Comparison of Raspberry Pi Models vs Competitor SBCs

This comparison covers popular Raspberry Pi models and several popular competing single-board computers (SBCs): NVIDIA Jetson Nano, Google Coral Dev Board, BeagleBone Black, Hardkernel ODROID N2+, and Radxa Rock Pi 4. Key metrics include performance (CPU, GPU, AI acceleration, power, thermals), physical form factor, connectivity, and suitability for various use cases. Each board’s country of origin is also noted.

Performance Metrics

The table below compares CPU and GPU specifications, AI processing capabilities, typical power consumption, and thermal characteristics of Raspberry Pi boards and competitor SBCs:

Board (Origin)	CPU (Processor & Clock)	GPU & Video	AI Acceleration	Power Consumption	Thermal Performance
Raspberry Pi Zero W (UK)	Broadcom BCM2835, 1× ARM11 @ 1.0 GHz (ARMv6). Single core; very limited compute performance (based on 2012 Pi 1).	Broadcom VideoCore IV @ 250 MHz (older 3D GPU). 1080p60 H.264 decode. No 3D graphics acceleration for modern APIs beyond OpenGL ES 2.0.	None. No dedicated AI hardware. Only CPU for ML (impractical for heavy AI).	Idle:~0.7 W; Load: ~1–2 W (very low power). Can run from battery for IoT sensors.	Runs cool under most loads. No heatsink needed. Even at max load (~1 W), temperature stays low.
Raspberry Pi 3 B+ (UK)	Broadcom BCM2837B0, 4× Cortex-A53 @ 1.4 GHz (64-bit). Moderate performance (3–4× faster than Pi Zero).	Broadcom VideoCore IV GPU. 1080p60 H.264 decode; OpenGL ES 2.0 support. Limited for 3D graphics or 4K video.	None. No AI accelerator. CPU can run small TensorFlow Lite models, but slowly.	Idle: ~1.9 W; Load: ~5.1 W (full CPU). Powered via 5V/2.5A microUSB. Low energy footprint.	Runs warm; has a metal heat-spreader on SoC. Throttling: Starts ~80 °C. Usually stays <70 °C with modest cooling.
Raspberry Pi 4 B (UK)	Broadcom BCM2711, 4× Cortex-A72 @ 1.5 GHz (64-bit). ~3× the CPU performance of Pi 3. Available with 1–8 GB RAM.	Broadcom VideoCore VI @ 500 MHz. Supports OpenGL ES 3.x; 4Kp60 H.265/H.264 decode and 1080p30 encode. Decent for media playback and light 3D.	None on-board.(Can use USB accelerators if needed). CPU/GPU can handle some ML tasks, but much slower than dedicated AI chips.	Idle: ~2.7 W; Load: ~6–7 W (quad-core CPU stress). Requires 5V/3A (15 W) USB-C supply.	Runs hot under load (28 nm SoC). Without cooling, will hit 80 °C and throttle. Heatsink/fan recommended for sustained performance.
NVIDIA Jetson Nano (USA)	NVIDIA Tegra X1 (Maxwell GPU SoC) with 4× Cortex-A57 @ 1.43 GHz. Similar multi-core performance to Pi 4 (slightly weaker CPU, but better GPU). 4 GB LPDDR4 RAM.	128-core NVIDIA Maxwell GPU @ 921 MHz (472 GFLOPS FP16). Capable of advanced 3D graphics and CUDA computations. Video encode: 4K30; decode: 4K60 HEVC.	GPU AI acceleration:Yes – supports CUDA, cuDNN, TensorRT. ~0.5 TFLOPS FP16 for AI inference. Excellent for computer vision, DNNs. No dedicated NPU; uses GPU for AI.	5 W and 10 W power modes. Idle: ~2–3 W; Max:~10 W in default mode. Needs 5V/4A (20 W) if fully utilizing peripherals.	Large passive heatsink included. Runs ~50–60 °C under moderate load. Can approach thermal limits at 10 W; a fan may be needed in sustained heavy AI workloads. Generally avoids throttling with default heatsink.
