Choosing the best single-board computer (SBC) depends on your specific project needs, whether it’s for general use, AI development, or industrial applications. The LattePanda 3 Delta stands out as the best overall with its x86 architecture, making it versatile for Windows-based tasks. The Raspberry Pi 5 8GB offers exceptional performance for a low price, while the NVIDIA Jetson Orin Nano excels in AI and machine learning workloads. As you compare options, consider tradeoffs like processing power, connectivity, size, and price. Keep reading for a detailed breakdown of these top choices and what makes each unique.
Key Takeaways
- The top picks balance performance, versatility, and price, with the LattePanda 3 Delta leading for general use.
- AI-focused options like the NVIDIA Jetson Orin Nano require a higher budget but deliver specialized capabilities.
- Raspberry Pi models dominate for low-cost, community-supported projects, especially with the Pi 5’s latest hardware.
- Connectivity features like Gigabit Ethernet and M.2 support are key for industrial or server applications.
- Size and power consumption vary widely; compact boards like Orange Pi 4 Pro suit embedded projects, while larger boards offer more expandability.
| LattePanda 3 Delta x86 Single Board Computer with Intel N5105, 8GB RAM, 64GB eMMC, and Arduino Coprocessor |  | Best Overall x86 SBC for Versatile Development | RAM: 8 GB DDR4 | Storage: 64 GB eMMC | CPU Model: Intel Celeron N5105 (2.9 GHz) | VIEW LATEST PRICE | See Our Full Breakdown |
| NVIDIA Jetson Orin Nano Super Developer Kit |  | Best AI Edge Computing Platform for AI Developers | AI Performance: up to 67 TOPS | Memory: 8GB | CPU: 6-core ARM | VIEW LATEST PRICE | See Our Full Breakdown |
| Raspberry Pi 3 Model B+ |  | Best Budget Choice for Basic Projects | RAM: 1GB LPDDR3 | Processor: 1.4GHz 64-bit quad-core Cortex | Connectivity: Dual-band Wi-Fi, Ethernet | VIEW LATEST PRICE | See Our Full Breakdown |
| Radxa Rock 2A Single Board Computer, RK3528A Quad-Core CPU, GPU, 4K HDMI and Gigabit Ethernet (RS113-D4T0) |  | Best Multimedia & Basic Computing for Embedded Projects | CPU Model: RK3528A | Processor Count: 4 | Memory: 4 GB | VIEW LATEST PRICE | See Our Full Breakdown |
| Cubie A5E, 8-core CPU, Dual Gigabit Ethernet Ports, Supporting M.2 2230 NVMe SSD, Single Board Computer |  | Best Industrial-Grade SBC with NPU and Dual Ethernet | CPU: Allwinner A527/T527 | Core Count: 8 | NPU: 2 TOPs | VIEW LATEST PRICE | See Our Full Breakdown |
| Raspberry Pi 5 8GB |  | Best Overall for Versatility and Future-Proofing | RAM Memory Installed: 8 GB | Processor Speed: 2.4 GHz | Storage Capacity: 8 GB | VIEW LATEST PRICE | See Our Full Breakdown |
| Orange Pi 4 Pro 4GB Single Board Computer with AI NPU and Wi-Fi 6 |  | Best for AI and Industrial Applications | SoC: Allwinner A733 | CPU: 2x Cortex-A76 + 6x Cortex-A55 @ 2.0GHz | Memory: 4GB LPDDR5 | VIEW LATEST PRICE | See Our Full Breakdown |
| Raspberry Pi 4 Model B 8GB Single Board Computer |  | Best for Cost-Effective Performance and Media Projects | RAM: 8 GB | Processor Speed: 1.5 GHz | USB Ports: 2 (USB 3.0) | VIEW LATEST PRICE | See Our Full Breakdown |
More Details on Our Top Picks
LattePanda 3 Delta x86 Single Board Computer with Intel N5105, 8GB RAM, 64GB eMMC, and Arduino Coprocessor
The LattePanda 3 Delta stands out for its native support of Windows 10/11 and Linux, making it ideal for developers who need a flexible platform. Its onboard Arduino coprocessor simplifies hardware integration, especially for robotics or automation projects. Compared with the NVIDIA Jetson Orin Nano, it offers broader OS compatibility, but at a higher price and with less dedicated AI performance. This model’s dual M.2 slots support high-speed NVMe storage and 5G modules, catering to edge computing needs. However, the 64GB eMMC might fall short for larger data sets or complex applications, and the cooling system can be noisy under sustained loads. This pick is perfect for those seeking a powerful, adaptable SBC that supports complex software and hardware projects.
