Developers writing design documents, PR descriptions, and incident postmortems hit the same wall: you voice-draft naturally, then realize you've hit a word cap and have to switch to typing. Or you explain the architecture clearly on a call, then spend 12 minutes rewriting the follow-up message to sound right. If you've exhausted your monthly word budget on a cloud transcription tool mid-thought, you know the moment.
The reason? Infrastructure.
Cloud Transcription Has a Hidden Variable Cost
Wispr Flow charges $14 per month for 2000 words. Willow's $12 for 5000. Superwhisper is $8.49. These aren't arbitrary prices.
When you speak into these tools, your voice travels to a cloud server, gets processed by a speech-to-text model, logged, optionally refined, then sent back to your device. Every utterance incurs a compute cost. The vendor caps free tiers not to drive conversions, but to manage infrastructure spend.
This is smart business. It's also not the only way to build a voice writing tool.
Local Whisper Runs on Your Device
Whisper is OpenAI's open speech-to-text model. It can run entirely on your machine. You speak, your device transcribes, done. No voice travels to a cloud server. No utterance gets metered.
Which means there's no variable cost per word.
Recitey uses local Whisper. The free tier has no word cap. Not because the company absorbs a loss. But because there is no infrastructure cost to cap. You're not paying for vendor compute. Your device does the work.
This is a structural difference, not a marketing claim.
Code Context Shouldn't Travel to the Cloud
Marcus works on payment settlement logic at a Series B fintech. He drafts design docs late at night, writes PR descriptions with code context, documents bugs in Slack. A year ago, he'd considered cloud dictation tools. Then he thought about it: his voice carries code snippets, variable names, architecture decisions, security context. That's intellectual property.
He stopped using cloud transcription. Stuck with typing.
Earlier this year, he switched to Cursor specifically because the autocomplete reduced the number of voice rewrites he had to make, each session felt tighter, more complete. But he still couldn't draft long-form docs by voice because he didn't trust the cloud option.
Local Whisper changes this. The speech-to-text never leaves his device. There's no server to worry about. No vendor logging his technical context.
The Difference Between Structural and Performative
Most voice tools announce privacy features like they're doing you a favor: "Your data is encrypted!" "We don't retain transcripts!" This is performative. The server still exists. The logging infrastructure is still there. You're just trusting the vendor's promise that they won't look.
Local Whisper is structural. If the inference runs on your device, there is no cloud infrastructure to log or retain data. You don't have to trust a privacy announcement because there's nothing to announce. The system doesn't phone home for transcription.
It works across Windows, Slack, email, browsers, terminal, every app via system clipboard. Not because there's clever cloud integration. But because the transcription itself doesn't require the cloud.
What Disappears When There's No Metering
When you can't hit a word cap, you stop planning your thoughts around tool constraints.
- No rewriting fragments across three different tools because you exhausted the free tier on the first one.
- No losing a design doc's thread because you switched to typing midway through.
- No speaking faster than you type, then abandoning the voice draft because it feels incomplete.
- No wondering if your next utterance will tip you over the monthly budget.
You just write by voice. Like thinking.
The cost isn't in the technology. It's in the infrastructure that distributes it. Recitey's free tier costs nothing to run because there is no infrastructure. Local means no metering, no variable cost, no vendor tax on every word you say.
That's the entire architecture.