The Blind Spot in GPU Monitoring: How Hybrid MoE Models Hide Performance Bottlenecks

As hybrid MoE models like NVIDIA's Nemotron rapidly gain adoption, current inference monitoring dashboards expose a critical blind spot: they measure aggregate GPU utilization but miss per-layer performance bottlenecks. While dashboards report 95%+ GPU usage, the actual tail latency is dominated by MoE all-to-all collective communication patterns that escape standard metrics. Understanding these hidden stalls is becoming essential for optimizing inference engines and preventing performance degradation.