Free alternative to Wispr Flow, Superwhisper, and Monologue
Free & fast alternative to Wispr Flow. Contribute to zachlatta/freeflow development by creating an account on GitHub.
Free alternative to Wispr Flow, Superwhisper, and Monologue launched on February 16, 2026 with 277 votes, #90 of 16,627 launches that month and more than 99% of that year's launches.
In plain words
This is an open-source speech-to-text tool designed as a free alternative to commercial transcription software like Wispr Flow, Superwhisper, and Monologue. It converts spoken words into written text and is intended for users seeking transcription functionality without subscription costs. The project is hosted on GitHub, making the code available for review and modification by the community.
written from the facts on this page · September 2026
From the sources
Free and open source alternative to Wispr Flow , Superwhisper , and Monologue . ⬇ Download FreeFlow.dmg Works on all Macs (Apple Silicon + Intel) FreeFlow is a free Mac dictation app inspired by Wispr Flow , Superwhisper , and Monologue . It gives you fast AI transcription, context-aware cleanup, and voice-driven text editing without a monthly subscription. Edit Mode lets you highlight existing text and transform it with a spoken instruction, like "make this shorter" or "turn this into bullets." Enable it in settings, then use your normal dictation shortcut on selected text, or choose Manual mode to require an extra modifier key. There is no FreeFlow server, so FreeFlow does not store or…from github.com
Does a similar job
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BetterWispr – Free, open-source dictation for Mac12d ago · betterwispr.com · ▲220Hold a shortcut, speak, and BetterWispr types clean text into any Mac app. Local speech models, a style for each app, meeting notes and insights. Free and open source, with no account required.



- OOOWhisper – Ollama for realtime speech-to-text2025 · docs.hyprnote.com · ▲289
Hello everyone. This is Yujong from the Hyprnote team (https://github.com/fastrepl/hyprnote). We built OWhisper for 2 reasons: (Also outlined in https://docs.hyprnote.com/owhisper/what-is-this) (1). While working with on-device, realtime speech-to-text, we found there isn't tooling that exists to download / run the model in a practical way. (2). Also, we got frequent requests to provide a way to plug in custom STT endpoints to the Hyprnote desktop app, just like doing it with OpenAI-compatible LLM endpoints. The (2) part is still kind of WIP, but…
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