Google Coral Dev Board (USA)	NXP i.MX 8M SoC: 4× Cortex-A53 @ 1.5 GHz. Moderate CPU performance (similar to Pi 3). 1 GB or 4 GB LPDDR4 RAM.	GC7000Lite GPU (Vivante)– basic 3D graphics; supports 1080p/720p displays (4K@30 max). Can decode 1080p60 H.264/H.265; 4K possible at lower framerate. Not designed for gaming or heavy GUI.	Edge TPU (ML accelerator): Yes – Google Edge TPU coprocessor (4 TOPS int8) on-board. Handles ~400 FPS MobileNet v2 inference in 2 W (extremely fast for vision models). No training, inference only.	Typically ~3–5 W under AI load (TPU ~2 W at full 4 TOPS, plus CPU). 5V/3A USB-C power input. Efficient for its AI performance.	Edge TPU and CPU are on a small module; moderate heat output. Comes with a heat spreader; may throttle if Edge TPU is run at max sustained. Best used with some airflow or heatsink for long AI inference sessions.
BeagleBone Black (USA)	TI Sitara AM3358, 1× Cortex-A8 @ 1.0 GHz. Single core, older ARMv7 architecture. Modest performance (comparable to Pi Zero 2 or Pi 1 levels). 512 MB DDR3 RAM.	PowerVR SGX530 GPU (limited OpenGL ES 2.0). Not generally used for display (often headless). Capable of driving a 16-bit LCD or micro-HDMI output at 1080p but not smooth for HD graphics.	2× PRU 32-bit microcontrollers (200 MHz) on-chip for real-time tasks. No neural accelerators. BeagleBone AImodel (separate board) adds TI DSP and AI co-processors, but Black does not have those.	Very low power: Idle: ~0.5–1 W; Load: ~2 W. Typically powered via 5V barrel or USB (500 mA). Can run from modest supply.	Runs cool without heatsink (CPU < 60 °C typically). Designed for embedded use in enclosed projects – stable thermal profile at 1 GHz. No throttling in normal conditions.
Hardkernel ODROID N2+ (South Korea)	Amlogic S922X SoC: 4× Cortex-A73 @ 2.2 GHz + 2× Cortex-A53 @ 2.0 GHz (big.LITTLE). Highest CPU performancehere – outperforms Pi 4 (A73 cores and higher clocks). Up to 4 GB DDR4 RAM.	ARM Mali-G52 MP6 GPU @ 800 MHz (Bifrost). ~10% faster than Mali-T860MP4. Supports OpenGL ES 3.2, Vulkan 1.0, OpenCL 2.0. Great for 3D gaming, emulation, and 4K60 video (hardware decode for H.265/VP9).	No dedicated AI unit. Can use GPU OpenCL for ML, or external USB TPU. (The N2+ focuses on CPU/GPU throughput; an external NPU module was offered by Hardkernel for AI, but not built-in.)	Idle: ~2.3–2.5 W; 6-core CPU load:~6.0 W. Highly power-efficient for its performance (12 nm SoC). 5V/2–4A barrel jack input.	Massive aluminum heatsink base included (90×90 mm board sits on it). Excellent cooling– can run at full 2.4 GHz without throttling. Stays under ~70 °C in heavy use. Often used fanless.
Radxa Rock Pi 4 (China)	Rockchip RK3399, 2× Cortex-A72 @ 2.0 GHz + 4× Cortex-A53 @ 1.6 GHz. Multicore performance on par with Pi 4 (similar scores in Geekbench). Up to 4 GB LPDDR4 RAM.	ARM Mali-T860 MP4 GPU. Good mid-range GPU: OpenGL ES 3.0, Vulkan 1.0 support. Handles 1080p gaming and UI smoothly. 4K60 H.265/H.264 video decode, 1080p30 encode.	No on-board AI engine.RK3399Pro variant (Rock Pi N10) adds an NPU (3 TOPS), but standard Rock Pi 4 relies on CPU/GPU for any ML tasks.	Idle: ~2.0 W; Load: ~6–8 W (CPU+GPU). Similar power envelope to Pi 4. Requires 5V USB-C supply (supports QC/PD input up to 12V).	Needs a heatsink for sustained heavy use – RK3399 will throttle under continuous load without cooling. With a proper heatsink or fan, it maintains full performance. Generally stable thermals with cooling; can run headless at high loads if cooled.

