When One GPU Isn’t Enough: Serving GLM-5.3 Across Two NVIDIA DGX Stations with vLLM

In 30 Sekunden

Was passiert ist

NVIDIA demonstrated serving GLM-5.3, a 753-billion-parameter model, across two DGX Stations using vLLM with tensor parallelism and RDMA connectivity.

Warum es zählt

Engineers deploying frontier-scale language models that exceed single-GPU memory must distribute weights across multiple machines while maintaining unified inference endpoints.

Achtung

Throughput degrades significantly under high concurrency: 607.8 tokens per second at 16 concurrent requests drops to 385.0 at 32 requests with 453-second latency.