Diffusion Self-Distillation is a self-distillation technique based on diffusion models for zero-shot custom image generation. This technology allows artists and users to generate their own datasets via a pre-trained text-to-image model without requiring large paired datasets, enabling them to fine-tune the model for image-to-image tasks conditioned on text and images. This approach surpasses existing zero-shot methods in maintaining performance on identity generation tasks and can rival instance-based tuning techniques without the need for optimization during testing.