Notes: All Raspberry Pi models and the Rock Pi 4 are designed in the UK or China, whereas Jetson Nano and Coral originate from USA, and ODROID from South Korea. BeagleBone boards are a project from a US-based foundation. “AI acceleration” refers to dedicated neural network inferencing hardware. GPU entries note 3D capabilities and video encode/decode support.

Form Factor & Connectivity

The following table compares physical dimensions and connectivity features: including available ports (USB, video outputs, Ethernet), wireless capabilities, and expansion headers of each board:

Board	Dimensions(mm)	USB Ports	Display Outputs	Networking	Wireless	GPIO / Expansion	Other Interfaces & Storage
Raspberry Pi Zero W	65 × 30 × 5 mm (tiny).	1× micro-USB OTG (USB 2.0). Power via separate micro-USB. No standard USB-A ports on board (requires adapters).	1× mini HDMI (1080p60 output). No secondary display connector.	No Ethernet port on-board (can use USB adapter).	2.4 GHz Wi-Fi (802.11n) & BT 4.1 LE built-in.	40-pin GPIO header (unpopulated) – same pinout as larger Pis.	Storage: microSD slot. Camera: Yes, 1× CSI-2 camera connector (mini). Other:Unpopulated pads for composite video.
Raspberry Pi 3 B+	82 × 56 × 19 mm (credit-card size).	4× USB 2.0 Type-A ports (480 Mb/s). Micro-USB for power (5V).	1× HDMI 1.3 (full-size) for up to 1080p output. 1× Composite A/V via 3.5 mm jack.	1× RJ45 Ethernet (Gigabit, via USB2 bus – ~300 Mbps max).	Dual-band Wi-Fi 4 (802.11ac 2.4/5 GHz) & BT 4.2 LE on-board.	40-pin GPIO header (populated) – extensive I/O (28 GPIO, I2C, SPI, UART, etc.).	Storage:microSD slot. Camera:1× CSI-2 camera port. Display:1× DSI ribbon connector. Other:PoE support via HAT (requires PoE add-on).
Raspberry Pi 4 B	85.6 × 56.5 × ~17 mm. Same footprint as Pi 3; slightly taller due to ports.	2× USB 3.0 + 2× USB 2.0 Type-A. USB-C for power (also supports USB 2.0 OTG).	2× micro-HDMI 2.0 ports – supports dual monitors up to 4K60. 3.5 mm A/V jack (stereo audio + composite video).	1× Gigabit Ethernet (full 1000 Mbps throughput). Optional PoE via HAT.	Dual-band Wi-Fi 5 (802.11ac) & BT 5.0 on-board.	40-pin GPIO (populated, Pi standard). Backward-compatible pinout with prior Pi’s.	Storage: microSD slot. (Boot from USB 3.0 drives supported via firmware). Camera/Display:2× MIPI CSI-2 camera and 1× MIPI DSI display connectors. Other: Dedicated Ethernet controller, improved USB bandwidth.
NVIDIA Jetson Nano	100 × 80 × 29 mm (including large heatsink). Board is larger than Raspberry Pi.	4× USB 3.0 Type-A (5 Gb/s). 1× Micro-USB 2.0 (device mode or 5V input). DC barrel jack on some kits (for 5V power).	1× HDMI 2.0 and 1× DisplayPort 1.2– dual simultaneous display support. (No DSI output on dev kit.)	1× Gigabit Ethernet (RJ45) on dev kit.	No built-in Wi-Fi/Bluetoothon standard dev kit. (Users can add via M.2 E-key slot or USB dongle). Newer Nano 2GB kit uses Wi-Fi dongle.	40-pin GPIO header (Raspberry Pi–compatible pin layout) for I/O (UART, I2C, SPI, GPIO).	Storage: microSD slot (dev kit). (Nano module version has 16 GB eMMC). Camera: 2× MIPI CSI-2 camera connectors (supports up to 2 cameras). Other: M.2 E-key slot for optional Wi-Fi/BT or NVMe (B01 revision).
