Seed 1.6

Seed 1.6 is a general-purpose multimodal model designed to handle complex reasoning tasks and extensive data analysis. Built on a sparse Mixture-of-Experts architecture, it utilizes 230 billion total parameters with 23 billion active parameters per forward pass to balance performance and efficiency. The model is specifically engineered for deep thinking, allowing it to process and synthesize information from diverse sources including text, images, and video. With its expansive context window, it is well-suited for applications that require managing large volumes of information, such as generating detailed reports or conducting comprehensive multimedia data analysis.

The model's development lineage emphasizes versatility and high-performance retrieval, with related iterations like the Flash variant and embedding-focused models utilizing phased training strategies to refine multimodal understanding. By progressively transforming base models into specialized tools, the architecture supports hybrid retrieval across different modalities and achieves high performance on benchmarks like CMTEB and MMEB-V2. These advancements make Seed 1.6 a robust choice for developers looking to integrate sophisticated, adaptive reasoning into workflows that demand both speed and the ability to interpret mixed-media inputs effectively.