device. Second, optional cloud features: MacWhisper and Superwhisper both offer cloud engines and AI API integrations alongside their local models, and Buzz can use OpenAI's cloud API. In each app, find the setting that selects the local engine and make sure the cloud option is off — we screenshot these settings during testing because they're not always obvious. Third, backups: a transcript stored only on your laptop is one spilled coffee away from disappearing, so decide deliberately where encrypted backups live.

The apps that run completely locally with no cloud path at all — noScribe's "runs completely locally on your computer" and Vibe's "fully offline transcription, no data ever leaves your device" — are the safest defaults for the most sensitive audio. Notta's Privacy Mode sits in the middle: transcription and recording stay on the machine and cloud summaries pause, but the app is part of a cloud product, so it suits teams whose sensitivity threshold is "no upload of this meeting" rather than "never touches a cloud vendor's servers at all." For the full decision framework, see our guide to local transcription versus cloud.