Hi @Andrew Haselhan,
Welcome to the Microsoft Q&A Platform! Thank you for asking your question here.
We see from your query that you're having an issue. Here is the solution we suggest:
NC-series VMs are ideal for training complex machine learning models and running AI applications. The NVIDIA GPUs provide significant acceleration for computations typically involved in deep learning and other intensive training tasks.
Please refer to this link for more information: https://learn.microsoft.com/en-us/azure/virtual-machines/sizes/gpu-accelerated/nc-family#workloads-and-use-cases
In this case you need to select a VM with 1 GPU to match the NVIDIA AI Enterprise is NCads_H100_v5 sizes series.
The NCads H100 v5 series virtual machines (VMs) are a new addition to the Azure GPU family. You can use this series for real-world Azure Applied AI training and batch inference workloads. The NCads H100 v5 series virtual machines are powered by NVIDIA H100 NVL GPU and 4th-generation AMD EPYC™ Genoa processors. The VMs feature up to 2 NVIDIA H100 NVL GPUs with 94GB memory each, up to 96 non-multithreaded AMD EPYC Genoa processor cores and 640 GiB of system memory. These VMs are ideal for real-world Applied AI workloads.
For more detailed information please refer to this: https://learn.microsoft.com/en-us/azure/virtual-machines/sizes/gpu-accelerated/ncadsh100v5-series?tabs=sizeaccelerators
To run a virtual machine with NVIDIA AI Enterprise, you need to request a quota for the specific GPU model you want to use in each region, as well as a global quota.
If you have any further queries, do let us know.
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