Best Single Board Computers of 2020

Looking back at 2019, many revolutionary single-board computers (SBCs) have been released. For example, some of them are the Raspberry Pi 4 which boasts ground-breaking processing and performance speed and a huge increase in memory and connectivity compared to the previous Raspberry Pi 3 Model B+ and the Coral Dev Board which can run onboard machine learning!

As 2020 approaches, we have compiled all the best SBC currently as of 2020 and have categorized them based on their individual strengths like cost, community, performance, simplicity, power consumption and many more!

We will be keeping a close lookout for new single-board computers that are getting released throughout this year and continuously update this list! So do not worry as this guide will be forever up to date!

Without further ado, let us jump right into the first Best Single Board Computer of 2020!

Cheapest: Raspberry Pi Zero / Zero W

Want to get an SBC and not break your bank for it? Or having space constraints with your projects? If that is the case, the Raspberry Pi Zero / Zero W will definitely suit your needs!

  • Costing less than your average movie ticket at $5 and $10 respectively for the Raspberry Pi Zero or Zero W, it is one of the cheapest SBC out there while offering decent performance.
  • In addition, standing at only 65mm x 30mm x 5mm, the Pi Zero / Zero W size small size makes it very convenient for makers to include into their projects. They have found their way inside security cameras, robots and even laptops!
  • Do you need Wi-Fi connectivity or bluetooth? Get the Raspberry Pi Zero W which includes 802.11 b/g/n wireless LAN, Bluetooth(R) 4.1 and Bluetooth Low Energy (BLE) for your Wi-Fi and Bluetooth connection needs!
  • With its price, you will definitely not find the best performance and power compared to other SBCs out there! It also lacks all the USB ports and audio jack found on the Raspberry Pi 4.
  • Want extra connectivity? You can easily solder on a 2*20 Pin Male & Female header which enable it to be able to plug in Pi HATs, GPIO cables, etc like a normal Raspberry Pi


SpecsRaspberry Pi Zero / Zero W
CPU1GHz, Single Core CPU
Price $5 and $10

Best Flexibility:
NVIDIA® Jetson Nano™ Developer Kit

Looking to do AI and machine learning but at the same time want to use your SBC as a desktop? The Jetson Nano from NVIDIA can do just that!

  • The NVIDIA® Jetson Nano™ Developer Kit delivers computing performance to run modern AI workloads at unprecedented size, power, and cost. Developers, learners, and makers can now run AI frameworks and models for applications like image classification, object detection, segmentation, and speech processing.
  • Despite having an older and weaker core than some of the SBCs currently, the Jetson Nano has a much more capable GPU and performant designed specifically for AI applications.
  • If you are looking for an SBC for AI and machine learning purposes while also using it as a general-purpose computer, the Jetson Nano would be your pick!
  • On the other hand, there is a price to pay for the powerful Maxwell GPU for the Jetson Nano.

But, you are in luck! Get a Jetson Nano now as we have just lowered the price of the NVIDIA Jetson Nano to only $89! (U.P $99)

Get the NVIDIA Jetson Nano to get started on your Machine Learning and AI journey now!

Interested in more NVIDIA products? You can check out all of our NVIDIA products here!


SpecsNVIDIA® Jetson Nano™ Developer Kit
CPUQuad-core ARM® A57 CPU
GPU128-core NVIDIA Maxwell™ GPU
RAM4 GB 64-bit LPDDR4

Most Power: ODYSSEY – X86J4105800

If you want a powerful board that is able to run a full version of Windows 10, the Odyssey-X86J4105800 is definitely the board for you.

