Hi r/windowsapps,

I just released TypeWhisper 1.0 for Windows: https://www.typewhisper.com

It is an open-source speech-to-text app for system-wide dictation, file transcription, and text workflows.

The idea is simple: press a hotkey, speak, and insert the final text into whatever app you are using. You can use local transcription models when privacy matters, or configure cloud engines/plugins when speed or accuracy matters more.

A few things it supports today:

• System-wide dictation with hotkeys
• Audio/video file transcription
• Local and cloud transcription engines
• Workflows for cleanup, rewriting, translation, and formatting after transcription
• Searchable transcription history
• Snippets, dictionary terms/corrections, and plugin support
• x64 and ARM64 Windows builds

I tried to make it useful for real daily writing instead of just a demo: notes, messages, GitHub issues, longer text, translation, and app-specific workflows.

Would love honest feedback, especially on first-run setup, local model setup, rough edges, or anything that feels confusing.

Hi r/macapps,

I build TypeWhisper, a macOS dictation and text automation app. I just shipped 1.5.0 as the new stable release.

Problem

I use dictation a lot, but the frustrating part is not just speech-to-text accuracy. It is everything around it:

• text insertion behaves differently in Terminal, Slack, Mail, browsers, writing apps, and Electron apps
• sometimes I want local-only transcription, sometimes a faster cloud/API engine is fine
• many dictation flows still leave me cleaning up punctuation, spacing, names, numbers, or formatting by hand
• advanced workflows often require copy/paste through several apps

TypeWhisper is my attempt to make that workflow more native and controllable on macOS.

What it does

• system-wide push-to-talk or toggle dictation
• local and cloud transcription engines
• file transcription for audio/video, including SRT/WebVTT export
• Workflows that can run by app, website/domain, hotkey, or fallback
• dictionary corrections, learned replacements, snippets, and searchable history
• plugin support, local HTTP API, CLI, widgets, and watch folders

What changed in 1.5.0

The main 1.5 work was making day-to-day dictation less brittle:

• app-aware insertion with better spacing, sentence position, terminal paste behavior, and rich-text target handling
• improved local model handling, including MLX memory controls, idle auto-unload, and stalled model-download recovery
• better dictionary learning and number normalization
• broader provider and plugin coverage
• reliability fixes for hotkeys, indicators, recording, uploads, workflows, fullscreen apps, and plugin metadata

One example setup: Terminal gets raw plain-text insertion, Slack uses a fast engine with auto-submit, and Mail can run a workflow that cleans up or rewrites the text before insertion.

Comparison

The closest apps people usually compare this with are Apple Dictation, Wispr Flow, Superwhisper, and MacWhisper. I think they are all useful, but they optimize for different people.

Apple Dictation

Apple Dictation is the best answer if you want something built in, free, and simple. For short messages it can be enough.

TypeWhisper is for the cases where I want more control: choosing the transcription engine, keeping a searchable history, applying dictionary corrections, running Workflows, processing text before insertion, or changing behavior per app/site.

Wispr Flow

Wispr Flow feels very polished if your main goal is: speak naturally, have the app clean it up, and get finished writing everywhere across desktop and mobile. Their positioning is very consumer-product focused: fast dictation, AI commands, auto-edits, cross-device support, and a simple free-to-paid path.

TypeWhisper is less about one managed voice-writing experience and more about control. It is open source, macOS-native, supports local and cloud engines, has Workflows, app/site routing, plugins, CLI/API automation, file transcription, dictionary learning, snippets, and local model controls.

So I would frame it like this: if you want the smoothest "just talk and it writes nicely" experience across devices, try Wispr Flow. If you want a macOS dictation system you can inspect, route, extend, and automate, TypeWhisper is closer to that.

Superwhisper

Superwhisper is probably the closest philosophical comparison. It also focuses on voice-to-text in any app, offline and cloud recognition, custom AI modes, 100+ languages, and polished AI text transformation. It has a strong cross-platform story too.

Where TypeWhisper tries to differ is the power-user surface: GPLv3 source, community plugins, bundled integrations, local HTTP API, CLI, watch folders, app-aware insertion rules, workflow triggers, and explicit control over local/cloud providers. I am trying to make it feel less like "a dictation box with AI modes" and more like a programmable text pipeline for macOS.

Superwhisper is likely a better fit if you want a mature, polished, cross-platform dictation product with strong default AI modes. TypeWhisper is likely a better fit if you care about open source, local-first options, automation, and deeply configurable per-app behavior.

MacWhisper

MacWhisper is very strong if your main job is transcribing audio and video files on a Mac. It also has dictation, ChatGPT prompt processing, and app-specific prompts in the direct version.

TypeWhisper overlaps with that, but its center of gravity is system-wide dictation plus automation: Workflows, app-aware insertion, provider choice, plugins, local APIs, dictionary learning, snippets, and live text insertion behavior. I still think MacWhisper is a great app if file transcription is the core use case. TypeWhisper is aimed more at people who dictate into many apps all day and want that behavior to be programmable.

Short version

• Use Apple Dictation if you want built-in and simple.
• Use Wispr Flow if you want the most polished managed voice-writing experience across devices.
• Use Superwhisper if you want a mature AI dictation product with strong cross-platform support and AI modes.
• Use MacWhisper if file transcription is your main workflow.
• Use TypeWhisper if you want open-source macOS dictation with local/cloud engines, app-aware insertion, Workflows, plugins, CLI/API automation, and more control over what happens after you speak.

The tradeoff is that TypeWhisper is more configurable. I am working on making the defaults feel simpler, but the app is intentionally built for people who want to tune their dictation workflow instead of treating it as a black box.

Privacy

Local transcription is available, and local prompt processing on Apple Silicon is available through verified Gemma 4 MLX models. Cloud transcription and LLM providers are optional and only used when configured.

Pricing

TypeWhisper is open source under GPLv3.

Installing and running an unmodified GPL copy is free, including personal use and GPL-compliant internal/commercial use.

Commercial licenses are for proprietary distribution, non-GPL use, procurement, invoicing, or support:

• Individual: 5 EUR/month or 99 EUR lifetime
• Team: 19 EUR/month or 299 EUR lifetime
• Enterprise: 99 EUR/month or 999 EUR lifetime

Pricing page: https://www.typewhisper.com/pricing

Links

• Website: https://www.typewhisper.com
• GitHub: https://github.com/TypeWhisper/typewhisper-mac
• Release: https://github.com/TypeWhisper/typewhisper-mac/releases/tag/v1.5.0
• Homebrew: brew install --cask typewhisper/tap/typewhisper

I would appreciate feedback from people who already use dictation heavily on macOS, especially around Workflows, local models, and app-specific insertion behavior.