Seedream 3.0 is a bilingual text-to-image foundation model developed by the Seed team at ByteDance. It represents a significant architectural evolution from previous iterations, moving to a native high-resolution framework that supports both English and Chinese prompts. The model is designed to generate high-fidelity images and natively supports 2K (2048×2048 px) resolution outputs without the need for external upscaling or refiner modules.
The model's architecture is built on a Diffusion Transformer (DiT) framework and utilizes a flow matching loss to predict conditional velocity fields. Technical innovations in this version include mixed-resolution training, cross-modality Rotary Positional Embeddings (RoPE), and a representation alignment loss that improves the correspondence between complex prompts and visual outputs. To ensure high aesthetic quality, the model's training pipeline incorporates a 20B parameter vision-language model (VLM) reward system to align results with human preferences.
A defining feature of Seedream 3.0 is its industry-leading typography and text-layout performance. It excels at rendering legible text within images, including small fonts and intricate Chinese characters, which are often challenging for diffusion models. Additionally, the model is optimized for speed; utilizing importance-aware timestep sampling, it can generate 1K resolution images in approximately 3 to 5 seconds, making it effective for both rapid prototyping and professional graphic design.