Google Coral Dev Board	88 × 60 × 24 mm (including SOM + heatsink) – compact footprint.	1× USB 3.0 Type-A host, plus 1× USB Type-C OTG (for data/power). 1× Micro-USB (serial console).	1× HDMI 2.0a (full-size, 4K30 output). 1× MIPI-DSI (4-lane) via FFC connector.	1× Gigabit Ethernet port (RJ45) on baseboard.	Dual-band Wi-Fi 5 (2×2 MIMO 802.11ac) & Bluetooth 4.2 BLE built-in.	40-pin GPIO header (compatible pin layout with Pi in function) – for digital I/O, i.MX8M’s interfaces.	Storage: 8 GB eMMC on SOM + microSD slot. Camera: 1× MIPI-CSI2 camera connector (4-lane). Audio: 3.5 mm audio jack, 2× built-in PDM microphones, 4-pin speaker out. Other: Ships as a removable SOM + baseboard for prototyping.
BeagleBone Black	86 × 53 × 18 mm (credit-card size) – fits in an Altoids tin.	1× USB 2.0 Type-A host, 1× mini-USB 2.0 (client/OTG, also for power).	1× micro-HDMI (1080p output). (Older BeagleBone had mini-DVI; Black adds HDMI).	1× 10/100 Ethernet (RJ45). (Throughput ~90 Mbps).	No on-board Wi-Fi or BT on standard Black. (BeagleBone Black Wireless variant includes 802.11n and BT 4.1).	2× 46-pin GPIO headers (extensive I/O: ~65 digital I/O, 7 analog inputs, I2C, SPI, UART, etc.). Many pins configurable via device tree; supports “capes” (add-on boards).	Storage: On-board 4 GB eMMC flash (preloaded with Debian) + microSD slot. Other: 1× serial debug header. Real-time I/O: 2 PRU microcontrollers accessible via headers for precise timing (unique feature).
Hardkernel ODROID N2+	90 × 90 × 17 mm (board). Sits on a 100 × 91 × 18 mm heatsink base. Not the same layout as Raspberry Pi.	4× USB 3.0 Type-A (5 Gb/s). 1× USB 2.0 Micro-B OTG (for device mode/ADB).	1× HDMI 2.0 (4K@60Hz with HDR) output. (No secondary display interface on main board).	1× Gigabit Ethernet (RJ45), full 1000 Mbps throughput.	No on-board Wi-Fi/Bluetooth.(Requires external USB adapter or the ODROID WiFi module accessory).	40-pin GPIO header (Pi-style, 3.3 V) – supports I/O, SPI, I2C, etc., similar pinout to ODROID-C2/Pi. Also a 7-pin JST for analog audio and IR.	Storage: microSD slot, and high-speed eMMC module socket(for up to 128 GB eMMC). Other: IR receiver on-board (for remote control), RTC with battery backup, SPI flash (8 MB) with bootloader.
Radxa Rock Pi 4	85 × 54 mm (matches Pi 3/4 footprint); 18 mm tall.	2× USB 3.0 Type-A + 2× USB 2.0 Type-A (same configuration as Pi 4). 1× USB Type-C for power (supports QC/PD input), which also functions as USB 3.0 OTG.	1× HDMI 2.0 (micro HDMI on Model A/B, full-size on Model C+) up to 4K@60. (Model C+ also includes a mini DisplayPort for dual display).	1× Gigabit Ethernet (RJ45).	Model B/C: Dual-band Wi-Fi 5 (802.11ac) & BT 5.0 on-board. (Model A lacks Wi-Fi/BT)	40-pin GPIO header (Pi-compatible layout, 3.3 V logic). Allows use of many Raspberry Pi HATs and expansions.	Storage: microSD slot. On-board eMMC socket for faster storage. Also M.2 M-Key slot (PCIe x4) for NVMe SSD (via optional adapter board). Camera/Display:2× MIPI CSI camera and 1× MIPI DSI display connectors (Pi compatible). Other: 3.5 mm audio jack with mic input.

