The thing that makes it particularly misleading is that models that do transcription to lowercase and then use inverse text normalization to restore structure and grammar end up making a very different class of mistakes than Whisper, which goes directly to final form text including punctuation and quotes and tone.

But nonetheless, they're claiming such a lower error rate than Whisper that it's almost not in the same bucket.

For example fal.ai has a Whisper API endpoint priced at "$0.00125 per compute second" which (at 10-25x realtime) is EXTREMELY cheaper than all the competitors.

I agree with your belief, other languages have either lower density (e.g. German) or lower understandability (e.g. English)

I don't know how widely accepted that conclusion is, what exceptions there may be, etc.

I tried speaking in 2 languages at once, and it picked it up correctly. Truly impressive for real-time.

And open weight too! So grateful for this.