zembed 1 is a focused, no-frills embedding specialist — it takes text in and produces vector representations, nothing more. With a 40K token context window, it can handle long documents without chunking them into tiny pieces, which makes it practical for tasks like semantic search or document similarity at scale. It's open-weight under a non-commercial license, so it's accessible for research and experimentation but not for building commercial products.