Sequential/iterative models can be easily parallelized without any challenges.

Tuning hyperparameters for sequential/iterative models is challenging because each iteration depends on the results of the previous one, making parallelization difficult.

Sequential/iterative models are identical to non-sequential models in terms of hyperparameter tuning challenges.

Sequential/iterative models cannot be tuned at all due to their inherent sequential nature.