Generative Model Evaluation involves assessing the quality and performance of models that generate new data. Metrics such as Inception Score, Fréchet Inception Distance, and human evaluation are used to measure how well the generated data matches the real data distribution and its realism. Evaluating generative models is essential for understanding their effectiveness in producing high-quality and diverse outputs, as well as for improving their performance through iterative refinement.