Having built with and tried every voice model over the last three years, real time and non-real time... this is off the charts compared to anything I've seen before.
Yes I've tried Parakeet v3 too. For its own purpose - running locally - it's amazing.
The thing that's particularly amazing about this Voxtral model is how incredibly rock solid the accuracy is.
For the longest time previous models have been 'mostly correct' or as people have commented elsewhere on this HN thread, have dropped sentences or lost or added utterances.
I have no affiliation with these folks, but I tried and struggled to get this model to break even speaking as adversariately as I could.
Thank you for the link! Their playground in Mistral does not have a microphone. it just uploads files, which does not demonstrate the speed and accuracy, but the link you shared does.
I tried speaking in 2 languages at once, and it picked it up correctly. Truly impressive for real-time.
Impressive indeed. Works way better than the speech recognition I first got demo'ed in... 1998? I remember you had to "click" on the mic everytime you wanted to speak and, well, not only the transcription was bad, it was so bad that it'd try to interpret the sound of the click as a word.
It was so bad I told several people not to invest in what was back then a national tech darling:
> I tried speaking in 2 languages at once, and it picked it up correctly.
I'm a native french speaker and I tried with a very simple sentence mixing french and english:
"Pour un pistolet je prefere un red dot mais pour une carabine je prefere un ACOG" (aka "For a pistol I prefer a red dot but for a carbine I prefer an ACOG")
And instead I got this:
"Je prépare un redote, mais pour une carabine, je préfère un ACOG."
"Je prépare un redote ..." doesn't mean anything and it's not at all what I said.
I like it, it's impressive, but literally the first sentence I tried it got the first half entirely wrong.
I used sell the Mac Voice Navigator (from Articulate Systems) in the 90s, which was a SCSI based hardware box that you plug into a Mac, Mac SE or Mac II. It used to use the same L&H speech recognition tech (if I recall correctly) and was called the "User Interface" of the future.
Horrible speech recognition rate and very glitchy. Customers hated it, and lots of returns/complaints.
A few years later, L&H went bankrupt. And so did Articulate Systems.
Doesn't seem to work for me - tried in both Firefox and Chromium and I can see the waveform when I talk but the transcription just shows "Awaiting audio input".
I can see the waveform but it still doesn't work for me. Switched to Edge, disabled all adblocking and privacy extensions, built-in tracking prevention, and "enhanced site security" (whatever that is), and still no dice. I'd love to try it and be impressed, but it seems impossible. :(
If you don't get sound there it won't work anywhere. A surprising number of problems like these can be solved by selecting the correct audio input source (provided your computer shows more than one).
Wow, that’s weird. I tried Bengali, but the text transcribed into Hindi!I know there are some similar words in these languages, but I used pure Bengali that is not similar to Hindi.
Well, on the linked page, it mentions "strong transcription performance in 13 languages, including [...] Hindi" but with no mention of Bengali. It probably doesn't know a lick of Bengali, and is just trying to snap your words into the closest language it does know.
I have seen the same impressive performance about 7 months ago here: https://kyutai.org/stt
If I look at the architecture of Voxtral 2, it seems to take a page from Kyutai’s delayed stream modeling.
The reason the delay is configurable is that you can delay the stream by a variable number of audio tokens. Each audio token is 80 ms of audio, converted to a spectrogram, fed to a convnet, passed through a transformer audio encoder, and the encoded audio embedding is passed, with a history of 1 audio embedding per 80 ms, into a text transformer, which outputs text embedding, then converted to a text token (which is thus also worth 80ms, but there is a special [STREAMING_PAD] token to skip producing a word).
There is no cross-attention in either Kyutai's STT nor in Voxtral 2, unlike Whisper's encoder-decoder design!
I’ve been using AquaVoice for real-time transcription for a while now, and it has become a core part of my workflow. It gets everything, jargon, capitalization, everything. Now I’m looking forward to doing that with 100% local inference!
Hey, I would really appreciate if you would try https://ottex.ai
I'm working on a Wispr/Spokenly competitor. It's free without any paywalled features, supports local models and a bunch of API providers including Mistral.
For local models ottex has - parakeet V3, Whisper, GLM-ASR nano, Qwen3-ASR (don't have voxtral yet though, looking into it).
btw, you can try new voxtral model via API (the model name to pick is `voxtral-mini-latest:transcribe`), I personally switched to it as my main default fast model - it's really good.
Same here; the voice waveform animates as expected but the model doesn't do anything when I click on the microphone. It just says "Error" in the upper-right corner.
Also tried downloading and running locally, no luck. Same behavior.
Not terrible. It missed or mixed up a lot of words when I was speaking quickly (and not enunciating very well), but it does well with normal-paced speech.
Yeah it messed up a bit for me too when I didn't enunciate well. If I speak clearly it seems to work very well even with background noise. Remember Dragon Naturally Speaking? Imagine having this back then!
Don't be confused if it says "no microphone", the moment you click the record button it will request browser permission and then start working.
I spoke fast and dropped in some jargon and it got it all right - I said this and it transcribed it exactly right, WebAssembly spelling included:
> Can you tell me about RSS and Atom and the role of CSP headers in browser security, especially if you're using WebAssembly?