NVIDIA Quadro RTX 6000

NVIDIA Quadro RTX 6000

About GPU

The NVIDIA Quadro RTX 6000 is a powerhouse of a GPU designed for professional use, and it certainly lives up to that expectation. With a base clock of 1440MHz and a boost clock of 1770MHz, this GPU delivers exceptional performance that is essential for demanding professional workflows. One of the most impressive features of the Quadro RTX 6000 is its massive 24GB of GDDR6 memory, ensuring that even the most complex and data-intensive tasks can be handled with ease. The memory clock of 1750MHz further enhances its capability to handle large datasets and compute-intensive workloads. With 4608 shading units and 6MB of L2 cache, this GPU is able to handle large-scale rendering, complex simulations, and AI-driven applications without breaking a sweat. In terms of power consumption, the Quadro RTX 6000 has a TDP of 260W, which is impressive considering the level of performance it delivers. It strikes a good balance between power efficiency and raw processing power. The theoretical performance of 16.31 TFLOPS further solidifies the Quadro RTX 6000 as a top-tier professional GPU, capable of handling the most demanding tasks with ease. Overall, the NVIDIA Quadro RTX 6000 is a top-of-the-line GPU that is well-suited for professional workloads such as 3D rendering, visual effects, and scientific simulations. Its impressive specs and performance make it a worthy investment for professionals who require the best in terms of GPU performance.

Basic

Label Name
NVIDIA
Platform
Professional
Launch Date
August 2018
Model Name
Quadro RTX 6000
Generation
Quadro
Base Clock
1440MHz
Boost Clock
1770MHz
Bus Interface
PCIe 3.0 x16

Memory Specifications

Memory Size
24GB
Memory Type
GDDR6
Memory Bus
?
The memory bus width refers to the number of bits of data that the video memory can transfer within a single clock cycle. The larger the bus width, the greater the amount of data that can be transmitted instantaneously, making it one of the crucial parameters of video memory. The memory bandwidth is calculated as: Memory Bandwidth = Memory Frequency x Memory Bus Width / 8. Therefore, when the memory frequencies are similar, the memory bus width will determine the size of the memory bandwidth.
384bit
Memory Clock
1750MHz
Bandwidth
?
Memory bandwidth refers to the data transfer rate between the graphics chip and the video memory. It is measured in bytes per second, and the formula to calculate it is: memory bandwidth = working frequency × memory bus width / 8 bits.
672.0 GB/s

Theoretical Performance

Pixel Rate
?
Pixel fill rate refers to the number of pixels a graphics processing unit (GPU) can render per second, measured in MPixels/s (million pixels per second) or GPixels/s (billion pixels per second). It is the most commonly used metric to evaluate the pixel processing performance of a graphics card.
169.9 GPixel/s
Texture Rate
?
Texture fill rate refers to the number of texture map elements (texels) that a GPU can map to pixels in a single second.
509.8 GTexel/s
FP16 (half)
?
An important metric for measuring GPU performance is floating-point computing capability. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy.
32.62 TFLOPS
FP64 (double)
?
An important metric for measuring GPU performance is floating-point computing capability. Double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy, while single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.
509.8 GFLOPS
FP32 (float)
?
An important metric for measuring GPU performance is floating-point computing capability. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.
15.984 TFLOPS

Miscellaneous

SM Count
?
Multiple Streaming Processors (SPs), along with other resources, form a Streaming Multiprocessor (SM), which is also referred to as a GPU's major core. These additional resources include components such as warp schedulers, registers, and shared memory. The SM can be considered the heart of the GPU, similar to a CPU core, with registers and shared memory being scarce resources within the SM.
72
Shading Units
?
The most fundamental processing unit is the Streaming Processor (SP), where specific instructions and tasks are executed. GPUs perform parallel computing, which means multiple SPs work simultaneously to process tasks.
4608
L1 Cache
64 KB (per SM)
L2 Cache
6MB
TDP
260W
Vulkan Version
?
Vulkan is a cross-platform graphics and compute API by Khronos Group, offering high performance and low CPU overhead. It lets developers control the GPU directly, reduces rendering overhead, and supports multi-threading and multi-core processors.
1.3
OpenCL Version
3.0

Benchmarks

FP32 (float)
Score
15.984 TFLOPS
OpenCL
Score
74179

Compared to Other GPU

FP32 (float) / TFLOPS
18.787 +17.5%
16.856 +5.5%
14.808 -7.4%
OpenCL
171826 +131.6%
112550 +51.7%
56310 -24.1%
34533 -53.4%