Mistral AI has just come out with a brand new AI model and it is called Voxrall. Now, there's a bunch of interesting things about this model in particular, one that is an open speech model, the benchmarks and the data essentially of how its word error rate and its price, I think are particularly interesting. I'm going to break all of this down, especially on the heels of a potential $1 billion round of funding that Mistral is looking at doing. And all of the rumors, swirling about Apple acquiring the company, what the founder has said about that, what the plans are for the future of this company.
This is an interesting time for Mistral, no doubt. We're going to get into all of that. But before we do, I wanted to mention, if you want to try out all of the latest models from Mistral, including all the latest models from a lot of different companies, the top 40 AI models, you go check out my own startup, which is AIbox.ai. Over there, we have CodeStroll, Mistral 3B Compact, Pixel Large Vision, Mistral Small.
A ton of these interesting models, but a ton of interesting models from anthropic, cohere, DeepSeek, Google, Meta, Microsoft, NVIDIA, OpenAI, Quen, Grok from XAI, all of the interesting companies. So you can check out all of those models and a bunch of other image speech and audio models at AIbox.ai for one subscription. 20 bucks a month, you don't have to have subscriptions, all of these different platforms. You can try them all out.
And there's a link in the description. All right, let's get into what Mistral is doing. So with VauxkStroll, the most interesting thing that they've essentially announced is that VauxkStroll is this open model. It's going to do transcription.
But basically what that means is like, it can take in audio files, understand what the audio files are saying and respond. So it has its own voice. It's a competitor to 11 Labs and a lot of these other players. And what they're saying about it is they've actually built three models specifically with three different use cases.
But what they're saying is, this is a much more efficient, this is way cheaper than using something like 11 Labs are other players. So this is pretty interesting. They have this kind of diagram that they have, its price USD per minute. And on the other column, it's the word error rate.
So basically how often it messes up the words that it's saying. And they have a couple of competitors they put on this diagram. One of them is Scribe, which is super expensive. And then on the other field, they have some others, which are interesting, essentially the fact that it is an open model.
So they're allowing you to take the model, run it locally on your own devices or server. And I think for a lot of companies, this is quite exciting to have that capability. When you look at right now, if you want to use these text models, you got to use something like 11 Labs. OpenAI has some options, but it's all going to be things that you have to pay for API usage.
So when you have the open models, it's pretty interesting being able to try and run them locally for a lot of companies. And they even have a super stripped down version that essentially allows you to run them locally on a device. And so this is kind of what a lot of people were saying that Mistral was going to be doing with Apple. This is why Apple wanted to acquire them is because they have a bunch of these tools that are stripped down and able to run on device.
You can imagine a tool like this would be incredibly useful for something like Siri, where you can run essentially edge models that have this one in particular called VoxStroll Mini. And VoxStroll Mini is the error rate is not the best. It's better still than Whisper Large V3 from OpenAI. And it's still a little bit better than Gemini 2.5 Flash, but it's not as good as GPT-40 Mini Transcribe.
But it's way cheaper and it can run on your device. They also have one called VoxStroll Mini Transcribe, which is also super cheap and has a much better word error rate. So in any case, they have all these different different models specifically that they have. And they're able to run locally on devices.
So for Apple for iPhone, they could essentially grab one of these models if they acquired the company or maybe make a partnership with them, put it on your iPhone, use it to power Siri, and even without the internet, Siri would still be able to understand what you're saying. They probably have another model to back it up, maybe something from Mistral or from another player, maybe an open source model from Mistral. But using this in conjunction with that, they could essentially run Siri with no internet, which would be really, really crazy. And I think that'd be something Apple would be interested in doing.
So people have essentially been talking about these rumors that Apple is interested in acquiring Mistral. The CEO of Mistral said they have no interest. I mean, they weren't really supposed to be talking about Apple, but there's like, we have no interest to be acquired. They said that they would like to IPO the company, essentially.
