Researchers at Apple have unveiled new findings on scaling laws for native multimodal models, emphasizing that early-fusion techniques outperform late-fusion methods, particularly at smaller parameter counts. The study indicates that early-fusion is not only more efficient to train but also easier to deploy. Additionally, the incorporation of Mixture of Experts (MoEs) allows models to learn modality-specific weights, leading to substantial performance improvements. This research highlights advancements in artificial intelligence and deep learning methodologies, potentially enabling faster and more effective image generation.