  • ODYSSEY is a series of SBC (Single Board Computer), allowing you to build Edge Computing applications with ease. The ODYSSEY – X86J4105,  based on Intel Celeron J4105, is a Quad-Core 1.5GHz CPU that bursts up to 2.5GHz.
  • It includes all the powerful features of Mini PC such as including an 8GB LPDDR4 RAM, 64GB eMMC Storage(optional), onboard Wi-Fi/BLE, Dual Gigabyte Ethernet Ports, Audio Input and Output, USB Ports, HDMI, SATA Connectors and PCIe, however, within a cost-effective price.
  • With simple connections to Mouse, Keyboard, and Monitor to ODYSSEY – X86J4105, you will get a Desktop Mini PC right away. With eMMC versions, you even have the Windows 10 Enterprise pre-installed!
  • The ODYSSEY – X86J4105 is more than just a computer, with the Arduino Co-processor onboard, it can be used to connect with sensors, gyroscope, and much more.
  • What can you do with the Odyssey-X86J4105? Well, possibilities are endless with this powerful SBC. Some applications are:
    • Mini PC
    • NAS (Network-Attached Storage)
    • Edge Computing
    • Router
    • Robotics
    • Industrial Applications
    • Media Center
    • IT Industry
    • Educational Fields
    • Thin Client
    • Server Cluster
    • IoT Gateway


SpecsODYSSEY – X86J4105
CPUIntel® Celeron® J4105 (Frequency: 1.5 – 2.5GHz)
Coprocessor Microchip® ATSAMD21G18 32-Bit ARM® Cortex® M0+
GPUIntel® UHD Graphics 600 (Frequency: 250 – 750MHz)
Price$188 – No operating System, no eMMC and no built-in fan.

$218 – Windows 10 Enterprise (Unactivated) with 64GB eMMC and built-in fan.

$258 – Windows 10 Enterprise Activated with 64 eMMC and built-in fan.

Best for Beginners: Raspberry Pi 4

Are you a beginner looking to start learning electronics with an SBC? With one of the biggest communities and support for debugging, the Raspberry Pi 4 is highly recommended for beginners and has become a must-buy for all makers and tech enthusiasts.

  • The Raspberry Pi 4 is commonly used by many makers and there are many detailed tutorials and projects using the Raspberry Pi 4 which are also well documented online.
  • With the new Raspberry Pi 4, it features impressive speeds and performance power compared to previous models while staying affordable and the same price as the previous Raspberry Pi Model 3B+ at $35.
  • At its price, it features a Broadcom BCM2711, quad-core Cortex-A72 (ARM v8) 64-bit SoC @ 1.5GHz which has a Videocore VI Graphics Processing Unit (GPU) handling all graphical input/output. With it, it can cope with 4K resolution and H.265 video, as well as video scaling, camera input, and all HDMI and composite video outputs. The 2711 also has ‘proper’ USB3.0 and Gigabit Ethernet interfaces!
  • Feel that your Raspberry Pi 4 is still slow for you? It is also compatible with the Coral USB Accelerator at a price of $74.99 to further improve its machine learning capabilities and performance!
  • Even though it is not the most powerful, most compact or cheapest, it is definitely still recommended due to its community and support which are very suitable for beginners just starting out on SBCs!
  • If you are interested in what the Raspberry Pi 4 can do, you can check out our other guides on:


SpecsRaspberry Pi 4
CPUBroadcom BCM2711, Quad coreCortex-A72 (ARM v8) 64-bit SoC 1.5GHz
GPUBroadcom VideoCore VI
Price$35 – 1 GB RAM

$45 – 2 GB RAM

$55 – 4 GB RAM

Do you need a more powerful or cheap Raspberry Pi 4? No worries as we have got you covered with some Raspberry Pi 4 alternatives that you can consider!

