8 vs 12 is a really big difference - especially with state of the art deep learning architectures. The problem isn't the size of the dataset but of the model. Large Convolutional Neural Networks often need the whole 12 GB VRAM of a Titan card for themselves and distributing over multiple cards/machines adds a lot of complexity.