Pros:- Supports native Windows 10/11 and Linux for broad software compatibility
- Built-in Arduino coprocessor simplifies hardware prototyping
- Dual M.2 slots enable high-speed storage and 5G expansion
- Fast Wi-Fi 6 and 2.5GbE Ethernet for low-latency networking
Cons:- 64GB eMMC storage may be insufficient for large-scale projects
- Higher price compared to basic SBCs like Raspberry Pi
- Fan cooling can be noisy under heavy workloads
Best for: Engineers and developers requiring a versatile, Windows/Linux-compatible SBC for robotics, edge AI, or industrial automation.
Not ideal for: Budget-conscious hobbyists or users primarily interested in AI/ML development, as it is more expensive and less optimized for AI workloads than NVIDIA options.
- RAM:8 GB DDR4
- Storage:64 GB eMMC
- CPU Model:Intel Celeron N5105 (2.9 GHz)
- Operating System:Windows 10/11 & Linux
- Connectivity:Wi-Fi 6, 2.5GbE Ethernet
- Expansion Slots:Dual M.2
- USB Ports:5
- Display Support:Triple (Dual 4K HDMI/Type-C, 1080P eDP)
- Cooling:Fan-cooled
Bottom line: This SBC is best suited for professionals needing a Windows/Linux powerhouse with hardware flexibility and robust connectivity.
NVIDIA Jetson Orin Nano Super Developer Kit
The NVIDIA Jetson Orin Nano Super Developer Kit offers up to 67 TOPS of AI performance, making it a top choice for AI enthusiasts and robotics developers. Its 8GB module with Ampere GPU and 6-core ARM CPU can handle multiple AI models simultaneously, including transformer-based and vision applications. Compared to the Radxa Rock 2A, it provides vastly superior AI inference capabilities but at a higher cost and with a focus on AI workloads rather than general computing. The wide range of connectors, including MIPI CSI for cameras, supports sophisticated robotics and vision projects. Its ecosystem, including NVIDIA’s software stack, accelerates development, but the device’s power consumption and heat output can be significant for embedded deployments. This kit is ideal for those pushing the frontiers of edge AI and needing high-performance inference on a compact platform.
Pros:- Up to 67 TOPS of AI performance for advanced inference
- Supports all modern AI models including transformers
- Rich connectivity options including high-res camera support
- Ecosystem with NVIDIA AI software and tools for rapid development
Cons:- Relatively high power consumption and heat output
- Higher cost compared to basic SBCs like Raspberry Pi
- Limited general-purpose computing performance outside AI tasks
Best for: AI developers building autonomous robots, smart cameras, or edge AI solutions needing maximum AI throughput.
Not ideal for: Hobbyists or budget-conscious users who require a general-purpose SBC without intensive AI needs.
- AI Performance:up to 67 TOPS
- Memory:8GB
- CPU:6-core ARM
- GPU:Ampere GPU
- Connectivity:Wide array including MIPI CSI
- Ecosystem:NVIDIA AI software stack
Bottom line: This platform is best for AI-focused projects where inference speed and AI model support are critical, not general computing tasks.