Alternative to Raspberry Pi 4: Rock Pi 4 Model B

  • Compared to the Raspberry Pi 4, the Rock Pi 4 offers a better performing CPU and GPU which makes it better suited for machine learning.
  • The measurements, layout, and design are exactly the same as the Raspberry Pi 4 making it a formidable alternative to consider.
  • It is able to run Android OS officially and supports mainstream AI stack with GPU acceleration which is good for computer vision application, robotics, etc.
  • In addition, with Rock Pi 4 multiple storage options, it features a better read and write performance on external storage drives, which allows for a quicker read and write speeds that results in improved workflows and file usage efficiency.
  • However, community and support are not as robust compared the Raspberry Pi as the community is smaller. Debugging may be a problem for beginners and novice users as documentation may not be as good.
  • It also comes with a slightly more expensive price tag at $49 to $75 compared to the Raspberry Pi 4 at $35 to $55 depending on the RAM storage.


SpecsRock Pi 4 Model B
CPUDual Cortex-A72, frequency 1.8Ghz with quad Cortex-A53, frequency 1.4Ghz
GPUMali T860MP4 GPU, supports OpenGL ES 1.1 /2.0 /3.0 /3.1 /3.2, Vulkan 1.0, Open CL 1.1 1.2, DX11.
RAM64bit dual channel LPDDR4@3200Mb/s, 4GB, 2GB or 1GB depending on model
Price4GB – $75

2GB – $59

1GB – $49

Alternative to Raspberry Pi 4: Banana Pi M64

  • The Banana Pi M64 comes with 8 GB of eMMC which is the main feature that differentiates it from the Raspberry Pi 4.
  • It also features a 4K HDMI interface, MIPI-DSI, and MIPI-CSI, as well as onboard wireless and Gigabit Ethernet for your connectivity needs.
  • Despite being a Raspberry Pi 4 alternative, the community and users are not as robust compared to the Raspberry Pi 4 with a bustling community.
  • With minimal tutorials and projects for you to choose and learn from, beginners may face difficulties as debugging may be a problem due to the documentation being not as good compared to the Pi 4.
  • The Banana Pi M64 also comes at a slightly higher price at $60.


SpecsBanana Pi M64
CPUAllwinner 64 Bit Quad Core ARM Cortex A53 1.2 GHz
GPUDual-core Mali 400 MP2

Alternative to Raspberry Pi 4: Orange Pi 3

  • The Orange Pi 3 features packs a quad-core 1.8GHz CPU, 2GB DDR3 RAM, four USB 3.0 ports, support for 4K displays via HDMI 2.0a, Gigabit Ethernet, onboard mPCIe 2.0, and Bluetooth 5.0.
  • It has been stated that the board officially supports Android 7.0, Ubuntu and Debian images.
  • You can use the Orange Pi 3 similarly to the Raspberry Pi 4 like building a computer, retro game console, media center, etc.
  • However, compared to the Raspberry Pi 4, it may have poor driver support and missing software with unstable versions of older operating systems. Similar to the previous alternatives, if you are a beginner, it is not recommended to get the alternatives but get a Raspberry Pi 4 instead as you will have to debug and solve issues on your own with a small and growing community of the alternatives.
  • The Orange Pi 3 also lacks the expandability of the Raspberry Pi, as it only has a 26-pin header for hooking up the SBC to other electronics.
  • If you prefer to run Android OS on an SBC, you can consider getting the Orange Pi 3.


SpecsOrange Pi 3
CPU H6 Quad-core 64-bit 1.8GHZ ARM Cortex-A53
GPUOpenGL ES3.1/3.0/2.0/1.1
Microsoft DirectX 11 FL9_3
ASTC(Adaptive Scalable Texture Compression)
Floating point operation greater than 70 GFLOPS
RAM1GB LPDDR3 (shared with GPU)+EMMC(Default Empty)
2GB LPDDR3(shared with GPU)+EMMC(Default Empty)
1GB LPDDR3 (shared with GPU)+8GB EMMC Flash
2GB LPDDR3(shared with GPU)+8GB EMMC Flash

With many alternatives for the Raspberry Pi 4, do note that if you prefer stability, support and projects that are well documented for you to pick from, the Raspberry Pi 4 is recommended!

