Krea Opens Krea 2's 12B Image Model So Anyone Can Train and Deploy

Krea just dropped the open weights of Krea 2, its flagship image generation model, in two flavors: Krea 2 Raw and Krea 2 Turbo. The headline pitch is simple: train on Raw, generate with Turbo. Together, they hand the community a 12-billion-parameter aesthetic image model that runs on consumer hardware and ships with a commercially friendly license.

Two weights, one strategy

The release is not a single model dump. Krea is releasing two distinct checkpoints that serve very different roles in a workflow:

• Krea 2 Raw is a mid-training checkpoint, snapshotted before any distillation, fine-tuning, or post-training. Think of it as the model in its most malleable state, before Krea baked in their aesthetic preferences. It is explicitly not recommended for direct inference, but it is the ideal base for training LoRAs (low-rank adapters, a lightweight fine-tuning technique that adds small trainable matrices to a frozen model) and full fine-tunes.
• Krea 2 Turbo is the polished, production-ready version. It has been distilled (compressed to run in far fewer steps) and post-trained for aesthetic quality. Turbo is an 8-step distilled checkpoint built for fast, high-quality generation at 1K to 2K resolution. It runs with guidance_scale=0.0, meaning no classifier-free guidance overhead.

The intended workflow is: train your LoRA on Raw, then run it on Turbo for inference. LoRAs trained on the Raw base model transfer well to Turbo for inference. Krea also released a collection of in-house LoRAs trained on Raw and meant to be used with Turbo, so you can see this pattern in practice immediately.

What is under the hood

Krea 2 is a latent-diffusion image model trained from scratch with an emphasis on aesthetics and stylistic control. The architecture is a single-stream multimodal diffusion transformer. The key architectural choices are worth knowing: