InstantStyle is a novel framework designed to address the challenges of style-preserving text-to-image generation. The paper highlights the underdetermined nature of style, which encompasses various elements such as color, material, atmosphere, design, and structure. Current methods often struggle with style degradation and content leakage, requiring meticulous weight tuning. InstantStyle introduces two key strategies: 1) Decoupling style and content within the feature space using subtraction operations, and 2) Injecting reference image features into specific style blocks to prevent style leaks. These strategies achieve superior visual stylization outcomes, balancing style intensity and textual controllability. The framework is tuning-free, model-independent, and compatible with other attention-based feature injection methods. The authors demonstrate the effectiveness of InstantStyle through extensive experiments, showing its ability to produce high-quality, style-consistent images without the need for complex weight tuning.InstantStyle is a novel framework designed to address the challenges of style-preserving text-to-image generation. The paper highlights the underdetermined nature of style, which encompasses various elements such as color, material, atmosphere, design, and structure. Current methods often struggle with style degradation and content leakage, requiring meticulous weight tuning. InstantStyle introduces two key strategies: 1) Decoupling style and content within the feature space using subtraction operations, and 2) Injecting reference image features into specific style blocks to prevent style leaks. These strategies achieve superior visual stylization outcomes, balancing style intensity and textual controllability. The framework is tuning-free, model-independent, and compatible with other attention-based feature injection methods. The authors demonstrate the effectiveness of InstantStyle through extensive experiments, showing its ability to produce high-quality, style-consistent images without the need for complex weight tuning.