However, if you prefer more power or other functions, you can consider the alternatives.

Best for Machine Learning with TensorFlow: Coral Dev Board

Looking to run machine learning with an SBC with TensorFlow? The Google Coral Dev Board will definitely do the trick!

For those who do not know what TensorFlow is, it is an end-to-end open-source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.

  • The reason why we say this SBC is the best for machine learning with TensorFlow is because it was designed just for use with the TensorFlow Lite neural network for microcontrollers!
    • However, this may be bad news for users who want to use other deep learning frameworks like Pytorch, Caffe / Caffe2, etc.
  • The Coral Dev Board features an Edge TPU module engineered to deliver high-performance machine learning interpretation which allows users to quickly prototype on-device Machine Learning products.
  • With one of the newest CPU, the NXP i.MX 8M SOC (Quad-core Cortex-A53, plus Cortex-M4F), combined with the Edge TPU, it offers incredible performance and power while being power efficient.
  • However, the Coral Dev Board comes with a heavy price tag costing $149.99. It also lacks a desktop operating system if you are looking for an SBC that can run as a desktop. Nonetheless, if you wish to do machine learning on an SBC with Tensorflow, the Coral Dev board will definitely get the job done.


SpecsCoral Dev Board
CPUNXP i.MX 8M SOC (quad Cortex-A53, Cortex-M4F)
GPUIntegrated GC7000 Lite Graphics
ML Accelerator Google Edge TPU coprocessor

Best for Machine Learning: Rock Pi N10

Next up, we have what we feel is the best SBC for machine learning overall. Why so? Well, is because of its onboard NPU which can support 8/16 bit computing and up to 3.0 TOPS computing power! Furthermore, it only costs $99!

  • Next up, we have what we feel is the best SBC for machine learning overall.
  • Why so? Well, is because of its onboard NPU which can support 8/16 bit computing and up to 3.0 TOPS computing power! Furthermore, it only costs $99!
  • The Rock Pi N10. It is a new member of the Rock pi family that is born for AI and deep learning processing.
  • It carries a powerful SoC(system on chip) which is RK3399Pro which features a CPU, GPU, and NPU.
  • Rock Pi N10 also has plenty of resources for storage. 64 bits dual-channel 4GB LPDDR and 16GB eMMC 5.1 is embedded on the mainboard for providing enough storage for processing and saving data.
  • The Rock Pi N10 is totally an interface monster. Like Raspberry 4B, Rock Pi N10 has rich interfaces for Audio, camera, display, Ethernet, USB and I/O pins. The Ethernet interface can support PoE function and has a PoE hat near the Ethernet interface.
  • Other boards that feature the RK3399Pro Rockchip with the NPU like the Toybrick RK3399Pro AI Developer Kit costs above $200, but with the Rock Pi N10, it is more affordable starting at only $99.
  • Curious how this SBC fare against other Machine learning SBC? Check out our other blog where we put the Rock Pi N10 up against the Jetson Nano and Raspberry Pi 4.


SpecsRock Pi N10
CPUDual Cortex-A72, frequency 1.8GHz with quad Cortex-A53, frequency 1.4GHz
GPUMali T860MP4 GPU, OpenGL ES 1.1 /2.0 /3.0 /3.1 /3.2, Vulkan 1.0, Open CL 1.1 1.2, DX1
NPUSupport 8bit/16bit computing, up to 3.0TOPs computing power
Price$99 – 4GB LPDDR3 & 16GB eMMC
$129 – 6GB LPDDR3 & 32GB eMMC
$169 – 8GB LPDDR3 & 64GB eMMC

Best for Smart Voice and Sound Applications: Respeaker Core v2.0

Looking for a board to make a smart speaker, intelligent voice assistant system, voice recorder, car voice assistant, or basically any smart voice and sound applications? This SBC right here, is perfect for all these applications.

