Investing in AI models requires infrastructure that effectively connects workloads to GPU telemetry for optimal performance assessment. By monitoring key operational signals like utilization, power, and temperature, teams can make informed decisions regarding capacity needs and model efficiency. This data allows for comparisons between model choices and helps troubleshoot performance discrepancies, ultimately transforming raw telemetry into actionable insights for better model economics and cost management.