Organizations training and deploying large AI models need infrastructure that won't slow them down. This blog post highlights Microsoft's latest AI-optimized Azure virtual machines — including new ND H200 v5 instances powered by NVIDIA H100 Tensor Core GPUs — and explains how they support compute-intensive workloads for faster innovation. Read the blog to understand the performance breakthroughs. Contact AGJ Systems and Networks for help planning your next AI deployment on Azure.
What are Azure ND H200 v5 Virtual Machines?
The Azure ND H200 v5 series virtual machines are cloud-based AI-supercomputing clusters designed to support advanced AI workloads. They are optimized for tasks such as foundational model training and generative inferencing, providing scalable and high-performance infrastructure to help businesses develop innovative AI-driven solutions.
What improvements do the ND H200 v5 VMs offer?
The ND H200 v5 VMs feature an increase of 76% in High Bandwidth Memory (HBM) to 141GB and a 43% increase in HBM Bandwidth to 4.8 TB/s compared to the ND H100 v5 series. These enhancements allow for faster access to model parameters, reducing application latency, and enabling the handling of more complex Large Language Models (LLMs) within a single VM.
How do ND H200 v5 VMs support AI workloads?
The ND H200 v5 VMs are designed to manage GPU memory more efficiently for model weights and batch sizes, which directly impacts throughput and latency in generative AI inference workloads. Early tests have shown up to a 35% increase in throughput for inference tasks compared to the ND H100 v5 series, making them suitable for both small and large language models.
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