  • The ReSpeaker Core v2.0 allows developers create powerful and impactful voice and sound interfaces. Suitable to use as a base for smart assistance as well as responding to environmental sounds, the ReSpeaker Core v2.0 was designed with the idea that developers deserve to have many options available to them.
  • This SBC is able to run and support Debian and Android with an onboard microphone array and software-based voice enhancement algorithms.
  • Around the core are peripherals including a Kingston 4GB eMMC to enable the OS to run onboard, a WiFi/BLE module, USB, Grove, and HDMI connectors, the on board 6-mic array, LED ring, and more.
  • Furthermore, the Respeaker Core v2.0 is able to process audio received through the 6 far-field microphones in real-time with the powerful Axol Core.
  • You can get all these goodness inside this SBC at only $99.


SpecsRespeaker Core v2.0
CPUQuad-Core Cortex-A7,up to 1.5GHz
GPUMali400MP, Support OpenGL ES1.1/2.0
RAM1GB RAM(Core Module includes RAM and PMU)

Running Android: Hikey 970 Development Board

Do you wish to run Android on an SBC together with Machine learning capabilities? With the Hikey 970, the board can run Android (AOSP) or Linux distributions (Ubuntu/Debian), and supports Huawei HiAI SDK that delivers up to 25 times performance, and/or 50 times the power efficiency for A.I. applications.

  • The latest HiAI SDK V150 supports Caffe, TensorFlow, TensorFlow Lite, and Android NN frameworks, and various tools.
  • Making use of with LPDDR4X 1866MHz memory, and featuring 64GB of UFS 2.1 storage, Bluetooth, WIFI, and GPS, this is a board specifically aimed at developers, especially those looking in maximizing accelerated AI capabilities that are not present of most other development platforms.
  • This makes the Hikey 970 to be used in most applications like Deep Learning, Robots, Automobile, and Smart City.
  • However, at a price of $299, it is one of the most expensive SBCs out there in the market but it will definitely be worth it with its performance.


SpecsHikey 970 Development Board
CPU4 x Cortex A73 @ 2.36GHz, 4 x Cortex A53 @ 1.8GHz
GPUMali G72-MP12

Compact: PocketBeagle

Looking for a compact and tiny board? The PocketBeagle should do the job!

  • Standing at 56mm x 35mm x 5mm, the PocketBeagle is the size of a tiny mint-tin almost similar to the Raspberry Pi Zero.
  • This board is unique in a way as it has similarities with the Raspberry Pi but also the Arduino. Being able to run Linux right out of the box and programmed through your web browser, there is no doubt that this is a single-board computer (SBC). However, it has 5 analog inputs with 44 GPIO pins and a microSD slot which makes it flexible and versatile and able to function like an Arduino while having a full onboard operating system!
  • One main feature of the Pocketbeagle is that you can easily program the Pocketbeagle through a web browser running on any other connected desktop like a USB key-fob.
  • This board is suitable for beginners who are looking to learn programming aspects and it is also a low-cost Linux computer with tremendous expansibility.


CPUOctavo Systems OSD335x SiP with TI Sitara AM3358 (1x Cortex-A @ 1GHz)

Arduino Compatible: Seeeduino Cloud

Before you guys go crazy over how this is not SBC but a microcontroller instead, we felt that it was appropriate to include it into the list as it is a microcontroller that is a Linux-ready SBC with full Arduino compatibility.

  • Seeeduino Cloud is a microcontroller board based on Dragino WiFi IoT module HE and ATmega32u4. HE is a high performance, low cost 150M, 2.4G WiFi module which means “core” in Chinese and with an Open Source OpenWrt system inside.
  • Seeeduino Cloud is also 100% compatible with Grove, shield and IDEs(Arduino IDE 1.5.3 and later).
  • Except for the normal interface of Arduino, Seeeduino Cloud has built-in Ethernet and WiFi support, a USB-A port which makes it very suitable for those prototype design that needs network connection and mass storage. It is also a good idea to make Seeeduino Cloud to an IoT gateway.
  • Historically, interfacing Arduino with complex web services has been quite a challenge due to the limited memory available. Web services tend to use verbose text-based formats like XML that require quite a lot of ram to parse. On the Cloud, you can use the Yun Bridge library which delegates all network connections and processing of HTTP transactions to the Linux machine.


