NVIDIA's A10, A100, and H100 GPUs offer varying performance-to-cost ratios, making them suitable for different machine learning tasks. The H100 is ideal for large language model workloads with high precision requirements, while the A100 is a versatile GPU suitable for larger models with moderate precision needs. In contrast, the A10 and L4 GPUs are more cost-effective options for smaller models or inference tasks. When selecting a GPU, consider factors such as task type, model size, memory requirements, budget, and performance needs to choose the best fit for your specific use case.