Ah. Sorry, good thing I attached the related link.

Everybody been rumoring about R2. So releasing this thing kinda unexpected

The RL is so good grok changed it’s personality by changing small part of it’s system prompt

They got the whole Twitter database. It’s kinda the same with Gemini. But somehow Meta isn’t catching up, maybe their llama 4 architecture isn’t that stable to train.

It changed after Grok 3

No, you can run sd, flux based model inside the koboldcpp. You can try it out using the original koboldcpp in google colab. It loads gguf model. Related discussion on Reddit: https://www.reddit.com/r/StableDiffusion/comments/1gsdygl/koboldcpp_now_supports_generating_images_locally/

Edit: Sorry, I kinda missed the point, maybe I’m sleepy when writing that comment. Yeah, I agree that LLM need big memory to run which is one of it’s downside. I remember someone doing comparison that API with token based pricing is cheaper that to run it locally. But, running image generation locally is cheaper than API with step+megapixel pricing.

There is koboldcp-rocm fork. Koboldcpp itself has basic image generation. https://github.com/YellowRoseCx/koboldcpp-rocm