The correct option is Vertex AI Model Cards with Fairness Indicators.

Vertex AI Model Cards with Fairness Indicators directly addresses governance and compliance by combining auditable documentation with structured fairness evaluation. Model Cards capture the models purpose, intended use, limitations, data and evaluation summaries, and performance metrics. They are tied to the registered model and its versions so auditors can trace lineage and see consistent, centralized documentation that can be viewed or shared when needed.

Fairness Indicators enables systematic bias testing by computing metrics across user defined slices that represent demographic groups. It helps teams compare performance across those groups and identify disparities and thresholds, which supports responsible AI reviews and ongoing monitoring of equitable outcomes.

Running open source models such as Gemma on Google Kubernetes Engine is an infrastructure choice for hosting or serving models and it does not provide built in governance artifacts or bias testing capabilities.

Gemini integration in Google Workspace enhances productivity applications and content creation but it does not supply model governance features for documenting model purpose or evaluating fairness for ML systems.

Cloud TPU is a hardware accelerator that speeds up model training and inference and it does not include features for compliance documentation or fairness evaluation.

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