NVIDIA RTX 4000 SFF Ada Generation
About GPU
The NVIDIA RTX 4000 SFF Ada Generation GPU is a powerful and impressive piece of hardware for professional use. With a base clock of 720MHz and a boost clock of 1560MHz, this GPU offers high-performance capabilities for demanding professional applications. The 20GB of GDDR6 memory coupled with a memory clock of 1750MHz ensures smooth and efficient operation even when dealing with large, complex datasets.
The 6144 shading units and 48MB of L2 cache further contribute to the GPU's ability to handle intensive workloads, making it a reliable choice for professionals working in fields such as data science, engineering, and content creation.
Despite its impressive performance capabilities, the NVIDIA RTX 4000 SFF Ada Generation GPU remains energy-efficient, boasting a TDP of 70W. This means that it can deliver high-end performance without excessive power consumption, making it a practical choice for a wide range of professional applications.
With a theoretical performance of 19.17 TFLOPS, this GPU is capable of handling the most demanding computational tasks with ease. Overall, the NVIDIA RTX 4000 SFF Ada Generation GPU is a top-tier choice for professionals seeking high-performance, energy-efficient computing solutions.
Basic
Label Name
NVIDIA
Platform
Professional
Launch Date
March 2023
Model Name
RTX 4000 SFF Ada Generation
Generation
Quadro Ada
Base Clock
720MHz
Boost Clock
1560MHz
Bus Interface
PCIe 4.0 x16
Memory Specifications
Memory Size
20GB
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.
160bit
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.
280.0 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.
124.8 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.
299.5 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.
19.17 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.
299.5 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.
18.787
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.
48
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.
6144
L1 Cache
128 KB (per SM)
L2 Cache
48MB
TDP
70W
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
18.787
TFLOPS
Blender
Score
4561
Vulkan
Score
105965
OpenCL
Score
122596
Compared to Other GPU
FP32 (float)
/ TFLOPS
Blender
Vulkan
OpenCL