Kwasi Ankomah

It was small enough that you could really fine tune it fantastically well for your use case and get it running.

And a lot of our clients, they've chosen to do that.

They've been like, hey, we have this concept to bring your own model, so you can bring your own checkpoint, load it onto our hardware, and then, of course, just use it as you normally would.

But as you say, the...

The overhead of switching models is something that we've really, really thought about and thought, how can we make this as slick as possible so that people can actually run these workloads using that?

So because the way a lot of agentic frameworks run at the moment, right, is that you can actually name, once you build the agent, right?

So if I take something like Landgraf or Crew AI, right, two very popular frameworks, and also AutoGen for that matter, all three of those frameworks allow you to, at each stage that you define an agent, to pass a model on.

So you can pass any model in at any stage.

Now, what we tend to see a lot of builders doing is that they just use, they're like, oh, I'll just use this.

And they use the same model for all the things.

But you can change that model.

Now, of course, what's going on in the background is that

you're still paying for that.

If you change it, you still have to pay for it.

What we're saying is that we want you to be able to switch those models that actually have the footprint be super small.

So it's like maybe it's one or two racks.

And that costs you control.

And that's what we're trying to say to people is that the overall total cost here can be a lot cheaper.

But in terms of answering your question, you can actually, yeah, you can define your agents to use any models that you kind of want.

You can kind of