Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Voxtral Transcribe 2

mistral.ai

Post reply on HN
Print view View original

91–100 of 255 posts

Re: Voxtral Transcribe 2

#91

Post by keeganpoppen »

janalsncm wrote: post #53

I noticed that this model is multilingual and understands 14 languages. For many use cases, we probably only need a single language, and the extra 13 are simply adding extra latency. I believe there will be a trend in the coming years of trimming the fat off of these jack of all trades models. https://aclanthology.org/2025.findings-acl.87/

uhhh i cast doubt on multi-language support as affecting latency. model size, maybe, but what is the mechanism for making latency worse? i think of model latency as O(log(model size))… but i am open to being wrong / that being a not-good mental model / educated guess.

Re: Voxtral Transcribe 2

#92

Post by archb »

jiehong wrote: post #85

It’s nice, but the previous version wasn’t actually that great compared to Parakeet for example. We need better independent comparison to see how it performs against the latest Qwen3-ASR, and so on. I can no longer take at face value the cherry picked comparisons of the companies showing off their new models. For now, NVIDIA Parakeet v3 is the best for my use case, and runs very fast on my laptop or my phone.

I like Parakeet as well and use it via Handy on Mac. What app are you using on your phone?

Re: Voxtral Transcribe 2

#93

Post by javier123454321 »

popalchemist wrote: post #78
janalsncm wrote: post #53

I noticed that this model is multilingual and understands 14 languages. For many use cases, we probably only need a single language, and the extra 13 are simply adding extra latency. I believe there will be a trend in the coming years of trimming the fat off of these jack of all trades models. https://aclanthology.org/2025.findings-acl.87/

It doesn't make sense to have a language-restricted transcription model because of code switching. People aren't machines, we don't stick to our native languages without failure. Even monolingual people move in and out of their native language when using "borrowed" words/phrases. A single-language model will often fail to deal with that.

yeah, one example I run into is getting my perplexity phone assistant to play a song in spanish. I cannot for the life of me get a model to translate: "Play señorita a mi me gusta su style on spotify" correctly

Re: Voxtral Transcribe 2

#94

Post by jiehong »

archb wrote: post #92
jiehong wrote: post #85

It’s nice, but the previous version wasn’t actually that great compared to Parakeet for example. We need better independent comparison to see how it performs against the latest Qwen3-ASR, and so on. I can no longer take at face value the cherry picked comparisons of the companies showing off their new models. For now, NVIDIA Parakeet v3 is the best for my use case, and runs very fast on my laptop or my phone.

I like Parakeet as well and use it via Handy on Mac. What app are you using on your phone?

Spokenly has it on Mac and iOS, in both cases for free when using parakeet

Re: Voxtral Transcribe 2

#95

Post by zipy124 »

XCSme wrote: post #62
cootsnuck wrote: post #55

Earlier quoted context omitted.

The error rate for human transcription can be as high as 5%.

Oh wow, I thought humans are like 0.1% error rate, if they are native speakers and aware of the subject being discussed.

I was skepitcal upon hearing the figure but various sources do indeed back it up and [0] is a pretty interesting paper (old but still relevant human transcibers haven't changed in accuracy).

[0] https://www.microsoft.com/en-us/research/wp-content/uploads/...

Re: Voxtral Transcribe 2

#96

Post by [deleted] »

mdrzn wrote: post #11
GaggiX wrote: post #8

Earlier quoted context omitted.

Gpt4o mini transcribe is better and actually realtime. Whisper is trained to encode the entire audio (or at least 30s chunks) and then decode it.

So "gpt4o mini transcribe" is not just whisper v3 under the hood? Btw it's $0.006 / minute For Whisper API online (with v3 large) I've found "$0.00125 per compute second" which is the cheapest absolute I've ever found.

[deleted]

Re: Voxtral Transcribe 2

#97

Post by ashenke »

sbrother wrote: post #40
coder543 wrote: post #18

Earlier quoted context omitted.

The diarization is on Voxtral Mini Transcribe V2, not Voxtral Mini 4B.

Do you have experience with that model for diarization? Does it feel accurate, and what's its realtime factor on a typical GPU? Diarization has been the biggest thorn in my side for a long time..

You can test it yourself for free on https://console.mistral.ai/build/audio/speech-to-text I tried it on an english-speaking podcast episode, and apart from identying one host as two different speakers (but only once for a few sentences at the start), the rest was flawless from what I could see

Re: Voxtral Transcribe 2

#98

Post by breisa »

mdrzn wrote: post #11
GaggiX wrote: post #8

Earlier quoted context omitted.

Gpt4o mini transcribe is better and actually realtime. Whisper is trained to encode the entire audio (or at least 30s chunks) and then decode it.

So "gpt4o mini transcribe" is not just whisper v3 under the hood? Btw it's $0.006 / minute For Whisper API online (with v3 large) I've found "$0.00125 per compute second" which is the cheapest absolute I've ever found.

Deepinfra offers Whisper V3 at 0.00045$ / minute of transcribed audio.

Re: Voxtral Transcribe 2

#99

Post by ashenke »

yewenjie wrote: post #65

One week ago I was on the hunt for an open source model that can do diatization and I had to literally give up because I could not find any easy to use setup.

I don't know if that will change, but right now only the Voxtral Mini Transcribe V2 supports diarization and it's not open-weight. The Voxtral Realtime model doesn't support diarization, but is open-weight.

Re: Voxtral Transcribe 2

#100

Post by make3 »

keeganpoppen wrote: post #91
janalsncm wrote: post #53

I noticed that this model is multilingual and understands 14 languages. For many use cases, we probably only need a single language, and the extra 13 are simply adding extra latency. I believe there will be a trend in the coming years of trimming the fat off of these jack of all trades models. https://aclanthology.org/2025.findings-acl.87/

uhhh i cast doubt on multi-language support as affecting latency. model size, maybe, but what is the mechanism for making latency worse? i think of model latency as O(log(model size))… but i am open to being wrong / that being a not-good mental model / educated guess.

model size directly affects latency
Post reply on HN