InstantID Image Personalization is a groundbreaking approach to creating personalized images. Unlike previous methods that required extensive storage and fine-tuning, InstantID uses a single facial image to generate various styles while maintaining high fidelity. This plug-and-play module integrates with popular pre-trained text-to-image diffusion models like SD1.5 and SDXL. It features an ID embedding for robust semantic face information, a lightweight adapted module for visual prompts, and an IdentityNet for detailed feature encoding. InstantID stands out by not requiring UNet training, avoiding test-time tuning, and offering better face fidelity with text editability. It supports both stylized and realistic styles, demonstrates robustness, editability, and compatibility, and performs well even with a single reference image. InstantID outperforms existing tuning-free techniques and is competitive with pre-trained character LoRAs, offering flexibility in non-human character identity attributes.