Wind turbines create wakes, which reduce downstream power. Optimizing turbine placement requires accounting for these reductions. We compared a neural network trained on numerical simulations against engineering wake models across various farm sizes. The neural network predicted flow most accurately but was slower. Surprisingly, a simple TurbOPark model produced layouts with higher validated energy output, suggesting that accuracy is not the only important metric for such models.