Introducing NVads V710 v5 series VMs

Cost-optimized AI inference, virtual workstations, and cloud gaming.

AI inferencing and graphics-intensive applications continue to demand cost-effective, low power, high performance GPUs with more GPU memory and faster CPUs.  Today we are thrilled to announce the General Availability of NVads V710 v5-series virtual machines (VMs) to expand our NV VM lineup to meet these very needs.

As we mentioned in our previous preview announcement, customers running small-to-medium AI/ML inferencing workloads, Virtual Desktop Infrastructure (VDI), visualization, and cloud gaming workloads need NVads V710 v5-series VMs.  Each VM is powered by an AMD Radeon™ Pro V710 GPU with up to 28 GB of GPU memory, which easily serves popular small open-source language models and handles the most demanding visualization scenarios.  On top of this, the vCPU cores are backed by high-frequency 4th Generation AMD EPYC™ CPUs (3.9 GHz base and 4.3 GHz max frequency) for compute-intensive workloads that demand both CPU and GPU performance.

Right size the VM for your workload needs.

With NVads V710 v5 VMs, you only pay for the GPU/CPU compute you need.  GPU partitioning capabilities enable customers to allocate fractions of the GPU – as small as 1/6^th of a V710 GPU – according to their workload requirements. This flexibility is ideal for customers that need to support a variety of inferencing and graphical workloads efficiently without requiring a full GPU for each application.  The series provides several options ranging from 1/6 of a GPU with 4 GB of memory, perfect for lightweight virtual desktop experiences, to a full V710 GPU with a massive 28 GB for graphics intensive engineering applications or AI.

Out of the box performance with ROCm and Radeon PRO Graphics.

AMD Radeon PRO Graphics provides a seamless and reliable experience for visualization-focused workloads.  The GPU and drivers are optimized or certified for all the major ISV solutions from vendors such as Adobe and Autodesk.  They also support the latest ROCm releases and are designed to seamlessly integrate with popular machine learning frameworks like PyTorch, Triton, ONNX, and vLLM to serve small to medium language models.

Upgrade to get up to 2.5x boost.

Our own internal benchmarks of popular VDI, rendering, and visualization tests show NVads V710 v5 VMs are up to 2.5x faster when compared to NV v4 VMs.  This means you can get more work done, faster, and have an overall better experience.

Microsoft internal benchmarking between Standard_NV32as_v4 and Standard_NV24ads_V710_v5 instances.

Customer Momentum

At Azure, we work closely with our partners and customers so they can take full advantage of these new VMs and accelerate their applications. Listen to what our partners at Dizzion, Cognata, and NAIO had to say.

	"The new Azure NVads V710 instances, powered by AMD Radeon Pro V710 GPUs, offer exceptional performance and flexibility at competitive prices. Dizzion Desktop as a Service customers delivering CAD, BIM, edge AI, and other high-performance workloads have eagerly awaited this addition to the market.” – Ruben Spruijt, Field CTO, Dizzion
	“In our experience, the V710 delivers excellent performance across both CPU and GPU workloads, making it a highly capable platform for a wide range of use cases. It offers a robust and reliable software stack, particularly well-suited for OpenGL and machine learning applications.” – Danny Atsmon, CEO, Cognata
	“We’ve tested the V710 thoroughly across a range of AI workloads, and the performance has really impressed us. It’s fast, stable, and scales well across different scenarios. It’s become a reliable, cost-effective part of our stack, and we’ll keep building on top of it as we expand our projects.” – Dr.-Ing. Timo Sämann, Chief AI Scientist, NAIO

Product Details

NVads V710 v5 VMs, now available in 5 Azure regions.

We are happy to announce NVads V710 v5 VMs are now available in East US, North Central US, South Central US, West US, and West Europe.  To learn more about our VMs and how to get started, please visit our documentation page.