Raspberry Pi 3 Model B+
The Raspberry Pi 3 Model B+ is a familiar, affordable SBC that excels for simple projects and educational use. Its 1.4GHz quad-core processor and dual-band Wi-Fi provide decent performance for media streaming, basic IoT, and learning tasks. Compared to the Radxa Rock 2A, it offers less RAM (1GB vs. 4GB) and fewer connectivity options but benefits from a huge community and extensive OS support. Its lack of onboard storage means you need an SD card, and it isn’t designed for intensive compute or AI workloads. The Pi’s low price is a strong advantage, but its limited RAM and processing power restrict its use for demanding applications. This is best for beginners, educational environments, or simple automation projects where cost and ease of use matter most.
Pros:- Affordable and widely supported by a large community
- Dual-band Wi-Fi and Ethernet for flexible networking
- Supports multiple operating systems
- Four USB ports for peripherals
Cons:- Limited to 1GB RAM, restricting multitasking and heavier workloads
- No onboard storage—requires SD card setup
- Not optimized for AI or high-performance computing
Best for: Hobbyists, students, or small-scale projects needing a reliable, low-cost SBC for learning or basic tasks.
Not ideal for: Advanced AI, multimedia editing, or high-performance robotics requiring more RAM and processing power.
- RAM:1GB LPDDR3
- Processor:1.4GHz 64-bit quad-core Cortex
- Connectivity:Dual-band Wi-Fi, Ethernet
- USB Ports:4
- Operating Systems:Multiple
- Smart Home Compatibility:No
Bottom line: Ideal for newcomers and basic projects, but not suited for intensive computing or AI applications.
Radxa Rock 2A Single Board Computer, RK3528A Quad-Core CPU, GPU, 4K HDMI and Gigabit Ethernet (RS113-D4T0)
The Radxa Rock 2A offers a compelling balance of multimedia and connectivity, with a quad-core RK3528A CPU and 4K HDMI output, making it suitable for media centers and embedded applications. Its Gigabit Ethernet with PoE support helps with reliable wired networking, and the FPC connector broadens expansion possibilities. Compared to the Cubie A5E, it provides more multimedia output and a more modern interface, although the Cubie offers NPU capabilities. The Rock 2A’s limited onboard storage and modest processing power make it less ideal for AI or heavy data processing, but it excels in video streaming, digital signage, and simple automation. Its small form factor and broad I/O make it attractive for hobbyists and developers seeking flexibility. This SBC is perfect for multimedia projects needing solid graphics and connectivity, with moderate compute demands.
Pros:- Supports 4K HDMI output for high-quality video
- Gigabit Ethernet with PoE for reliable network and power options
- Broad expansion options via FPC connector
- Compact design suitable for embedded applications
Cons:- Limited onboard storage options
- Less suitable for heavy AI or data processing workloads
- Processing power may be insufficient for demanding tasks
Best for: Media centers, digital signage, and basic embedded systems where video output and network connectivity are priorities.
Not ideal for: AI development or intensive data processing tasks, as its CPU and NPU capabilities are modest.
- CPU Model:RK3528A
- Processor Count:4
- Memory:4 GB
- Connectivity:Gigabit Ethernet, PoE
- Video Output:4K HDMI
- Form Factor:Compact
Bottom line: This SBC is best for multimedia and embedded projects where high-quality video and reliable networking are required, but not for AI or heavy computing.
Cubie A5E, 8-core CPU, Dual Gigabit Ethernet Ports, Supporting M.2 2230 NVMe SSD, Single Board Computer
The Cubie A5E excels in demanding industrial and networked applications, featuring an 8-core Allwinner A527/T527 CPU and 2TOPs of NPU processing power. Its dual Gigabit Ethernet ports support high-speed networking, ideal for industrial automation or network appliances. Compared to the Raspberry Pi 4B 8GB, it offers better NPU capabilities and dual Ethernet, but at a higher complexity and potentially less extensive software support. The support for M.2 2230 NVMe SSD allows for high-speed storage expansion, critical for data-heavy tasks. Its compact design and versatile I/O make it suitable for environments requiring reliable, high-performance processing. Yet, its niche ecosystem and limited community may pose challenges for troubleshooting or software updates. This SBC is best for industrial, network, and edge AI applications where robust connectivity and processing are needed.
