You're three design docs deep at 11pm, explaining the payment settlement logic to an engineer who just joined the team. You're speaking fast, thinking out loud, and the words are flowing naturally. Then your dictation tool hits its cap. Mid-sentence. Mid-thought.
You're suddenly back to typing, and the thinking stops. The prose fragments. You tell yourself you'll clean it up in the morning. You never do.
This happened to me on every voice tool that mattered enough to try. Whisper.ai's free tier. Wispr Flow's free tier. Superwhisper's free tier. They all had a limit. Usually 2,000 words on free. Wispr Flow charges $14 a month to uncap it. Superwhisper is $8.49 a month. That seems like the cost of voice dictation. It is not.
The real cost is not the speech-to-text
Here's what I discovered: cloud-based dictation tools price themselves the same way Netflix prices streaming. The speech-to-text model, usually OpenAI Whisper or a fine-tuned variant, costs almost nothing to run. It has been commodity-priced for three years.
Whisper-large-v3 achieves 96.3% word-error rate on LibriSpeech. That model has not improved meaningfully since 2023. The cost to run it has gone down.
So why does Wispr Flow charge $14 a month? Because they're paying for the infrastructure to serve it, store your transcriptions, route your audio, run their cleanup models, and keep the service alive. That is a legitimate business. But you are paying for their backend, not because speech-to-text is expensive.
If speech-to-text costs almost nothing, why cap it?
The alternative is to run Whisper on your device. Locally. No cloud. No word counter. No metering. No variable backend cost.
Recitey does this. Runs Whisper locally, on your laptop. Zero variable cost to run it, which means zero reason to cap words or count them. The free tier is uncapped because uncapping it does not cost them anything.
The paid tier is for something else: the rewrite engine. The part that polishes your rough draft into clean, structured prose. That part requires GPU time and a backend. That part actually costs money to deliver. So they price the part that is expensive.
Why this split matters for developers specifically
Your workflow is not the same as a general user. You are not recording voice memos about groceries. You are dictating 400-word explanations of why a payment retry is timing out at 11pm. You are voice-recording PR descriptions and code review comments. You are explaining the shape of a data model to Cursor and asking Claude to build it. Long-form intent, not short-form notes.
That intent matters. You cannot type it as fast as you think it. Dictation gets you 80% there. The last 20% is the rewrite, turning rough speech into clean words. "Uh, so basically, the settlement batching is, uh, we need to make sure that we never process the same batch twice because of idempotency" becomes "Settlement batching requires idempotency guards to prevent double-processing in asynchronous failures."
Most developers I know hit this ceiling: they find themselves repeating design docs into Slack threads, PRs, Linear tickets, and Notion because voice capture is faster than writing but cloud dictation caps at 2,000 words. The moment you stop mid-doc to switch tools, the flow breaks.
Knowing that split is real, that dictation and rewriting are two different steps, is how you choose the right tool. Most commercial voice tools bundle them. Wispr Flow does. Superwhisper does. You pay for both all the time, whether you need the rewrite or not. And you hit a word cap that breaks your thinking flow.
Recitey separates them. Whisper is free and uncapped because it runs locally and costs nothing per word. The rewrite is paid because it is a backend. You can dictate without limits. You only pay if you want the cleanup. You never lose a design doc to a word cap again.
The privacy piece is not secondary for code
One more thing: if you are working with code, IP concerns are not theoretical. Cloud dictation means your prompts leave your device. Your design docs travel to a server. Your incident postmortems get transcribed in someone's datacenter.
Most developers do not realize they are making this choice. They see "voice dictation" and think "faster input." They do not think "my architectural explanations now live in external storage." They do not consider that cloud platforms have data retention policies, compliance obligations, or (rarely) breaches.
Running Whisper locally means nothing leaves your device except your final text. That is not a marketing feature. That is infrastructure. For a fintech developer, or anyone working with regulated data, this matters more than speed.
The latency trade-off is real
Local dictation is not faster than cloud dictation. Cloud dictation has lower latency because it runs on a server farm. Local Whisper runs on your laptop. On a modern laptop, Whisper processes roughly 5 to 8 seconds of latency per 30 seconds of audio. That is real. That is a cost.
If you are dictating short messages, that latency is not worth it. Slack messages. Quick notes. For those, cloud tools win.
If you are dictating long-form, design docs, code explanations, PR descriptions, incident postmortems, the latency becomes invisible. You spend 5 seconds waiting while you read back what you said or grab water. The latency matters less than the freedom. You gain uncapped dictation. You keep your IP local. You do not get charged per word. You do not lose a thought to a word cap.
That trade is worth making once. Once you make it, you notice every cloud tool that hits a cap.