Scaling AI and analytics can lead to growing costs as queries consume more resources, especially when dashboards refresh or AI agents query data sources. Understanding the actual cost of a single query becomes crucial to manage budgets effectively. Cube Cloud offers a standardized benchmark comparison with direct queries to modern cloud data platforms, showcasing its compute model's predictability and lower costs per query, particularly at high throughput. Unlike traditional cloud data warehouses, which charge based on compute time, concurrency scaling, query complexity, and data scanned, Cube Cloud uses an API instance and worker compute usage-based pricing, focusing on throughput rather than query volume or data complexity. The benchmark results demonstrate that as volume increases, the cost per query in Cube Cloud decreases drastically, while the cost per query in traditional Data Warehouses decreases at a slower rate. This fundamental shift enables massive savings, especially once reaching high-volume territory, making Cube Cloud an attractive option for analytics architecture optimization and operational efficiency.