PNY NVA30TCGPU-KIT NVIDIA A30 24 GB HBM2 Graphic Card

MPN: NVA30TCGPU-KIT
PNY NVA30TCGPU-KIT NVIDIA A30 24 GB HBM2 Graphic Card
In Stock
Highlights
  • Standard Memory: 24 GB
  • Host Interface: PCI Express 4.0
  • Cooler Type: Passive Cooler
  • Product Type: Graphic Card
$4,875.00
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Non-cancelable and non-returnable
B2B pricing options available.

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PNY NVA30TCGPU-KIT NVIDIA A30 24 GB HBM2 Graphic Card
MPN: NVA30TCGPU-KIT

$4,875.00

Non-cancelable and non-returnable

PNY NVA30TCGPU-KIT NVIDIA A30 24 GB HBM2 Graphic Card

In Stock
Highlights
  • Standard Memory: 24 GB
  • Host Interface: PCI Express 4.0
  • Cooler Type: Passive Cooler
  • Product Type: Graphic Card
B2B pricing options available.

SabrePC B2B Account Services

Save instantly and shop with assurance knowing that you have a dedicated account team a phone call or email away to help answer any of your questions with a B2B account.

  • Business-Only Pricing
  • Personalized Quotes
  • Fast Delivery
  • Products and Support

NVIDIA A30 | Versatile Compute Acceleration for Mainstream Enterprise Servers

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. By combining fast memory bandwidth and low-power consumption in a PCIe form factor optimized for mainstream servers, A30 enables an elastic data center and delivers maximum value for enterprises.

The NVIDIA A30 Tensor Core GPU delivers a versatile platform for mainstream enterprise workloads, like AI inference, training, and HPC. With TF32 and FP64 Tensor Core support, as well as an end-to-end software and hardware solution stack, A30 ensures that mainstream AI training and HPC applications can be rapidly addressed. Multi-instance GPU (MIG) ensures quality of service (QoS) with secure, hardware-partitioned, right-sized GPUs across all of these workloads for diverse users, optimally utilizing GPU compute resources.