A Deep Learning VM configured with an n1-standard-2 machine and 1 GPU, which comes with all necessary deep learning libraries and frameworks pre-installed, allowing for immediate start of training without the need for manual dependency installation.

A Compute Engine VM equipped with 8 GPUs, offering high computational power but requiring manual installation and configuration of all deep learning dependencies, which could delay the start of your training process.

A Compute Engine VM with 1 TPU, providing specialized hardware for deep learning tasks but necessitating manual setup of all dependencies and potential code modifications to leverage the TPU's capabilities.

A Deep Learning VM with e2-highcpu-16 machines, optimized for CPU performance and pre-installed with all necessary libraries, though lacking GPU acceleration which is crucial for CNN training speed.

Both A and C, as using a GPU for initial rapid experimentation and a TPU for scaling up training could offer a balanced approach between speed and scalability, despite the initial setup overhead for the TPU.