NVIDIA Jetson Orin NX 16 GB
The NVIDIA Jetson Orin NX 16 GB GPU is a professional-grade graphics processing unit that delivers exceptional performance and efficiency for a variety of applications. With a memory size of 16GB and the latest LPDDR5 memory type, this GPU offers significant improvements in data transfer speeds and power efficiency compared to previous generations.
The 1600MHz memory clock and 1024 shading units provide the processing power needed for demanding tasks such as AI inferencing, autonomous machines, and high-performance computing. The 256KB L2 cache helps to further enhance the GPU's performance by reducing memory latency and improving overall efficiency.
Despite its impressive performance capabilities, the Jetson Orin NX 16 GB GPU has a relatively low TDP of 25W, making it suitable for power-constrained environments such as edge devices and embedded systems. This combination of high performance and low power consumption makes it an ideal choice for a wide range of applications, from robotics and autonomous vehicles to medical imaging and industrial automation.
With a theoretical performance of 1.88 TFLOPS, the Jetson Orin NX 16 GB GPU is capable of handling complex computational tasks with ease, making it a versatile solution for developers and engineers working on AI and deep learning projects.
Overall, the NVIDIA Jetson Orin NX 16 GB GPU offers a compelling blend of performance, efficiency, and advanced features, making it a valuable addition to any professional workstation or edge computing device.
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Basic
Label Name
NVIDIA
Platform
Professional
Launch Date
February 2023
Model Name
Jetson Orin NX 16 GB
Generation
Tegra
Bus Interface
PCIe 4.0 x4
Transistors
Unknown
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.
32
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.
32
Foundry
Samsung
Process Size
8 nm
Architecture
Ampere
Memory Specifications
Memory Size
16GB
Memory Type
LPDDR5
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.
128bit
Memory Clock
1600MHz
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.
102.4 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.
14.69 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.
29.38 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.
3.760 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.
940.0 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.
1.918
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.
8
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.
1024
L1 Cache
128 KB (per SM)
L2 Cache
256KB
TDP
25W
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
8.6
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.
16
Benchmarks
FP32 (float)
Score
1.918
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS