Shruti Koparkar

Senior Manager of Product Marketing in NVIDIA’s Accelerated Computing group, focused on AI inference. Her work covers AI-infrastructure economics and tokenomics, including token utility, demand, supply, monetization, and inference efficiency; she previously held product marketing roles at AWS and Arm.

Cost Per Token Is Replacing FLOPS as the AI Infrastructure Metric

Shruti Koparkar of NVIDIA’s Accelerated Computing team argues that AI infrastructure should be evaluated by token economics rather than by GPU-hour pricing or FLOPS per dollar. On NVIDIA’s AI Podcast, she lays out a four-part framework — token utility, supply, demand and monetization — in which cost per token becomes the central measure of business value. Koparkar says NVIDIA Blackwell’s system-level design delivers 50 times more tokens per watt than Hopper and 35 times lower token cost, while lower token costs will expand GPU demand by making more AI workloads economically viable.

NVIDIAMay 21, 202612 min read