SpecsSeeeduino Cloud

Honorable Mention: Seeeduino Mega

Why did we include this microcontroller? Well, even though it is based around microcontrollers instead of a microprocessor, it has shared characteristics as the Raspberry Pi 4 in budget hardware and STEM education.

  • While both boards can control electronics attached to their pins, the Pi is also capable of being used as a full desktop computer but the Arduino is easier to use when building electronic prototypes, and also to swap out for a new microcontroller in the final product. So do pick which microcontroller or SBC that suits your project the most!
  • The Seeeduino Mega is a powerful micro-controller derived from Arduino Mega. It features ATmega2560 processor which brings a large number of I/O pins, as much as 70 digital I/O, 16 analog inputs, 14 PWM, and 4 hardware serial ports.
  • Compared to Arduino Mega, we shrunk the volume of Arduino Mega by at least 30% and made it 100% compatible with Seeed Shield products. And as a member of Seeeduino series, Seeeduino Mega inherits deliberate details from Seeeduino, like selectable operating voltage(3.3V/5V), right angle reset button, and so on.
  • If you are looking to create robotic projects or you want something for a 3D printer, the Seeeduino Mega will be a handy replacement to Raspberry Pi even though it is based on a microcontroller and not a microprocessor.


SpecsSeeeduino Mega
CPUATmega 2560 @ 16MHz

Honorable Mention: Micro:bit

Another microcontroller? And besides this, when you compare its specs and other single board computers on this list, the micro:bit is nowhere near as powerful or as versatile.

Before you start bashing me, due to the micro:bit low cost and how user-friendly it is for beginners, we decided to include it into the list. If you are looking to enter into the world of electronics and programming, getting a powerful single board computer might not be the best choice as you wouldn’t be able to fully make use of it.

Why not get a micro:bit which is a pocket-sized microcontroller designed for kids and beginners learning how to program which can be used for all sorts of cool creations, from robots to musical instruments and many more for only $15! Not to mention, it can be powered with just 2 x AAA batteries.

  • The BBC micro:bit has an awful lot of features for you to create various projects, prominently:
    • 25 red LED lights flashing messages
    • Two programmable buttons used to control games/pause and skip songs on a playlist
    • Low energy Bluetooth connection that interacts with other devices and the Internet
    • Embedded compass, accelerometer, mobile, and well-based programming capabilities
  • Programming the board is very easy and beginner-friendly where you do not need to have years of experience. All you need is just a few minutes learning the basics and you are good to go!
  • If you feel like this is only a child’s toy, be rest assured it isn’t as with this board, you can also learn how to program with python as well just like any other single-board computer. In addition, it can be paired with the Raspberry Pi 4 as well!
  • If you wish to expand the micro:bit capabilities, here at Seeed, we offer various kits, shields, cases, and extensions for you like BitmakerBitwearBitPlayer,BitCarBitWearable KitKittenbot and many more!
  • Interested in what the micro:bit can do? You can check out our list on Top 25 Micro:Bit Projects You Must Try 2019!


CPUNordic nRF51822 – 16 MHz 32-bit ARM Cortex-M0
RAM256 KB flash memory, 16 KB static ram


That’s it for the best Single Board Computers of 2019! With so many SBCs being released each year, it is hard to keep track of all of them. Single Board Computers each have their own various functions like machine learning and education each with different prices as well! So do pick out wisely in which SBC suits your projects the most to make the most out of it.

