NVIDIA RTX A5000-12Q
About GPU
The NVIDIA RTX A5000-12Q GPU is a powerful and efficient graphics card that is designed for professional use in desktop workstations. With a base clock of 1170MHz and a boost clock of 1695MHz, it offers fast and reliable performance for a wide variety of demanding applications.
One of the key features of the RTX A5000 is its 12GB of GDDR6 memory, which provides ample room for handling large datasets and complex visualizations. The memory clock running at 2000MHz ensures smooth and seamless operations, even when working with high-resolution content. Additionally, with 8192 shading units and 6MB of L2 cache, this GPU is capable of handling complex rendering tasks with ease.
In terms of power consumption, the RTX A5000 has a TDP of 230W, making it relatively efficient compared to other high-end GPUs in its class. Despite its lower power consumption, it still delivers impressive performance, with a theoretical peak performance of 27.215 TFLOPS.
Overall, the NVIDIA RTX A5000-12Q GPU is a top-of-the-line option for professionals in fields such as design, engineering, and content creation. Its combination of high memory capacity, efficient power usage, and impressive performance make it a great choice for those who require a reliable and high-performing GPU for their intensive tasks. While it may be pricier than consumer-grade GPUs, its capabilities are well worth the investment for those who need the best performance and reliability in their work.
Basic
Label Name
NVIDIA
Platform
Desktop
Launch Date
April 2021
Model Name
RTX A5000-12Q
Generation
Quadro Ampere
Base Clock
1170MHz
Boost Clock
1695MHz
Bus Interface
PCIe 4.0 x16
Memory Specifications
Memory Size
12GB
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
2000MHz
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.
768.0 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.
162.7 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.
433.9 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.
27.77 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.
433.9 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.
27.215
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.
64
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.
8192
L1 Cache
128 KB (per SM)
L2 Cache
6MB
TDP
230W
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
27.215
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS