Incidentally, I've been testing a lot of dictation apps and models. I am on macOS Sequoia and intend to skip Tahoe altogether, so newer Apple models were not an option. I also dictate in multiple languages.
I mostly use the MacWhisper app until now, but I got frustrated by its slow development and lack of focus and dictation. So I tried the free TypeWhisper app. It works very well, but then I tested multiple models and my conclusion was that one cannot beat the Whisper Large v3 model for accuracy. I tried Qwen ASR (very good, but only for English), Voxtral (spoke Polish to it and it wrote Russian, BIG oopsie), Parakeet TDT 3 (very fast, but sometimes inaccurate).
I got frustrated by the speed of the Whisper Large model. So I spent an hour with AI benchmarking, testing and developing a new plugin. Turns out that on a modern Mac with a good GPU you can run the Whisper Large model at roughly the same speed as the tiny Parakeet model. 2-3x faster than what other apps ship. It's just that nobody bothered.
So, I am now happily dictating into TypeWhisper and then feeding the dictated text into a local gemma-4-26b-a4b-qat LLM for corrections. Everything happens instantly.
Thank you for testing TypeWhisper and the different models so thoroughly, and for sharing the results. Comparing several engines across multiple languages is already valuable; going one step further and building a faster Whisper Large v3 plugin is a real contribution.
This is exactly why I made TypeWhisper’s engine and plugin layer extensible. The best setup depends heavily on language, hardware, and workload. Your result that Large v3 can run close to Parakeet speeds on a modern Mac is especially interesting, as is your fully local Whisper plus Gemma correction workflow.
If you’re comfortable sharing the plugin or benchmark setup, I’d be very interested in taking a closer look and seeing whether it could benefit more users. Either way, thank you for putting so much time into this and contributing your findings back to the project.