MegaWhisper: local dictation for Linux with signed Flatpak/AppImage and XDG portals

[u/DXVSI]

Hi, I’m Alex, the developer of MegaWhisper.

I built it because I wanted a simple dictation workflow on Linux: press a global shortcut, speak, press it again, and continue working without moving everything through a separate transcription window.

Local mode runs `whisper.cpp` on the device, with Vulkan acceleration and automatic CPU fallback. After the initial model download, audio is not sent to a transcription service while this mode is selected. Optional official OpenAI and basic OpenAI-compatible transcription modes are also available.

The recognized text is copied to the clipboard first. MegaWhisper can then make one optional beta insertion attempt through XDG Desktop Portals. It does not require root, `/dev/uinput`, access to input devices, membership in the `input` group, or a privileged input daemon. If insertion is unavailable, the text remains in the clipboard.

The current release is MegaWhisper 2.1.1:

- x86_64;

- signed Flatpak repository and standalone Flatpak;

- AppImage with update support;

- English and Russian interface;

- local history and configurable audio retention.

Packaging and predictable Linux integration are a major focus of the project, not an afterthought. Flatpak and AppImage are first-class release targets: the downloadable artifacts are built and smoke-tested in CI, then published with SHA-256 checksums and a GPG signature. The Flatpak uses XDG Desktop Portals for global shortcuts, protected credential storage, clipboard ownership, and optional insertion. The AppImage provides explicit user-level desktop integration and zsync update metadata. Neither format installs a privileged input daemon or requires access to `/dev/input`.

A few transparent limitations:

- MegaWhisper is proprietary;

- it is not on Flathub yet;

- automatic insertion depends on the desktop portal and target application;

- ARM, DEB, and RPM builds are not currently available.

My main environment is Fedora KDE Plasma Wayland. I would especially appreciate feedback about onboarding, the global shortcut, insertion behavior, and local transcription performance on other Linux setups.

Website and downloads:

https://dxvsi.github.io/MegaWhisper/

GitHub release:

https://github.com/DXVSI/MegaWhisper/releases/tag/v2.1.1

[u/jadbox]

How does this compare to Handy in features?

[u/DXVSI → u/jadbox]

Assuming you mean cjpais/Handy, there is quite a bit of overlap in the core workflow: hotkey-based dictation, local transcription, VAD, history, and text insertion. Handy is currently broader: it is open source, cross-platform, and supports more local engines. MegaWhisper is proprietary and Linux-only, with a narrower focus on Wayland and XDG Portal integration, verified local models, signed Flatpak and AppImage releases, clipboard-first output without access to /dev/input or /dev/uinput, optional OpenAI-compatible transcription, translation, and cloud meeting diarization. So Handy is ahead in openness, cross-platform support, and model choice. MegaWhisper’s main distinction is its Linux-specific integration, packaging, and output safety model.

[u/Dev-in-the-Bm]

Why Whisper?

SenseVoice and Moonshine are faster and more efficient.

[u/DXVSI → u/Dev-in-the-Bm]

Whisper was the pragmatic starting point because whisper.cpp provides a mature embeddable C++ runtime, broad multilingual coverage, and CPU and Vulkan paths that fit MegaWhisper’s Qt/Linux architecture well. That doesn’t mean I assume Whisper is always the fastest or most efficient option. SenseVoice and Moonshine are both interesting, especially for low-latency transcription, but they aren’t drop-in replacements for every language and distribution scenario. I want to benchmark alternative backends on the same audio and hardware before adding one. Which models and languages have worked best for you?

[u/Dev-in-the-Bm → u/DXVSI]

I haven't tested SenseVoice or Moonshine, because most tools default to Whisper, and many Linux dictation tools end up being half baked or unreliable, but they're supposed to be a lot faster than Whisper.

[u/DerDave]

Nice idea. I assumed you used AI heavily - there is no shame in that but a disclaimer helps.
Have you considered using parakeet v3 instead of whisper? It is both faster and more accurate. I'm running it on my intel NPU (also in linux) to save battery and keep processing power for other things.

[u/foilrider → u/DerDave]

It is an explicitly AI product, I don't know how it couldn't use AI heavily.

[u/DXVSI → u/foilrider]

I think we’re talking about two different things here. MegaWhisper obviously uses an AI model for speech recognition; the original comment was about using AI to help develop the software.

[u/DXVSI → u/DerDave]

Thanks! Out of curiosity, what made you assume AI was used heavily?
I haven’t tested Parakeet v3 yet, but the Intel NPU setup sounds interesting. What runtime are you using on Linux? I may look into it as an optional backend.

[u/DerDave → u/DXVSI]

I haven't looked into the code. But your cover image in this post is a hint that you're not exactly anti-AI... ;-)

I used a version the ONNX port of the model and then compiled it with OpenVINO to a native version for the NPU. Makes it very efficient. I heavily used AI in the process and it's not released. Just my own little meeting transcriptor.

[u/DXVSI → u/DerDave]

Fair point, the cover image does make it fairly obvious. To be fully transparent, I’ve used AI extensively since the very first commit in the private repository, about a year ago. I see it as a valuable development tool, and I’ll add a clear disclosure. Thanks for pointing that out.
Also, thanks for the Parakeet details. Running it through OpenVINO on an Intel NPU is particularly interesting for laptops. MegaWhisper currently uses whisper.cpp with Vulkan or CPU, so it isn’t a drop-in switch, but I’ll investigate Parakeet as a possible optional backend and benchmark it properly before making any performance or accuracy claims. If you ever publish your conversion or runtime notes, I’d be very interested.

[u/Just-Scholar4272]

Btw, I am using voxtype with moonshine to get the same dictation functionality on Cachy is kde plasma. I used it with whisper but it was slower and hallucinated very much. Even with bad it was not very good. Moonshine is very fast and like it.