Core Differences Between Standard, Multimodal, and Embedding (Emb) Models — A Clear, Easy-to-Understand Guide
In AI, standard models, multimodal models, and embedding (Emb) models are three core yet easily confused types. This article systematically unpacks their essential differences across four dimensions—definition, primary function, technical characteristics, and application scenarios. Standard models are single-purpose processors that focus on specific tasks within a single modality; multimodal models are fusion processors that integrate and transform information across text, images, audio, and other modalities; embedding models act as information-to-vector converters, transforming diverse inputs into low-dimensional vectors that provide foundational support for other models. The piece also clarifies their collaborative relationships and common misconceptions, helping readers quickly identify each model’s role and choose the right model for different scenarios.
