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articles/virtual-machines/sizes-gpu.md

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@@ -21,7 +21,8 @@ GPU optimized VM sizes are specialized virtual machines available with single, m
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- The [NCv3-series](ncv3-series.md) and [NC T4_v3-series](nct4-v3-series.md) sizes are optimized for compute-intensive GPU-accelerated applications. Some examples are CUDA and OpenCL-based applications and simulations, AI, and Deep Learning. The NC T4 v3-series is focused on inference workloads featuring NVIDIA's Tesla T4 GPU and AMD EPYC2 Rome processor. The NCv3-series is focused on high-performance computing and AI workloads featuring NVIDIA’s Tesla V100 GPU.
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- The [NC 100 v4-series](nc-a100-v4-series.md) sizes are focused on midrange AI training and batch inference workload. The NC A100 v4-series offers flexibility to select one, two, or four NVIDIA A100 80GB PCIe Tensor Core GPUs per VM to leverage the right-size GPU acceleration for your workload.
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- The [NC 100 v4-series](nc-a100-v4-series.md) sizes are focused on midrange AI training and batch inference workload. The NC A100 v4-series offers flexibility to select one, two, or four NVIDIA A100 80GB PCIe Tensor Core GPUs per VM to leverage the right-size GPU acceleration for your workload.
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- The [ND A100 v4-series](nda100-v4-series.md) sizes are focused on scale-up and scale-out deep learning training and accelerated HPC applications. The ND A100 v4-series uses 8 NVIDIA A100 TensorCore GPUs, each available with a 200 Gigabit Mellanox InfiniBand HDR connection and 40 GB of GPU memory.
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- [NGads V620-series](ngads-v-620-series.md) VM sizes are optimized for high performance, interactive gaming experiences hosted in Azure. They're powered by AMD Radeon PRO V620 GPUs and AMD EPYC 7763 (Milan) CPUs.

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