Kandinsky-3.1 is a large text-to-image diffusion model developed by Sber and AIRI, featuring 11.9 billion parameters. The model consists of a text encoder, U-Net, and decoder, enabling high-quality, detailed image generation from text prompts. It is trained on extensive datasets and is designed for both creative and scientific applications.
Not enough throughput data
Not enough TTFT data