How is 'K-means' clustering different from 'hierarchical' clustering?

Hierarchical clustering creates a hierarchy of clusters, while K-means does not
Hierarchical clustering uses centroids, while K-means does not
K-means requires the number of clusters to be defined beforehand, while hierarchical clustering does not
K-means uses a distance metric to group instances, while hierarchical clustering does not

K-means clustering requires the number of clusters to be defined beforehand, while hierarchical clustering does not. Hierarchical clustering forms a dendrogram from which the user can choose the number of clusters based on the problem requirements.

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