The insight brief, AI Infrastructure & GPU Cost: The Cheapest GPU Is the Most Expensive Way to Ship, advises AI-native startups to look beyond low hourly GPU pricing when managing infrastructure costs. While the immediate instinct is often to choose the cheapest available GPUs, the report argues that this approach can increase overall expenses, slow development, and negatively impact business outcomes. For CTOs and machine learning leaders, the true cost of AI infrastructure includes factors such as performance, reliability, utilization rates, job completion time, scalability, and operational efficiency. As AI compute becomes one of the largest spending categories for GPU-intensive companies, especially those training and deploying advanced models, organizations must optimize for productiv

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