Model Card

A model card is a structured profile for an AI model. It explains what the model was built for, what is known about its data and training assumptions, which capabilities have been tested, where its limits are, and which use cases it should not handle. A useful model card goes beyond marketing language. It should include the model version, release date, license, known risks, evaluation methods, relevant benchmarks, recommended use cases, exclusions, and notes on privacy or regulatory constraints. For companies, the model card connects technical selection with governance. It helps teams decide whether a model fits a specific application, industry, risk class, or deployment environment. For open-weight and interchangeable models, a model card does not replace internal evaluation, but it gives teams a solid starting point. When providers do not publish clear model cards, buyers must investigate more themselves: origin, performance limits, rights, safety behavior, and update cadence. A model card makes model decisions easier to document, audit, migrate, and approve later.