Pros:- 8-core CPU with industrial-grade performance
- Supports M.2 2230 NVMe SSD for fast storage
- Dual Gigabit Ethernet ports for robust networking
- 2TOPs NPU for AI acceleration
Cons:- Limited software ecosystem compared to Raspberry Pi
- Higher complexity and cost for hobbyist use
- Less community support for troubleshooting
Best for: Industrial automation, network appliances, or edge AI applications needing high NPU performance and dual Ethernet connectivity.
Not ideal for: General-purpose or hobbyist projects that require a large software community or extensive multimedia support.
- CPU:Allwinner A527/T527
- Core Count:8
- NPU:2 TOPs
- Ethernet Ports:2
- Storage:Supports M.2 2230 NVMe SSD
- Form Factor:Compact
Bottom line: This SBC is ideal for industrial and network applications needing high NPU performance and dual Ethernet, not casual or multimedia projects.
Raspberry Pi 5 8GB
The Raspberry Pi 5 8GB stands out as the most adaptable single-board computer in this lineup, thanks to its substantial 8GB of RAM and a 2.4 GHz quad-core ARM processor that comfortably handles a wide range of projects—from media centers to IoT hubs. Compared with the Raspberry Pi 4 Model B 8GB, it offers improved processing power and future support for higher-resolution displays, making it the best pick for users who want longevity and flexibility. However, the Pi 5’s higher price and slightly more complex setup might be a hurdle for absolute beginners. Its extensive connectivity options, including Bluetooth, HDMI, and USB ports, translate into seamless integration for various peripherals, but the overall power consumption and heat dissipation could be concerns for long-term, intensive use. This model makes the most sense for tech enthusiasts and developers seeking a high-performance, scalable platform.
Pros:- Large 8GB RAM for multitasking and demanding applications
- Fast 2.4 GHz ARM processor enhances performance
- Extensive connectivity including Bluetooth, HDMI, and multiple USB ports
- Supports 4K displays with HDMI input
Cons:- Higher price point compared to earlier Pi models
- Requires more advanced setup and configuration
- Power consumption and heat management can be challenging for continuous heavy workloads
Best for: Tech-savvy hobbyists and developers needing a future-proof, versatile SBC for a broad array of projects
Not ideal for: Complete beginners or users with strict budget constraints who prefer simple, low-cost solutions
- RAM Memory Installed:8 GB
- Processor Speed:2.4 GHz
- Storage Capacity:8 GB
- Connectivity Technology:Bluetooth, HDMI
- Processor Brand:ARM
- Operating System:Raspberry Pi OS
- Total USB Ports:4
Bottom line: This is the best choice for users who need a high-performance, future-ready SBC capable of handling complex projects.
Orange Pi 4 Pro 4GB Single Board Computer with AI NPU and Wi-Fi 6
The Orange Pi 4 Pro 4GB distinguishes itself with a robust octa-core CPU and an integrated AI NPU capable of 3 TOPS, making it ideal for AI inference, robotics, and industrial automation. Compared with the Raspberry Pi 4 Model B 8GB, it offers dedicated AI acceleration and support for multiple OS including Android and OpenHarmony, which broadens its application scope. However, its smaller community and less mature software ecosystem can pose challenges for newcomers, and onboard storage options are limited without additional modules. Its support for Wi-Fi 6 and PoE simplifies deployment in networked environments, but the PCB’s compact size may restrict expansion, especially for those needing extensive I/O or storage options. This pick is best suited for professionals working on AI projects, robotics, or IoT deployments that benefit from powerful onboard AI and industrial-grade connectivity.
