A concerted effort to sequence matched primary and metastatic tumors is vastly improving our ability to understand metastasis in humans. Compelling evidence has emerged that supports the existence of diverse and surprising metastatic patterns. Enhancing these efforts is a new class of algorithms that facilitate high-resolution subclonal modeling of metastatic spread. Here we summarize how subclonal models of metastasis are influencing the metastatic paradigm.