Highlights:

Size & Form Factor: Raspberry Pi and Rock Pi 4 share a compact credit-card size, facilitating use of existing cases and accessories. Jetson Nano and ODROID N2 are larger boards with big heatsinks, better suited for installation in embedded systems or enclosures that can accommodate their size. Pi Zero W is ultra-small and lightweight, ideal for size-constrained projects.
USB and Peripherals: Raspberry Pi 4 and Rock Pi 4 offer USB 3.0 connectivity for high-speed peripherals. Jetson Nano provides four USB3 ports as well. Pi Zero has only a single USB OTG (requiring a hub for multiple devices). BeagleBone Black’s single USB host limits peripheral count without an external hub.
Video Outputs: Raspberry Pi 4 supports dual monitors (two micro-HDMI), unique among these (Jetson has HDMI+DP for dual display, while others typically have one display output). Most can output at least 1080p; Pi 4, Jetson, ODROID, Rock Pi support 4K output. BeagleBone’s micro-HDMI is mainly for basic display or GUI, and Coral’s HDMI supports up to 4K30.
Networking: All except Pi Zero and BeagleBone have wired Ethernet (100 Mbps on BeagleBone, Gigabit on Pi 3B+/4, Jetson, Coral, ODROID, Rock Pi). Wireless connectivity is built-in on Raspberry Pi’s (except Pi Zero v1.3), Coral, and Rock Pi 4, whereas Jetson Nano and ODROID N2 require external Wi-Fi. This can be a deciding factor for projects needing wireless out-of-the-box.
Expansion Headers: Raspberry Pi’s 40-pin header has become a de-facto standard, and both Jetson Nano and Rock Pi 4 mimic this for compatibility. BeagleBone’s dual 46-pin headers provide far more I/O pins and unique features (like analog inputs and PRU signals) not present on the others. ODROID N2 and Coral also have expansion headers for GPIO and common interfaces, but with less community standardization than Raspberry Pi’s.

Use Case Comparisons

Each board has strengths in different application domains. The table below rates the suitability of each for various use cases: AI/ML, Robotics, Media Center, Edge Computing, IoT, and General Desktop Computing.

AI / ML (Neural network inference, vision)

Pi Zero W: Very limited CPU; not feasible for ML except trivial tasks.
Pi 3 B+: No AI hardware; can run small models on CPU but slow.
Pi 4 B: Fair – Can handle basic TensorFlow Lite models on CPU; no accelerator on-board.
Jetson Nano: Excellent – Designed for AI; 128-core CUDA GPU accelerates deep learning. Runs CNNs, object detection, etc., efficiently.
Coral Dev Board: Excellent – Purpose-built Edge TPU (4 TOPS) for fast inferencing. Ideal for vision models and low-power AI on the edge.
BeagleBone Black: Limited – No AI acceleration; 1 GHz CPU struggles with ML. BeagleBone AI model exists, but Black is not for neural networks.
ODROID N2+: Fair – Powerful CPU can run some models, and GPU supports OpenCL, but no specialized AI unit. Can use USB TPU add-on.
Rock Pi 4: Fair – Similar to Pi 4 – strong CPU/GPU but no dedicated ML hardware. Suitable for running AI with USB accelerators or small models.

