Grokkfast is a cutting-edge optimization algorithm designed to speed up the generalization process in neural networks, particularly in scenarios where traditional optimizers might struggle. It's implemented in MonsterAPI finetuning platform and aims to accelerate learning and improve model performance. Grokkfast works by amplifying slow-varying components of parameter updates, effectively accelerating the generalization process. The algorithm modifies existing optimizers by applying a low-pass filter to the gradients, which can lead to significant improvements in training speed and performance. Initial experiments with Grokkfast pretraining have shown promising results across various tasks, including algorithmic tasks, image classification, molecule property prediction, and sentiment analysis. Users can leverage the potential benefits of Grokkfast in their machine-learning projects by using it as an optimizer option in MonsterAPI.