Pros:- High-performance octa-core CPU with Cortex-A76 cores
- Integrated AI NPU supporting 3 TOPS for inference tasks
- Support for multiple OS including Android and OpenHarmony
- Wi-Fi 6 and PoE for simplified network deployment
Cons:- Limited onboard storage capacity without additional modules
- Small PCB size may restrict expansion options
- Steep learning curve for open-source and industrial applications
Best for: AI developers, robotics engineers, and industrial automation specialists seeking high-performance compute and connectivity
Not ideal for: Home users or hobbyists without specific AI or industrial needs, due to complexity and limited community support
- SoC:Allwinner A733
- CPU:2x Cortex-A76 + 6x Cortex-A55 @ 2.0GHz
- Memory:4GB LPDDR5
- Storage:eMMC 16GB-128GB, M.2 NVMe, microSD
- Connectivity:Wi-Fi 6, Bluetooth 5.4, Gigabit Ethernet (PoE)
- GPU:Imagination BXM-4-64
- NPU:3 TOPS
Bottom line: This is the ideal SBC for professionals needing powerful AI processing and industrial-grade connectivity in compact form.
Raspberry Pi 4 Model B 8GB Single Board Computer
The Raspberry Pi 4 Model B 8GB offers an excellent balance of performance and affordability, featuring a 1.5 GHz quad-core Cortex-A72 processor and ample 8GB RAM, which makes it suitable for media centers, mini PCs, and lightweight server applications. Compared to the Raspberry Pi 5, it provides slightly lower processing power but benefits from a large, established community and a wide range of compatible accessories. Its dual micro HDMI ports support 4K output at 60Hz, making it a strong choice for multimedia projects. Nevertheless, it requires an external Wi-Fi adapter, and its power demands are higher than some similar SBCs, which could impact portable or low-power setups. Its limited onboard storage and lack of USB 3.0 ports at the time of release mean it may need extra peripherals for certain uses. This model is best for budget-conscious users who want reliable performance for media, IoT, or light computing tasks.
Pros:- Powerful 1.5 GHz quad-core Cortex-A72 CPU
- 8GB RAM for multitasking and media applications
- Dual 4K HDMI support for high-quality video output
- Supports high-speed USB 3.0 ports
Cons:- Requires an external Wi-Fi adapter
- Higher power consumption with USB-C power supply
- Limited onboard storage options without external drives
Best for: Budget-conscious hobbyists and educators seeking a versatile, well-supported SBC for media and lightweight computing
Not ideal for: Power users requiring high processing throughput or extensive onboard storage, or those needing built-in Wi-Fi and USB 3.0 support
- RAM:8 GB
- Processor Speed:1.5 GHz
- USB Ports:2 (USB 3.0)
- Connectivity:Ethernet, Bluetooth 5.0
- Operating System:Raspberry Pi OS
- Video Output:Dual 4K@60Hz via micro HDMI
Bottom line: This is the best option for those who want a cost-effective, capable SBC with strong multimedia support and active community backing.
How We Picked
We evaluated each single-board computer based on performance, expandability, connectivity options, price-to-value ratio, and community support. Boards with robust hardware specifications, versatile I/O options, and reliable software ecosystems scored higher. We also considered the target user — whether beginners, developers, or industrial users — and prioritized models that meet common project requirements without excessive complexity. The ranking reflects a balance between raw power, usability, and value, ensuring a broad range of needs are addressed.Factors to Consider When Choosing Best Single-board Computers
When selecting a single-board computer, it’s important to weigh several key factors to match your project’s demands. Performance is crucial, especially if you’re running intensive applications or AI workloads. Connectivity options like Ethernet, Wi-Fi, and USB determine how well the SBC integrates with other hardware. Expandability features such as M.2 slots and GPIO pins can influence future upgrades. Size and power consumption are vital for embedded or portable projects. Lastly, consider software support and community resources, which can significantly impact your development experience.Performance and Processing Power
Understanding the CPU and GPU capabilities of an SBC helps you match the board to your workload. For simple media centers or IoT projects, lower-power ARM chips may suffice. However, for AI, machine learning, or desktop-like tasks, boards with more powerful processors like Intel or high-end ARM cores are necessary. Be cautious of overestimating your needs—paying extra for unnecessary power can lead to wasted budget and higher power consumption.
