In this work, we present our system Memento 3.0 for participation in the Lifelog Search Challenge 2023, which is a successor to the previous 2 iterations of our system called Memento 1.0 and Memento 2.0. Memento 3.0 employs image-text embeddings derived from OpenAI CLIP models as well as larger OpenCLIP models trained on ∼5x more data. Our system also significantly reduces the query processing time by almost 75% when compared to its predecessor systems by employing a cluster-based search technique. We additionally make important updates to the system’s user interface to offer more flexibility to the user and at the same time be better suited to efficiently handle new query types introduced in the Lifelog Search Challenge.