Why Memory Bandwidth, Not FLOPS, Is the Real AI Inference Bottleneck
ai · x · 2026-10-06
AI hardware attention is shifting from raw GPU compute to memory and interconnects. Using NVIDIA's H100 SXM (989 TFLOPS dense BF16, 80 GB, 3.35 TB/s) and Llama 3.1 70B (70.6B weights, 141 GB in BF16) as a worked example: dense token generation touches every weight, so the bottleneck is moving massive data close to compute—explaining why memory bandwidth and chip interconnects now matter more than ever.
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