Real-World GPU VM Options by Cloud Provider

All major cloud providers offer GPU-enabled virtual machines powered by NVIDIA hardware. Below are common VM families and the GPUs they support for machine learning workloads.

AWS GPU Instances

Amazon Web Services provides several EC2 instance families designed for GPU acceleration. These instances are commonly used for deep learning training and inference.

• p3 instances – NVIDIA V100 GPUs, suitable for deep learning training and high-performance computing.
• p4d instances – NVIDIA A100 GPUs, optimized for large-scale distributed training and advanced AI workloads.
• g4dn instances – NVIDIA T4 GPUs, commonly used for inference, video processing, and lightweight training.
• g5 instances – NVIDIA A10G GPUs, offering strong performance for both training and real-time inference.

Google Cloud Platform (GCP) GPU Instances

GCP allows GPUs to be attached to Compute Engine virtual machines, offering flexibility across multiple machine types.

• A2 machine series – NVIDIA A100 GPUs, designed specifically for large-scale machine learning and deep learning workloads.
• N1 / N2 machine types – Support NVIDIA T4 and V100 GPUs for general-purpose ML tasks.
• G2 machine series – NVIDIA L4 GPUs, optimized for inference, media processing, and energy-efficient AI workloads.

Microsoft Azure GPU Virtual Machines

Azure offers multiple GPU-focused VM families tailored to different AI and compute use cases.

• NC-series – NVIDIA T4 and V100 GPUs, commonly used for machine learning training and inference.
• ND-series – NVIDIA A100 GPUs, optimized for large-scale deep learning and distributed training.
• NV-series – NVIDIA GPUs optimized for visualization, rendering, and GPU-accelerated applications.

Choosing the Right GPU

Selecting the right VM and GPU depends on workload size, training complexity, and budget. GPUs like the T4 and L4 are well-suited for inference, while V100 and A100 GPUs excel at large-scale training and high-performance deep learning.

All of these GPU instances rely on NVIDIA drivers and CUDA to deliver maximum performance for machine learning frameworks.