NVIDIA RTX A6000

POWERED BY THE NVIDIA AMPERE ARCHITECTURE

NVIDIA Ampere Architecture CUDA

Double-speed processing for single-precision floating point (FP32) operations and improved power efficiency provide significant performance improvements for graphics and simulation workflows, such as complex 3D computer-aided design (CAD) and computer-aided engineering (CAE), on the desktop.

Second-Generation RT Cores

With up to 2X the throughput over the previous generation and the ability to concurrently run ray tracing with either shading or denoising capabilities, second-generation RT Cores deliver massive speedups for workloads like photorealistic rendering, architectural design, and virtual prototyping of product designs.

3rd-Gen Tensor Cores

New Tensor Float 32 (TF32) precision provides up to 5X the training throughput over the previous generation to accelerate AI and data science without requiring any code changes. Hardware support for structural sparsity doubles the throughput for inferencing. Tensor Cores also bring AI to graphics with capabilities like DLSS, AI denoising.

48GB of GPU Memory

Ultra-fast GDDR6 memory, scalable up to 96 GB with NVLink, gives data scientists, engineers, and creative professionals the large memory necessary to work with massive datasets and workloads like data science and simulation.

Power Efficiency

Featuring a dual-slot, power efficient design, the RTX A6000 is up to 2X more power efficient than Turing GPUs and crafted to fit into a wide range of workstations from worldwide OEM vendors.

PCI Express Gen 4

Support for PCI Express Gen 4 provides double the bandwidth of PCIe Gen 3, improving data-transfer speeds from CPU memory for data-intensive tasks like AI and data science.

Virtualization-Ready

Support for NVIDIA virtual GPU (vGPU) software allows a personal workstation to be repurposed into multiple high-performance virtual workstation instances  enabling remote users, to share resources to drive high-end design, AI, and compute workloads.

3rd-Gen NVIDIA NVLink

Increased GPU-to-GPU interconnect bandwidth provides a single scalable memory to accelerate graphics and compute workloads and tackle larger datasets.