NVIDIA RTX 4000 Mobile Ada Generation
The NVIDIA RTX 4000 Mobile Ada Generation GPU is an impressive addition to the RTX lineup, offering high-end performance and advanced features for mobile users. With a base clock of 1290MHz and a boost clock of 1665MHz, this GPU delivers exceptional speed and responsiveness for demanding tasks such as gaming, 3D rendering, and video editing.
One of the standout features of the RTX 4000 Mobile is its generous 12GB of GDDR6 memory, which provides ample storage for high-resolution textures and complex scenes. The memory clock of 2250MHz ensures fast access to this memory, further enhancing overall performance. With 7424 shading units and a substantial 48MB of L2 cache, this GPU excels at handling complex calculations and graphical workloads.
Despite its impressive performance, the RTX 4000 Mobile maintains a reasonable power profile, with a TDP of 110W. This makes it suitable for use in a wide range of laptops and mobile workstations without sacrificing battery life or generating excessive heat.
Overall, the theoretical performance of 24.72 TFLOPS makes the RTX 4000 Mobile Ada Generation GPU a compelling choice for users who require high-end graphics capabilities on the go. Whether for gaming, content creation, or professional design work, this GPU delivers the power and efficiency needed to handle demanding tasks with ease.
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Basic
Label Name
NVIDIA
Platform
Mobile
Launch Date
March 2023
Model Name
RTX 4000 Mobile Ada Generation
Generation
Quadro Ada-M
Base Clock
1290MHz
Boost Clock
1665MHz
Bus Interface
PCIe 4.0 x16
Transistors
35,800 million
RT Cores
58
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.
232
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.
232
Foundry
TSMC
Process Size
5 nm
Architecture
Ada Lovelace
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.
192bit
Memory Clock
2250MHz
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.
432.0 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.
133.2 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.
386.3 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.
24.72 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.
386.3 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.
25.214
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.
58
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.
7424
L1 Cache
128 KB (per SM)
L2 Cache
48MB
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
8.9
Power Connectors
None
Shader Model
6.7
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.
80
Benchmarks
FP32 (float)
Score
25.214
TFLOPS
Blender
Score
5163
Compared to Other GPU
FP32 (float)
/ TFLOPS
Blender