This uses SenseVoice under the hood, which claims to have better accuracy than Whisper. Not sure how accurate that statement is though, since I haven't seen a third party comparison, in this space it's very easy to toot your own horn.

[0] https://github.com/FunAudioLLM/SenseVoice

I mean they make a bold statement up top just to paddle back a little bit further down with: "[…] In terms of Chinese and Cantonese recognition, the SenseVoice-Small model has advantages."

It feels dishonest to me.

[0] https://github.com/FunAudioLLM/SenseVoice?tab=readme-ov-file...

This uses SenseVoice small under the hood. They claim their large model is better than Whisper large v3, not the small version. This small version is definitely worse than Whisper large v3 but still usable and the extra annotation it does is interesting.

this claims to have speaker diarization which is a potentially killer feature missing from most whisper implementations.

I've been doing some things with Whisper and find the accuracy very good, BUT I've found the timestamps to be pretty bad. For example, using the timestamps directly to clip words or phrases often clips off the end of word (even simple cases where is followed by silence). Since this emphases word timestamps, I may give it a try.