dvrp

Ladies and gentlemen, the Streisand Effect in its full glory!

Did you check the “Only what you asked. Not one pixel more” section?

Not only do I think the website section addresses exactly this, but we also built a pixel diff viz tool for you to compare with other models.

I meant workflows in the generic definition. Not as in Node-based Workflows (which we also support).

they’ll come!

We will release a technical report about it. But our Krea 2 technical report is out and, AFAIK, it’s the most open technical report out there (1 hour estimated of reading time lol) so you can get a lot of information there already!

Thank you for the constructive reply; I think you are quite right.

I’ll ponder about what would be a better growth strategy - even in turbulent times - while, like you say, we also ensure is done on a good financial base/cushion.

Thanks for taking the time too.

correct!

I think my product team is rapidly iterating on this page based off feedback and the HN crawler it’s re-scraping metadata such as title tags

the post used to be titled “Frontier Image Model 4x faster than Nano Banana Pro”

I actually was just talking about this with a peer. He was saying that people inside labs and data brokers use image models for RL training of LLMs to get better at these sort of tasks, which would make sense as a way to try to embed the knowledge into the LLM - similar to how Astra was clearly trained with more CAD, 3D, and Robotics in mind.

Oh! We should put it there then!

I was aware of AWS Bedrock

Check Krea 2. Not only open weight but even better terms in the license!

Also, Krea 1 was co-developed with BFL !

K3 open weights is being discussed internally as I type this!

Gemini (the product) is a mix of an LLM plus image model plus agentic tooling. Is not apples to apples.

A fairer comparison would be Krea Agent with Krea 3 as image model. So you could have grounding, web search, verification models that assess results, etc.

If you told me Nano Banana Pro and that’s it, that’s a different story.

Ngl that made me laugh