Scalable Multi GPU


Bring accelerated performance to every enterprise workload with NVIDIA A30 Tensor Core GPUs. With NVIDIA Ampere architecture Tensor Cores and Multi-Instance GPU (MIG), it delivers speedups securely across diverse workloads, including AI inference at scale and high-performance computing (HPC) applications.

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The Data Center Solution for Modern IT

Deep Learning

Tensor Cores with Tensor Float (TF32) provide up to 10X higher performance over the NVIDIA T4.


Up To 3X higher throughput than V100 at real-time conversational AI and T4 at real-time image classification.


Features FP64 NVIDIA Ampere architecture Tensor Cores that deliver the biggest leap in HPC performance since the introduction of GPUs.


With MIG, an A30 GPU can be partitioned into as many as four independent instances, giving multiple users access to GPU acceleration.



FP64 5.2 teraFLOPS
FP64 Tensor Core 10.3 teraFLOPS
FP32 10.3 teraFLOPS
TF32 Tensor Core 82 teraFLOPS | 165 teraFLOPS*
BFLOAT16 Tensor Core 165 teraFLOPS | 330 teraFLOPS*
FP16 Tensor Core 165 teraFLOPS | 330 teraFLOPS*
INT8 Tensor Core 330 TOPS | 661 TOPS*
INT4 Tensor Core 661 TOPS | 1321 TOPS*
Media engines 1 optical flow accelerator (OFA)
1 JPEG decoder (NVJPEG)
4 video decoders (NVDEC)
GPU memory 24GB HBM2
GPU memory bandwidth 933GB/s
Interconnect PCIe Gen4: 64GB/s
Third-gen NVLINK: 200GB/s**
Form factor Dual-slot, full-height, full-length (FHFL)
Max thermal design power (TDP) 165W
Multi-Instance GPU (MIG) 4 GPU instances @ 6GB each
2 GPU instances @ 12GB each
1 GPU instance @ 24GB
Virtual GPU (vGPU) software support NVIDIA AI Enterprise
NVIDIA Virtual Compute Server
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