NVIDIA Quadro RTX 4000 Mobile
About GPU
The NVIDIA Quadro RTX 4000 Mobile GPU is a high-performance professional grade graphics card designed for professionals who require top-tier graphics processing power. With a base clock speed of 1110MHz and a boost clock speed of 1560MHz, this GPU offers impressive performance for a wide range of professional applications.
With 8GB of GDDR6 memory and a memory clock speed of 1750MHz, the Quadro RTX 4000 ensures that demanding workloads can be handled with ease. The 2560 shading units and 4MB L2 cache further contribute to the GPU's ability to handle complex tasks with precision and efficiency.
One of the standout features of the Quadro RTX 4000 is its TDP of 110W, making it a relatively power-efficient option considering its impressive performance capabilities. This is particularly advantageous for professionals who require high-end graphics performance in a mobile workstation.
The theoretical performance of 7.987 TFLOPS showcases the GPU's ability to handle complex rendering, simulation, and visualization tasks with ease. Whether it's 3D modeling, animation, virtual reality, or deep learning, the Quadro RTX 4000 delivers the power and reliability demanded by professional users.
Overall, the NVIDIA Quadro RTX 4000 Mobile GPU is a top-tier graphics card that offers exceptional performance, efficiency, and reliability for professional applications. It is an excellent choice for those in need of high-performance computing power for demanding workloads.
Basic
Label Name
NVIDIA
Platform
Professional
Launch Date
May 2019
Model Name
Quadro RTX 4000 Mobile
Generation
Quadro Mobile
Base Clock
1110MHz
Boost Clock
1560MHz
Bus Interface
PCIe 3.0 x16
Transistors
13,600 million
RT Cores
40
Tensor Cores
?
Tensor Cores are specialized processing units designed specifically for deep learning, providing higher training and inference performance compared to FP32 training. They enable rapid computations in areas such as computer vision, natural language processing, speech recognition, text-to-speech conversion, and personalized recommendations. The two most notable applications of Tensor Cores are DLSS (Deep Learning Super Sampling) and AI Denoiser for noise reduction.
320
TMUs
?
Texture Mapping Units (TMUs) serve as components of the GPU, which are capable of rotating, scaling, and distorting binary images, and then placing them as textures onto any plane of a given 3D model. This process is called texture mapping.
160
Foundry
TSMC
Process Size
12 nm
Architecture
Turing
Memory Specifications
Memory Size
8GB
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.
256bit
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.
448.0 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.
99.84 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.
249.6 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.
15.97 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.
249.6 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.
8.147
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.
40
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.
2560
L1 Cache
64 KB (per SM)
L2 Cache
4MB
TDP
110W
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
OpenGL
4.6
DirectX
12 Ultimate (12_2)
CUDA
7.5
Power Connectors
None
Shader Model
6.6
ROPs
?
The Raster Operations Pipeline (ROPs) is primarily responsible for handling lighting and reflection calculations in games, as well as managing effects like anti-aliasing (AA), high resolution, smoke, and fire. The more demanding the anti-aliasing and lighting effects in a game, the higher the performance requirements for the ROPs; otherwise, it may result in a sharp drop in frame rate.
64
Benchmarks
FP32 (float)
Score
8.147
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS