Seedream 4.0

ByteDance's new multimodal deep-thinking model, supporting both text and visual inputs with enhanced reasoning capabilities.

Bytedance Seed 1.8 features stronger multimodal understanding and agent capabilities. The model delivers superior performance across a wide range of complex real-world tasks, helping enterprises create greater value.

Seed 2.1 Turbo is ByteDance’s multimodal language model supporting text, image, and video inputs with text output. It offers a 262,144-token context window, reasoning, function calling, and structured JSON output.

Seedream 4.5 is the latest in-house image generation model developed by ByteDance. Compared with Seedream 4.0, it delivers comprehensive improvements—especially in editing consistency, including better preservation of subject details, lighting, and color tone. It also enhances portrait refinement and small-text rendering. The model’s multi-image composition capabilities have been significantly strengthened, and both reasoning performance and visual aesthetics continue to advance, enabling more accurate and artistically expressive image generation.

ByteDance-Seedream-5.0-lite is the latest image generation model released by BytePlus. For the first time, it introduces web-connected retrieval, enabling the model to fuse real-time online information to significantly improve the timeliness and relevance of generated images. The model’s reasoning and comprehension capabilities are further upgraded, allowing it to accurately interpret complex prompts and visual inputs. In addition, ByteDance-Seedream-5.0-lite delivers notable improvements in global knowledge coverage, reference consistency, and professional-grade scene generation, making it well suited for enterprise-level visual creation workflows.

Seedream-5.0-Pro, ByteDance's newest image generation model, delivers comprehensive upgrades for complex, lifelike image creation and editing, ushering in a new phase of controllable visual production. It stands out with precise editing control, robust commercial applicability and natural rendering results.