Still struggling in making a decision? To make it easier for you guys, we have compiled them into a table for you to easily compare their differences and pick your favourite:

SBCCPUGPURAMOther featuresPrice
Raspberry Pi Zero / Zero W 1GHz, Single Core CPU 512MB RAM $5 and $10
NVIDIA® Jetson Nano™ Developer Kit Quad-core ARM® A57 CPU 128-core NVIDIA Maxwell™ GPU 4 GB 64-bit LPDDR4 $89
Raspberry Pi 4 Broadcom BCM2711, Quad coreCortex-A72 (ARM v8) 64-bit SoC 1.5GHz Broadcom VideoCore VI 1 GB, 2 GB, or 4 GB LPDDR4 SDRAM $35 – 1 GB RAM

$45 – 2 GB RAM

$55 – 4 GB RAM
Rock Pi 4 Model B Dual Cortex-A72, frequency 1.8Ghz with quad Cortex-A53, frequency 1.4Ghz Mali T860MP4 GPU, supports OpenGL ES 1.1 /2.0 /3.0 /3.1 /3.2, Vulkan 1.0, Open CL 1.1 1.2, DX11. 64bit dual channel LPDDR4@3200Mb/s, 4GB, 2GB or 1GB depending on model 4GB – $75

2GB – $59

1GB – $49
Banana Pi M64 Allwinner 64 Bit Quad Core ARM Cortex A53 1.2 GHz Dual-core Mali 400 MP2 2GB DDR$60
Orange Pi 3 H6 Quad-core 64-bit 1.8GHZ ARM Cortex-A53 OpenGL ES3.1/3.0/2.0/1.1
Microsoft DirectX 11 FL9_3
ASTC(Adaptive Scalable Texture Compression)
Floating point operation greater than 70 GFLOPS
1GB LPDDR3 (shared with GPU)+EMMC(Default Empty)
2GB LPDDR3(shared with GPU)+EMMC(Default Empty)
1GB LPDDR3 (shared with GPU)+8GB EMMC Flash
2GB LPDDR3(shared with GPU)+8GB EMMC Flash
Coral Dev Board NXP i.MX 8M SOC (quad Cortex-A53, Cortex-M4F) Integrated GC7000 Lite Graphics 1 GB LPDDR4 ML Accelerator – Google Edge TPU coprocessor $149.99
Rock Pi N10 Dual Cortex-A72, frequency 1.8GHz with quad Cortex-A53, frequency 1.4GHzMali T860MP4 GPU, OpenGL ES 1.1 /2.0 /3.0 /3.1 /3.2, Vulkan 1.0, Open CL 1.1 1.2, DX1 4/6/8 GB LPDDR3 NPU -Support 8bit/16bit computing, up to 3.0TOPs computing power
$99 – 4GB LPDDR3 & 16GB eMMC
$129 – 6GB LPDDR3 & 32GB eMMC
$169 – 8GB LPDDR3 & 64GB eMMC
Respeaker Core v2.0 Quad-Core Cortex-A7,up to 1.5GHzMali400MP, Support OpenGL ES1.1/2.01GB RAM(Core Module includes RAM and PMU)$99
Hikey 970 Development Board 4 x Cortex A73 @ 2.36GHz, 4 x Cortex A53 @ 1.8GHz Mali G72-MP12 6GB LPDDR4 $299
PocketBeagle Octavo Systems OSD335x SiP with TI Sitara AM3358 (1x Cortex-A @ 1GHz) PowerVR SGX530 512MB RAM$25
Seeeduino Cloud ATHEROS AR9331 64MB RAM$49.95
Seeeduino Mega ATmega 2560 @ 16MHz 8KB$43
Micro:bit Nordic nRF51822 – 16 MHz 32-bit ARM Cortex-M0 256 KB flash memory, 16 KB static ram $14.90

What are your thoughts on all these Single Board Computers? Do you have in mind any Single Board Computers that deserve to be on this list? We would love to hear from you guys so do let us know in the comments down below!

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