Your team is developing a Convolutional Neural Network (CNN) from scratch for an image recognition project. Initial tests on your on-premises CPU-only setup showed promising accuracy, but the training process was prohibitively slow, delaying your project timeline. To accelerate model training and meet the aggressive time-to-market goals, you're evaluating Google Cloud VMs for their superior hardware capabilities. Your current codebase does not include manual device placement and is not wrapped in an Estimator model-level abstraction. Given these constraints, and considering the need for a balance between cost, setup time, and performance, which of the following environments should you choose for training your model? (Choose one correct option)