Robotics (DIY robots, drones, motor control)

Pi Zero W: Fair for very simple robots or IoT sensors; small size is a plus, but limited processing for vision or complex tasks.
Pi 3 B+: Good – Widely used in hobby robotics. Has Wi-Fi, decent GPIO, and community support for robot frameworks.
Pi 4 B: Good – More CPU power for sensor fusion, can do some onboard vision. Many robotics HATs and libraries available.
Jetson Nano: Good – Great for robots needing onboard vision/AI (e.g., object tracking with camera). Higher power draw and size, so better for larger robots.
Coral Dev Board: Good – Focused on edge AI, so good for autonomous robotics that need fast ML inferencing. CPU is moderate, so best paired with tasks that leverage the TPU for vision.
BeagleBone Black: Excellent – Often used in industrial robotics. Real-time PRU co-processors allow precise motor control, timing, and feedback loops. Lots of I/O for interfacing with sensors/actuators.
ODROID N2+: Good – High-performance CPU can handle complex robot software (SLAM, planning). Lacks onboard IMU or ADC but can be interfaced.
Rock Pi 4: Good – Similar use as Raspberry Pi 4 for robotics. More performance headroom for vision than Pi 3. Has CSI camera ports and can add accelerators.

Media Center (Home theater, Kodi, video playback)

Pi Zero W: Fair – Can output 1080p video, but GUI may be sluggish. Handles only up to 1080p H.264 smoothly.
Pi 3 B+: Good – 1080p media playback is solid. Can run Kodi or RetroPie well at 1080p. Limited to 1080p output, no 4K.
Pi 4 B: Excellent – Popular 4K media center choice. Dual-display, hardware decode of 4K60 H.265, H.264, and partial VP9. Runs LibreELEC/Kodi smoothly.
Jetson Nano: Good – Can serve as a 4K media player. Capable of 4Kp60 decode, HDMI 2.0 output, and powerful GPU for high-bitrate video.
Coral Dev Board: Fair – Can play videos up to 1080p/4K30, but media is not its main focus. Lacks community HTPC setups.
BeagleBone Black: Poor – Not intended for media playback. Can do basic video out via HDMI, but no HD video decode hardware.
ODROID N2+: Excellent – Very strong for media center. Hardware decode for 4K HDR content. HDMI CEC and IR receiver built-in for remote control.
Rock Pi 4: Good – Can function well as a media hub. Decodes 4K video in hardware. NVMe storage can hold large media library.

Edge Computing (on-site data processing, gateways)

Pi Zero W: Fair – Suitable for simple IoT edge tasks. Not suitable for heavy processing.
Pi 3 B+: Good – Can act as an IoT gateway or edge server for moderate workloads. Limited RAM (1 GB) constrains heavier edge analytics.
Pi 4 B: Good – Quad-core and up to 8 GB RAM make it viable for robust edge computing. Widely used in edge deployments.
Jetson Nano: Excellent – Designed for edge AI computing. Ideal for deploying AI models at the edge without cloud.
Coral Dev Board: Excellent – Purpose-built for edge ML. Excels at scenarios like local image classification, anomaly detection on-device.
BeagleBone Black: Good – Robust IO, can directly interface with machinery. Often used in factories for control and data logging.
ODROID N2+: Good – Has the horsepower to act as an edge server. Can run containers, databases, etc., more efficiently than Pi.
Rock Pi 4: Good – Similar to Pi 4 in edge use; plus faster I/O (eMMC/NVMe) for local data logging or databases.

IoT (embedded IoT devices, sensors, remote monitoring)

Pi Zero W: Excellent – Very low-cost and small. Great for embedding in IoT devices. Wi-Fi + BT onboard for connectivity.
Pi 3 B+: Good – Frequently used as IoT hub or device. Wi-Fi and wired net give flexibility.
Pi 4 B: Good – Excellent as an IoT gateway or controller. More power usage but can handle more concurrent IoT tasks.
Jetson Nano: Fair – Powerful, but power consumption and size make it less ideal for battery-powered or tiny IoT deployments.
Coral Dev Board: Fair – Focused on AI IoT. Great for “intelligent IoT” nodes. Consumes ~3W idle, so not as low-power as Pi Zero.
BeagleBone Black: Good – Geared towards industrial IoT. Lots of I/O to directly connect sensors/actuators.
ODROID N2+: Good – Suitable for gateways, local processing nodes, etc. Lacks built-in wireless.
Rock Pi 4: Good – Shares Raspberry Pi’s versatility in IoT, with added features like faster storage for databases or logs.