And Mistral really is kind of like the crown jewel of Europe. It's the number one AI company coming out of Europe. It's raised the most money. Europe as a country has backed it and given a lot of resources, whether that's compute or special deals, essentially.
And so I think they've been, like, they've largely benefited a lot from a lot of programs in Europe. And so I think people want to see it say owned and operated inside of Europe. But overall, definitely it's building a lot of really interesting tools that would be very useful for a lot of people. What's interesting, Mistral says that Voxel can transcribe up to 30 minutes of audio because it has LLM's back bone.
That Mistral small 3.1 can understand up to 40 minutes of audio, which is honestly fantastic. I mean, for a majority of all conversations I ever have, it's going to be less than that. So essentially you can ask questions about audio content. You can generate summaries.
You can turn voice commands into real-time actions, like calling APIs or running functions. It's also multilingual. So, you know, I mean, you can imagine a lot of these cases. It's like you upload an audio file to it.
Probably less so the live talking is not what this is used for as much, but you upload an audio file to it and it can understand what's in the audio file. You can imagine something like a big use case of this technology would be like YouTube, where you have the transcription of every single YouTube video on the side. YouTube is using their own transcription models for this. Obviously Google has their own tools, but you can imagine like other players that are in Google that don't have that massive tool will need to use something.
Maybe even something like Vimeo or another like video kind of platform out there or companies that just wanted to have transcriptions or transcribe a lot of their content on the platform and Facebook and LinkedIn and all of them need that functionality. So you can imagine there's a lot of people that need that functionality. So it's multilingual. It does English-Spanish, French, Portuguese, Hindu, German, Dutch, and Italian, which is a bunch of languages right off of that, which is pretty cool.
They have of course two variations of their speech understanding model. So if they got Vauxkstrel small and that is a 24 billion parameter for production scale deployments, it's competitive. Apparently with 11 labs scribe, although it's way cheaper. It's also competitive with GPT-40 Mini and Gem 9.5 Flash, although it's on their diagram.
It's cheaper and a better word error rate than all those companies. Then they have their Vauxkstrel Mini, which has a three billion parameter. And this is the one I've been talking about that, like maybe Apple would be interested in, but this is for local and edge deployments. And then of course they have an ultra-treat super stripped down, very fast API version, a three billion model called Vauxkstrel Mini transcribe.
So this is really optimized only for transcriptions, but it says that it can outperform OpenAI's Whisper and it's less than half the price. So this is definitely something interesting. And people right now can go and try this over on, you can go for free, download the API on HuggingFace, or you can have the testing model is in their website. Mistrel's chat has it there.
So very, very interesting. This is obviously one of the big AI firms out of Europe. They have this big quote unquote $1 billion equity investment looking like it's going to happen from Abu Dhabi's MGX Fund happening soon. So this is kind of the perfect time for them to start rolling out these tools and perhaps getting some of their competitors or perhaps business partners interested in acquisitions or looking at making deals with them.
So if they got the Apple deal, that would be absolutely incredible, whether even if that's not an acquisition by Apple, which sounds like they don't really want to go in that direction. But making some sort of partnership, we know Apple right now is talking to more than just opening eye who's powering Apple intelligence and other looking anthropics. So, I think it's quite interesting to see that Apple's cloud. It seems like Apple feels quite behind.
All of their investors and board is quite upset about Apple with their slowness to adopt these AI features and what they've said is kind of like a failure in that department. So, a choir company like this might be good, but if not, they may be interested in working with Mistrel. So it'll be very interesting. I'll keep you up to date on everything happening with this startup and with others as people get their hands on this new tool from Mistrel, start incorporating into products.
I think it's going to be interesting. And we'll make sure to get it up on AI box in not to distant of the future. So thanks so much for tuning in to the podcast. Make sure you leave a rating and review.
If you enjoyed the episode, if you learned anything new about what's going on over at Mistrel, thanks so much for tuning in. Thank you.