Krea AI released Krea 2, a 12B-parameter DiT (Diffusion Transformer) image generation model. The dual release includes: Krea 2 Base (the full 12B model) and Krea 2 Turbo (an 8-step distilled variant for real-time use). The standout: Krea 2 Turbo generates a 2K image in 2 seconds on an H100, with quality on par with Stable Diffusion 3.5 Large.
The technical details: Krea 2 Base uses a 12B DiT with 32 attention heads and a 1024-token sequence length, trained on 4B image-text pairs. The training used a "curriculum" approach — start with low-resolution images (256×256) and progressively increase to 2K, with the learning rate carefully tuned at each stage.
The Turbo variant uses "adversarial diffusion distillation" (ADD) — a student model is trained to mimic the base model's output in just 8 steps, with a discriminator ensuring the student doesn't lose quality. The result: 2-second 2K image generation on H100, 0.8-second 1K on RTX 4090.
The bigger takeaway: "real-time image generation" is becoming a commodity. The 2-second 2K mark is the threshold where image generation can be used in interactive applications — chat avatars, AR filters, real-time creative tools. Krea 2 is the first model to break this threshold with an open-source release.
For the industry, this signals that "real-time generation" is the next competitive battleground. The closed-source models (Midjourney v7, DALL-E 4) have been at this threshold for months, but Krea 2 is the first open-source model to catch up. The "open vs closed" gap in real-time generation is closing fast.