General Computing (desktop use, education, basic PC tasks)

Pi Zero W: Poor – Too slow for most desktop environments. Best used headless or for specific single-purpose applications.
Pi 3 B+: Fair – Can function as a basic desktop in a pinch. Good for learning Linux, programming basics.
Pi 4 B: Good – Usable as a low-cost Linux PC. 4 GB/8 GB RAM options and faster CPU allow web browsing, coding, etc.
Jetson Nano: Good – Can run a full Ubuntu desktop and handle multitasking well. Mainly aimed at developers.
Coral Dev Board: Fair – Runs Debian-based Mendel Linux. Not ideal for a full desktop experience.
BeagleBone Black: Fair – Primarily an embedded board. Can output GUI but not smooth for modern desktop tasks.
ODROID N2+: Excellent – Can serve as a mini PC or Linux workstation. Ubuntu with MATE runs very fast.
Rock Pi 4: Good – Similar to Pi 4 for everyday computing. Can handle web browsing, coding, etc.

Notes: Raspberry Pi boards (especially Pi 4) are often the first choice for education, basic desktop projects, and maker endeavors because of their balanced performance and strong community support. The Jetson Nano and Coral Dev Board shine in AI/ML use cases – Jetson for versatility in model types (FP16 GPU compute) and Coral for power-efficient high-speed inferencing. BeagleBone Black is niche butexcellent for real-time control(e.g., robotics that need deterministic timing). ODROID N2+ offers an ARM platform powerful enough to replace some PC workloads in a pinch, making it popular among enthusiasts who need more performance than Raspberry Pi for things like emulation, servers, or 4K media.

Price-Performance & Notable Features

Finally, we compare approximate prices and highlight unique features that differentiate each board, often dictating their ideal applications:

Board	Typical Price (USD)	Price-Performance	Notable Unique Features / Niche Strengths
Raspberry Pi Zero W	~$10 (Zero W, 512 MB). $15 (Zero 2 W, quad-core).	Unbeatable value for size/cost. The cheapest here by far. Performance is very low, but for simple tasks $10 goes a long way.	Ultrasmall form factor: tiny footprint for wearables, sensors, or hidden computing. Lowest power draw:great for battery IoT. Cost-sensitive projects: can deploy many nodes cheaply.
Raspberry Pi 3 B+	$35 (at release for 1 GB model).	Good performance per dollar (Quad-core & wireless for $35). Now surpassed by Pi 4, but second-hand or in kits, it’s still affordable.	Mature ecosystem: huge community, many hats/shields and tutorials. Backward compatibility: works with many existing Pi accessories. All-in-one connectivity: first Pi with dual-band Wi-Fi and improved Ethernet – solid for general projects.
Raspberry Pi 4 B	$35 (1 GB) to $75 (8 GB). (2 GB ~$45, 4 GB ~$55).	High bang-for-buck: Still one of the most cost-effective SBCs given its capabilities. Offers desktop-class features (dual 4K, USB3, 8GB RAM) at under $100.	Versatility: excelling in many roles – from media center to Kubernetes cluster node. Massive software support:official Raspberry Pi OS and others optimized for it. Community & longevity: foundation guarantees long-term supply, tons of documentation.
NVIDIA Jetson Nano	$99 (Developer Kit). $129 (production module).	Good value for an AI-focused SBC (significantly cheaper than NVIDIA’s higher-end Jetsons). More expensive than Pi 4, but you’re paying for the CUDA-capable GPU.	CUDA and NVIDIA AI Stack: Only platform here with full GPU CUDA support – can run PyTorch, TensorFlow with GPU acceleration. Edge AI powerhouse: brings supercomputer-class AI frameworks to hobbyists. Flexible power modes: can scale 5W/10W for different scenarios. Great for learning AI, robotics vision, and GPU programming.
Google Coral DevBoard	$150 (1 GB RAM), $200 (4 GB) – note: often out of stock or higher due to demand.	Expensive relative to general SBCs, but priced for its specialized TPU. Pure CPU/GPU power per dollar is low; value comes if your use case needs the Edge TPU acceleration (which outperforms others on int8 ML tasks).	Edge TPU (4 TOPS): Ultra-fast inferencing for quantized models – orders of magnitude faster on these than CPUs. Low-power ML: 2 TOPS/W efficiency is stellar. Modular design: the compute module can be pulled off and integrated into products, attractive for startups prototyping on Dev Board then scaling to custom boards. Great for vision AI at the edge (smart cameras, IoT AI sensors).
BeagleBone Black	~$55–$60 (Rev C, 4 GB eMMC).	Decent value for embedded I/O-heavy projects. CPU/$ is low, but you’re paying for reliability and I/O rather than raw performance. Often in stock when Raspberry Pis are not, which has made it a Pi alternative despite lower specs.	Precise I/O and control: dual PRUs give capabilities none of the others have – software-defined peripherals, real-time bit-banging, etc. Built-in eMMC: faster and more robust storage for embedded apps than SD cards. Industrial use: designed to be mounted and used in prototypes and products (many BeagleBones run 24/7 in factories). Fully open hardware design.
Hardkernel ODROID N2+	~$80 (2 GB) / $100 (4 GB). (Includes big heatsink in price.)	High performance per dollar: At ~$80 it outperforms some x86 micro-PCs in CPU tasks. Lacks some peripherals (Wi-Fi, etc.), but if you need sheer speed in an SBC, the $/compute is excellent.	Speed and thermals: one of the fastest ARM SBCs in its class – great for demanding tasks (compiling code, running game console emulators, etc.). Media & Emulation: beloved in retro gaming community – can emulate PSP, N64, Dreamcast at better frame rates than Pi. Heatsink design: robust cooling out of the box, ideal for sustained loads in harsh environments. Also has quality-of-life features like IR receiver and RTC.
Radxa Rock Pi 4	$60 (1 GB) to $75 (4 GB). ($69 for 4 GB Model C+)	Competitive pricing with Raspberry Pi for similar specs (often slightly higher cost than an equivalent RAM Pi 4, but offers some extras like eMMC). Community is smaller, so factor in effort as part of “cost.”	Storage flexibility: eMMC module support and NVMe SSD via M.2 give it an edge for high-speed storage needs – ideal for databases or disk-intensive tasks on SBC. Pi Form-factor with extra kick: drop-in alternative where one might use a Pi, but possibly get better I/O throughput (PCIe interface) and CPU boost (2.0 GHz big cores). Expandable power input: supports wide-range PSU (6–12V) which can be handy in automotive or battery applications.

Notable Trends: Raspberry Pi’s ecosystem and balanced design make it a generalist champion – often “good enough” across many categories at a very low price, which explains its popularity. Competitors like Jetson and Coral carve out niches in AI and performance, albeit at higher prices. BeagleBone addresses the embedded industrial niche with its real-time IO, while ODROID and Rock Pi target users needing more performance or features (like fast storage) than the Raspberry Pi can provide. Country of origin sometimes influences ecosystem and support – e.g., Raspberry Pi (UK) and BeagleBone (USA) have strong non-commercial community roots, NVIDIA/Google boards tie into corporate ecosystems, and ODROID/Radxa (Korea/China) often appeal to open-source hardware enthusiasts and are supported through manufacturer forums and the Arm Linux community.

Each of these SBCs has unique strengths, and the “best” choice ultimately depends on the project requirements – be it raw computing power, machine learning, low power operation, I/O needs, budget, or community support. This comparison provides a high-level guide to inform that selection, with detailed specs and use-case suitability to match the right board to the right job.