According to God of Prompt on Twitter, the evolution of Mixture of Experts (MoE) models is creating significant advantages for the open source AI community compared to dense models. Dense models like Meta's Llama 405B require retraining the entire model for any update, resulting in high costs—over $50 million for Llama 405B (source: God of Prompt, Jan 3, 2026). In contrast, DeepSeek's V3 MoE model achieved better results with a lower training cost of $5.6 million and offers modularity, allowing for independent fine-tuning and capability upgrades. For AI businesses and developers, MoE architectures present a scalable, cost-effective approach that supports rapid innovation and targeted enhancements, widening the gap between dense and modular AI models for open-source development.