Model Card
Also known as: model documentation, model spec
A model card is a structured disclosure document. When Anthropic releases Claude 4 or Google releases Gemini 2.5, the model card tells you: what benchmarks it was evaluated on and what scores it achieved, what data it was trained on (or what is known about it), what tasks it was designed for, what failure modes and limitations the team identified, and how it should and shouldn't be used.
Model cards were formalized as a concept by Google researchers in 2018 and have become standard practice across major AI labs. They range from thorough technical documents (Anthropic and Llama model cards are detailed) to marketing-forward summaries that omit inconvenient limitations.
For builders choosing models, model cards are the primary source of official capability claims and known limitations. They're also increasingly required by regulation: the EU AI Act mandates technical documentation for high-risk AI systems that aligns closely with the model card concept. Reading model cards critically, especially benchmark footnotes and known-limitations sections, is a basic research skill for anyone evaluating models.