NVIDIA details deploying GLM-5.3 on dual DGX Stations
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NVIDIA publishes a technical blog post detailing how to deploy GLM-5.3 on two DGX Stations. The two machines are interconnected via ConnectX-8 RDMA, and with vLLM's tensor parallelism, the model weights and computation are split across the two GPUs, serving inference through a single endpoint. The model used is NVIDIA GLM-5.3 NVFP4, a quantized version of Z.ai's mixture-of-experts model.
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- NVIDIA Technical BlogWhen One GPU Isn’t Enough: Serving GLM-5.3 Across Two NVIDIA DGX Stations with vLLM
Running a frontier-scale model locally requires keeping all its weights in GPU memory, and the largest models no longer fit on one machine. Two NVIDIA DGX Stations connected over ConnectX-8 RDMA serve one model through a single endpoint, with tensor parallelism splitting the model weights and computation across both GPUs. The NVIDIA GLM-5.3 NVFP4 model is described as a quantized version of Z.ai's mixture-of-experts model.
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