Connectivity and I/O
Check the available ports and networking options—Ethernet, Wi-Fi, Bluetooth, USB, HDMI, and GPIO pins—since these determine how easily your SBC integrates with other hardware. Industrial or server applications demand Gigabit Ethernet and multiple I/O options, while portable projects may prioritize Wi-Fi and Bluetooth. Consider future expansion—boards with M.2 slots or PCIe support can accommodate additional peripherals or storage devices.
Expandability and Upgrades
Boards with support for SSDs, additional RAM, or GPIO expansion provide longer-term flexibility. For example, models supporting NVMe SSDs are better suited for data-intensive tasks. Conversely, compact boards with minimal expansion options are ideal for embedded or space-constrained applications but limit future upgrades. Think about your project’s expected lifespan and whether you might need to upgrade hardware down the line.
Size, Power, and Portability
Size impacts where and how you deploy your SBC. Smaller boards are perfect for embedded or portable devices, but may have fewer ports or less performance. Power consumption is critical for battery-powered or energy-sensitive projects—more powerful boards tend to draw more power. Balance size and power needs with your project’s environment to avoid over-specifying hardware or running into space constraints.
Community Support and Software Ecosystem
A strong community can greatly ease development, troubleshooting, and project customization. Popular boards like the Raspberry Pi have extensive documentation, tutorials, and third-party accessories. Less common or more specialized boards may lack this support but offer unique hardware advantages. Consider your familiarity level—beginners benefit from well-supported platforms, while advanced users might prioritize technical specs over community size.
Frequently Asked Questions
What is the best single-board computer for AI projects?
The NVIDIA Jetson Orin Nano excels at AI and machine learning tasks thanks to its dedicated NPU and GPU hardware, delivering high-performance inference capabilities. It’s more expensive than general-purpose boards but provides hardware acceleration crucial for AI workloads. If your focus is AI development, this board minimizes the need for additional processing hardware, saving time and complexity.
Can I run Windows on a single-board computer?
Some SBCs like the LattePanda 3 Delta are designed to run full Windows OS, thanks to their x86 architecture. This makes them suitable for applications that require Windows compatibility or specific Windows-based software. However, most ARM-based boards like Raspberry Pi or Orange Pi are limited to Linux distributions. Choosing an x86 board involves considering higher costs and power consumption but offers familiar software environments.
How do I decide between a Raspberry Pi and a more powerful SBC?
Raspberry Pi boards are ideal for beginners, educational projects, and low-cost applications due to extensive support and community resources. More powerful SBCs like LattePanda or NVIDIA Jetson provide increased processing power and specialized features but come at a higher price and complexity. Your decision should depend on whether your project demands extra performance or if a simple, well-supported platform suffices.
Are expandable features worth the extra cost?
Expandability options like M.2 slots, additional RAM, or PCIe support can extend the lifespan and versatility of your SBC, especially for data-heavy or industrial applications. However, boards with these features tend to be pricier and sometimes larger. If your project is likely to evolve or require upgrades, investing in expandable hardware makes sense; otherwise, a simpler, less expensive board might be more practical.
What should I consider for portable or embedded projects?
Size and power consumption are the primary factors for portable projects. Compact boards like Orange Pi 4 Pro or Raspberry Pi Zero variants are ideal, but they may sacrifice some connectivity or processing power. For embedded applications, low power draw and minimal size are critical, so select a board designed for energy efficiency and space constraints. Balancing these factors ensures your project remains practical and reliable.
Conclusion
For general-purpose use and a balance of features, the LattePanda 3 Delta offers the best overall experience, especially if Windows compatibility matters. Budget-conscious buyers should consider the Raspberry Pi 5 8GB for its strong performance at a low price point. Developers focused on AI or machine learning will find the NVIDIA Jetson Orin Nano the most capable, despite its higher cost. Beginners and hobbyists will benefit from the extensive community and ease of use with the Raspberry Pi 4 Model B. Industrial or embedded projects should prioritize boards with expandability and robust connectivity, like the Cubie A5E or Orange Pi 4 Pro. Ultimately, your choice hinges on your specific project needs and budget constraints.
