The Voxtral release seemed interesting, because it brought back competitive open source audio transcription. I wonder if it was necessary to have an LLM backbone (vs a pure-function model) though, but the approach is interesting.
Bear in mind that there are a lot of very strong _open_ STT models that Mistral's press-release didn't bother to compare to, making impression they are the best new open thing since Whisper. Here is an open benchmark: https://huggingface.co/spaces/hf-audio/open_asr_leaderboard . The strongest model Mistral compared to is Scribe, ranked 10 here.
This benchmark is for English, but many of those models are multilingual (eg https://huggingface.co/nvidia/canary-1b-flash )
One element of comparison is OpenAI Whisper v3, which achieves 7.44 WER on the ASR leaderboard, and shows up as ~8.3 WER on FLEURS in the Voxtral announcement[0]. If FLEURS has +1 WER on average compared to ASR, it would imply that Voxtral does have a lead on ASR.
Also note that, Voxtral's capacity is not necessarily all devoted to speech, since it "Retains the text understanding capabilities of its language model backbone"
IBM’s granite models seems multilingual and well ranked, but can’t find any app using it.
Anybody aware of a dictation app using one of those "better" models?
They do support Voxtral, among others.