Kwasi Ankomah

So I would say those big models, I think they're going to be there, but we're already seeing a switch to these smaller ones as well.

It depends.

And I know that's such a cop-out answer, but it really does.

And I think we, like, some of us, we're kind of agnostic, right?

We want to give you the best model for your use case.

And, you know, we, for instance, OSS,

For a moment, it's a fantastic model.

It's a fantastic model considering its footprint, 120 billion parameters.

It's smaller, right?

It's smaller than some of its other frontier contenders.

And that makes it more accessible to customers.

And we're seeing that as well.

People can say, oh, hey, this is actually, I can run this even faster on your platform, which means that I can run it maybe on more even real-time applications.

Yeah.

I think that, you know, we've also got the Quen Coda models, which are absolutely phenomenal.

You know, like the full, you know, those are the 480, I think, billion parameter model as well, working really, really well.

But I think, and this is also kind of based on the open route to traffic, like I think DeepSeat V3 has really hit a mark and also Maverick as well.

Like Maverick because of its vision.

I know people, people weren't kind of super happy with the reasoning performance, but I would also kind of,

counter that with, it is a multimodal model, right?