If you are planning to use a Single Board Computer (SBC) for an upcoming project, you might be looking for the variety of SBC models available in the market. The most popular options that you may have heard of are the Raspberry Pi and Nvidia Jetson. Both of these boards are considered more popular than other brands. However, do you know the differences between them and how to pick the correct board for your next project? Today, we are going to do a deep comparison of them in various aspects.
When comparing the Raspberry Pi 4B and Jetson Nano B01, the first thing that cannot be ignored is the price. Therefore, in this article, we will explore the reasons why the Nvidia Jetson sells for a higher price than the Raspberry Pi. Let's take a closer look together
The Nvidia Jetson Nano B01 board (left) and the Raspberry Pi 4 Model B board (right).
The first thing we need to know is that the Nvidia Jetson board is designed with an emphasis on processing power, especially for AI performance. The Jetson board is divided into two parts: the SOM (System On Module) and the carrier board. The SOM is the processing unit, which can be removed separately. It includes the CPU, GPU, RAM, and storage units. The most important component of the SOM is the GPU. For the lowest spec model, the Nvidia Jetson Nano, the GPU comes with 128 NVIDIA CUDA cores. For higher-end models, such as the Nvidia Jetson Xavier NX, it comes with 384 NVIDIA CUDA cores and 48 Tensor cores. These cores are key components that give the Jetson board much more processing power than the Raspberry Pi.
The carrier board is the expansion board that comes with GPIO, USB ports, RJ45 ports (for LAN), display ports (HDMI, Display Port), and in some models, PCIe ports for using M.2 SSDs or wireless adapters
The carrier board (left) and System on Module (right)
Although the Jetson Nano uses a lower CPU (Quad-core Cortex A57) than the Raspberry Pi 4B (Quad-core Cortex A72), its processing power is still much better than that of the Raspberry Pi 4B, mainly due to its GPU. Just like everyone knows, Nvidia is well-known for its GPU technology.
In terms of interface ports, both boards have similar ports, such as USB, RJ45 (LAN), HDMI, and Display Port (only on Nvidia Jetson). The number of ports may vary depending on the carrier boards, but the main difference lies in the number of CSI ports for camera connections. Currently, all Nvidia Jetson models provide two CSI ports, whereas the Raspberry Pi 4 Model B only has one. Additionally, the A/V out port is only available on the Raspberry Pi board, which can be used to connect headphones or speakers.
Interface ports available on the Nvidia Jetson Nano board (left) and Raspberry Pi 4 Model B (right).
Jetson Nano 40-pin GPIO (left) and Raspberry Pi 4 Model B (right).
The size of the Jetson Nano board (bottom) compared to the Raspberry Pi 4 Model B (top).
The Nvidia Jetson boards offer better AI performance than the Raspberry Pi in the areas of machine learning and computer vision, thanks to the processing power of the GPU and the software developed to support the hardware. For example, Nvidia Jetson boards allow users to use popular deep learning frameworks, such as TensorFlow, PyTorch, and Caffe, or use specialized tools provided by Nvidia, such as TensorRT, cuDNN, CUDA, and Nvidia Deepstream SDK. While the Raspberry Pi can also use these frameworks (except for Nvidia-specific tools), its processing performance is limited due to the lower-performance GPU.
Machine Learning and AI tools available for Nvidia Jetson platform
Tools for Machine Learning and AI that can be used on both Raspberry Pi and Nvidia Jetson platforms.
The Nvidia Jetson boards are designed for high-performance computing programs or applications, including robotics, drones, self-driving vehicles, and AI tasks. They are particularly suitable for real-time processing and low latency applications, such as object detection, gesture recognition, and natural language processing. On the other hand, the Raspberry Pi is designed for general-purpose use, including portable computers, media or sensor centers, IoT, and educational projects. It is a versatile tool and platform that can be used for various purposes, from creating a smart home system to teaching children how to program.
To detect multiple human faces and scan their body temperature, AI or machine learning is required to recognize the facial features of humans. This can be achieved using the Nvidia Jetson board.
A smarthome system that uses Raspberry Pi 4 Model B board.
Nvidia Jetson boards are generally more expensive than Raspberry Pi, with prices starting at around USD 200 and going beyond USD 2500 for the highest-end models. On the other hand, Raspberry Pi boards are generally much cheaper, with prices starting from USD 15 for the Raspberry Pi Zero series and going up to below USD 100 for the Raspberry Pi 4 Model B 8GB RAM. This makes Raspberry Pi a suitable and affordable option for makers and students who want to build IoT projects or for learning purposes.
It's important to note that while Nvidia Jetson boards may be more expensive, they offer significantly more processing power and are designed for high-performance computing tasks such as robotics, AI, and computer vision. Raspberry Pi, on the other hand, is a more affordable option that is suitable for general-purpose use and educational projects. Ultimately, the choice between the two will depend on the specific needs and requirements of the project or application.