Offline Transcription Software
Why It Finally Works
For years, local transcription meant slower and worse. That's changed. Here's what happened.
A Bit of Context
A few years ago, if you wanted accurate transcription, you had to upload your audio to someone's server. Local options existed, but they were noticeably worse. The trade-off was real.
Then a few things happened. OpenAI released Whisper as an open model. Apple shipped chips with dedicated AI hardware. Suddenly the same models that powered cloud services could run on a laptop.
We started building Whisper Notes around that time, mostly because we wanted it for ourselves. Turns out a lot of people were looking for the same thing.
What Changed
Three things used to make cloud transcription the obvious choice. All three have shifted.
Computing Power
The AI models that do transcription are large—hundreds of millions of parameters. Running them used to be slow and battery-draining on consumer hardware.
Apple's Neural Engine changed that. It's a dedicated chip for AI workloads, and it's in every M-series Mac and recent iPhone. Whisper Large v3 Turbo now runs comfortably on a MacBook Air.
On phones, we use smaller models that are optimized for mobile chips. They're not quite as accurate as the large model, but they're still better than most built-in dictation.
Accuracy
This one surprised us. We expected local models to be "good enough." They're actually quite good.
Whisper Large v3 has lower word error rates than most system dictation. And the gap between local and cloud APIs has gotten pretty small. For most use cases, you probably won't notice a difference.
That changes the calculation. If accuracy is comparable, the main reason to upload audio disappears.
Privacy
We're not here to scare you about cloud services. Most of them handle data responsibly.
But there's a difference between "they promise not to misuse it" and "they never had it." Your voice is biometric—unlike a password, you can't change it if something goes wrong.
With local transcription, your audio stays on your device. Not encrypted-then-uploaded. Just... stays. For some people that matters a lot. For others, maybe not. We built for the first group.
When to Use What
Local isn't always the right choice. Here's how we think about it.
Need real-time collaboration?
Cloud tools like Otter are built for that. Multiple people editing the same transcript needs a central server. That's a good use of cloud.
On Windows or Android?
Local AI is harder on those platforms—the hardware support isn't as mature. Dragon works for Windows. On Android, cloud services are usually the practical choice.
Need speaker identification?
Knowing who said what (diarization) requires additional models. Cloud services like Rev handle this well. Local tools are catching up, but it's still an area where cloud has an advantage.
Just need private, accurate transcription?
That's what we focused on. If your main concerns are privacy and accuracy, and you're on Apple hardware, local works well now.
What Whisper Notes Does
It runs Whisper Large v3 Turbo on your Mac, or a smaller optimized model on your iPhone. Your audio never leaves the device.
On Mac, transcription runs at about 10-15x real-time speed using the Neural Engine. A one-hour recording takes a few minutes. On iPhone it's slower, but still practical for most recordings.
It's $4.99 once, for both platforms. We don't run servers, so we don't need subscriptions. That's about it.
Get Whisper NotesThe Short Version
Local transcription used to be a compromise. Now it's a reasonable default for a lot of people.
If you need collaboration or work on non-Apple platforms, cloud services still make sense. If you mainly want accurate, private transcription on a Mac or iPhone, the local option has gotten pretty good.
We use Whisper Notes ourselves every day. It does what we needed it to do.
Try It Out
You can test it in airplane mode if you want to verify nothing gets uploaded. Everything works the same.
App Store • $4.99 • Mac and iPhone
One purchase covers both platforms.