[D] - 1M tokens/second serving Qwen 3.5 27B on B200 GPUs, benchmark results and findings

Wrote up the process of pushing Qwen 3.5 27B (dense, FP8) to 1.1M total tok/s on 96 B200 GPUs with vLLM v0.18.0. DP=8 nearly 4x'd throughput over TP=8. Model is too small for tensor parallelism to help on B200s. MTP-1 mattered than anything else (GPU utilization was 0% without it). MTP-5 crashed with cudaErrorIllegalAddress. 97.1% scaling efficiency at 8 nodes, 96.5% at 12. TPOT flat at ~46ms regardless of node count. Inference Gateway (KV-cache-aware routing) added ~35% overhead vs ClusterIP round-robin. Single EPP pod is the bottleneck.