
VentureBeat
Cheaper tokens, bigger bills: The new math of AI infrastructure
As enterprises transition from AI experimentation to production, the focus shifts from model training to the infrastructure necessary for efficiently managing concurrent inference workloads. This new landscape, driven by agentic AI, demands continuous support for unpredictable requests, highlighting the importance of infrastructure efficiency. Anindo Sengupta from Nutanix underscores that while costs per token have decreased, overall expenses are rising due to increased consumption. To thrive, organizations must adapt their infrastructure strategies, prioritizing metrics like GPU utilization and total cost of ownership for sustainable AI deployment.






















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