Powered by the NVIDIA Turing architecture and the NVIDIA RTX platform, the PNY NVIDIA Quadro RTX 5000 Graphics Card fuses ray tracing, deep learning, and advanced shading to provide creative and technical professionals the power they need to keep up with their workflows.
Equipped with 3072 CUDA cores, 384 Tensor Cores, 48 RT Cores, and 16GB of GDDR6 VRAM, the Quadro RTX 5000 can render complex models and scenes with accurate shadows, reflections, and refractions. There are four DisplayPort 1.4 outputs that support up to four displays at 4096 x 2160 at 120 Hz or 5120 x 2880 at 60 Hz. You can also opt for dual displays at 7680 x 4320 at 60 Hz. The USB Type-C port provides VirtualLink support and is VR ready.
Real-Time Ray Tracing
The NVIDIA GeForce RTX platform enables real-time ray tracing of objects and environments with physically accurate shadows, reflections, refractions, and global illumination. The RTX 5000 features 8 GigaRays per second and up to 62T RTX-OPS*.
*Equivalent aggregate math operations contributed by the Turing Shaders, CUDA Cores, Tensor Cores, and RT Cores needed to render RTX graphics.
*Equivalent aggregate math operations contributed by the Turing Shaders, CUDA Cores, Tensor Cores, and RT Cores needed to render RTX graphics.
USB Type-C with VirtualLink
VirtualLink is an open industry standard that enables next-gen VR headsets to connect with PCs and other devices using a single, high-bandwidth USB Type-C connector. The Alternate Mode of USB Type-C simplifies and speeds up VR setup time, avoiding key obstacles to VR adoption. VirtualLink connects with VR headsets to simultaneously deliver four high-speed HBR3 DisplayPort lanes, which are scalable for future uses, a USB 3.1 Gen 2 data channel for supporting high-resolution cameras and sensors, and provides up to 27 watts of power.
NVLink Support
This GPU supports NVLink, which enables applications to scale memory and performance with multi-GPU configurations.
CUDA
NVIDIA's parallel computing platform which enables an increase in computing performance by harnessing the parallel nature of GPU processing. CUDA-compatible applications can assign intensive parallel computing tasks, such as real-time video rendering, to the GPU to process, freeing up the computer's CPU to run other tasks.