In the news
When One GPU Isn’t Enough: Serving GLM-5.3 Across Two NVIDIA DGX Stations with vLLM
NVIDIA Developer · Published · 3 min read
In 30 seconds
- What happened
- NVIDIA demonstrated serving GLM-5.3, a 753-billion-parameter model, across two DGX Stations using vLLM with tensor parallelism and RDMA connectivity.
- Why it matters
- Engineers deploying frontier-scale language models that exceed single-GPU memory must distribute weights across multiple machines while maintaining unified inference endpoints.
- Watch out
- 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.
- llm
- quantiz
- serving
- vllm
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