SemiAnalysis Says AI Inference Bottlenecks Are Shifting Toward Memory Bandwidth and Scheduling
A SemiAnalysis report says MoE inference efficiency depends more on memory bandwidth, scheduling, and tiered KV cache management, and forecasts that a single pipeline stage may require approximately 400 to 500GB of local high-speed memory in 2027.