You're 45 minutes into a 6,000-word design doc. Voice has been faster than your keyboard for explaining the architecture, the trade-offs, the edge cases. Then the word cap hits. The dictation stops. You switch back to typing. The thinking flow breaks. By the time you return to it the next morning, you've lost the thread and you're rewriting the whole thing anyway.
That friction isn't an accident. It's a business model. Wispr Flow, Willow, and Superwhisper all price around a word cap on the free tier. Wispr charges $14/month. Willow is $12. Superwhisper is $8.49. They all convert you by making free frustrating just enough that paying feels like relief.
Recitey's free tier has no word cap. It runs local Whisper on your device. That's the entire point.
Why This Matters for Your LLM Workflow
The work changed. You used to write code. Now you write prompts. Specs. Intent descriptions for Cursor. GitHub PR explanations. Slack threads that walk someone through a bug investigation. These are long-form, thinking-heavy, prose-forward tasks.
Typing these takes longer than it should. Voice is native to this. You explain the problem on a call and it takes 8 minutes. You write it down and it takes 30 minutes because writing forces you to pretend you know what you're saying before you've finished thinking.
Voice dictation used to be a typing accelerator. Now it's a thinking tool. And thinking tools don't work well with word caps. You need to think out loud for as long as the thought takes.
The Cloud Model Breaks Here
Wispr Flow, Willow, and Superwhisper all run transcription in the cloud. That gives them flexibility on the backend. They also get metered revenue: every transcription past the cap generates a billing event.
The problem isn't their implementation. It's the structure. If the transcription lives in the cloud, variable cost per word matters to the business model. A local model eliminates that cost entirely. They can afford uncapped free. But they have to absorb the GPU cost upfront, which changes the pricing conversation completely.
Recitey ships Whisper-large-v3 locally. It runs on your device. Zero variable cost per transcription. No metering. No word counter. The free tier and the pro tier share the same dictation engine; the difference is the rewrite polish (cloud-based grammar and tone cleanup, which is genuinely expensive to compute at scale).
The Trade-Off You Actually Get
You lose cloud backup of your raw dictations. You gain: no IP concerns, no data leaving your device during dictation, instant latency, permanent free access to the transcription layer. The accuracy is 96.3% on LibriSpeech, which is indistinguishable from cloud Whisper for most use cases. The human rewrite fixes edge cases faster than cloud perfection anyway.
You trade privacy-bleed for workflow ownership. Most developers prefer that trade.
Who Should Use What
Wispr Flow, Willow, and Superwhisper are good products for their actual audience: people who want dead-simple dictation on phones, who don't write long-form content, who value cloud sync and backup. They price fairly for that audience.
Recitey is built for developers, technical writers, and anyone whose workflow includes long-form thinking-by-voice. Marcus, a backend engineer at a fintech startup, works on design docs at 11pm in Cursor (chosen for its tab-complete that reduces voice rewrites). He refuses cloud transcription because design docs contain code IP. For him, local uncapped isn't a feature. It's the only acceptable option.
If you're writing specifications in Cursor, design docs in Notion, Slack threads explaining bug investigations, or PR descriptions that need full context, you're the audience. And the word cap isn't a feature. It's a limitation that exists only to push you to a higher tier.
Recitey says: thinking shouldn't have a meter.