NCasT4_v3-series (In Preview)
The NCasT4_v3-series virtual machines are powered by Nvidia Tesla T4 GPUs and AMD EPYC 7V12(Rome) CPUs. The VMs feature up to 4 NVIDIA T4 GPUs with 16 GB of memory each, up to 64 non-multithreaded AMD EPYC 7V12 (Rome) processor cores, and 440 GiB of system memory. These virtual machines are ideal for deploying AI services- such as real-time inferencing of user generated requests, or for interactive graphics and visualization workloads using NVIDIA's GRID driver and virtual GPU technology. Standard GPU compute workloads based around CUDA, TensorRT, Caffe, ONNX and other frameworks, or GPU-accelerated graphical applications based OpenGL and DirectX can be deployed economically, with close proximity to users, on the NCasT4_v3 series.
You can submit a request to be part of the preview program.
Premium Storage: Supported
Premium Storage caching: Supported
Live Migration: Not Supported
Memory Preserving Updates: Not Supported
|Size||vCPU||Memory: GiB||Temp storage (SSD) GiB||GPU||GPU memory: GiB||Max data disks||Max NICs|
Size table definitions
Storage capacity is shown in units of GiB or 1024^3 bytes. When you compare disks measured in GB (1000^3 bytes) to disks measured in GiB (1024^3) remember that capacity numbers given in GiB may appear smaller. For example, 1023 GiB = 1098.4 GB.
Disk throughput is measured in input/output operations per second (IOPS) and MBps where MBps = 10^6 bytes/sec.
Data disks can operate in cached or uncached modes. For cached data disk operation, the host cache mode is set to ReadOnly or ReadWrite. For uncached data disk operation, the host cache mode is set to None.
If you want to get the best performance for your VMs, you should limit the number of data disks to two disks per vCPU.
Expected network bandwidth is the maximum aggregated bandwidth allocated per VM type across all NICs, for all destinations. For more information, see Virtual machine network bandwidth.
Upper limits aren't guaranteed. Limits offer guidance for selecting the right VM type for the intended application. Actual network performance will depend on several factors including network congestion, application loads, and network settings. For information on optimizing network throughput, see Optimize network throughput for Azure virtual machines. To achieve the expected network performance on Linux or Windows, you may need to select a specific version or optimize your VM. For more information, see Bandwidth/Throughput testing (NTTTCP).
Supported operating systems and drivers
To take advantage of the GPU capabilities of Azure NCasT4_v3-series VMs running Windows or Linux, Nvidia GPU drivers must be installed.
To install Nvidia GPU drivers manually, see N-series GPU driver setup for Windows for supported operating systems, drivers, installation, and verification steps.
- General purpose
- Memory optimized
- Storage optimized
- GPU optimized
- High performance compute
- Previous generations
Learn more about how Azure compute units (ACU) can help you compare compute performance across Azure SKUs.