GigaGAN is a large-scale GAN model designed for text-to-image synthesis. It boasts fast inference speeds, the ability to generate high-resolution images, and an editable latent space, enabling various potential space editing applications such as latent interpolation, style mixing, and vector arithmetic operations. GigaGAN can generate 512-pixel images at a rate of up to 7.7 images per second and supports 16-megapixel image synthesis. It is an efficient text-to-image synthesis model applicable to diverse scenarios.