“You can fine-tune or train a model that is two orders of magnitude fewer parameters if you have the data and you can beat the bigger model. And then because it's smaller, you're going to be another magnitude faster and cheaper. … Right now we are at 40x cheaper than the most expensive frontier models.”
The TWIML AI Podcast · AI Builders · November 2026
Context
Asked why Canva bothered training its own models when frontier and open-weights models exist, Stefano Corazza argued that unique data plus vertical integration beats generic models on cost and speed. The 40x figure is his own claim.
Transcript
…the loop and be able to iterate in a way that is fast and also fun. So that's a key part, I think, of what we do. Until the moment when we will have telepathic helmets that you can wear and you can transfer the full amount of your intent and your vision, but that is a little bit far out, I think.
…you could have. You, Canva, could have chosen to build on. On the other hand, it's like, you know, maybe it's obvious that a Canva with all of the data and user interactions that you have access to would build a model. Do you think it's interesting, or do you think it's obvious that you did it?
No, I think it's very interesting because I think it also applies to other companies, maybe of similar size, when basically there's two factors. So, first of all, you have unique data that nobody else has. And then the second part is deep vertical integration of AI Design’s in your stack is going to provide incredible performance and cost reduction. Those two factors are basically the driving input. And I'm sure there's a lot of companies that are like in the thousands of employees or even smaller that will do that and where it makes sense. And so for us, it was kind of the discovery of the fact that you can fine-tune or train a model that is two orders of magnitude fewer parameters if you have the data and you can beat the bigger model. And then because it's smaller, you're going to be like another magnitude faster and cheaper, right? So that is the belief that we had. And right now we are in the 40x cheaper than the most expensive frontier models. They can do the same design task, but they are using others or magnitude more parameters to do it. Instead, we have smaller models that…
In what sense? Without making it a full episode, in what sense?
Something happened like about, I think, four months ago where some of the companies developing video models started releasing open weights versions. And that had a fantastic domino effect where it forced all the competitors to do it. And so now you have an ecosystem where a lot of the image models…
With Kraft, did you start from an open weights model and train it, tune it, or is it a from scratch train?
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