Choosing the right single board computer (SBC) matters whether you’re building a home server, edge AI prototype, robotics brain, or a compact embedded gadget. These recommendations come from hands-on testing, benchmarking, and synthesis of expert reviews and user feedback to surface the best SBCs for different needs.
How we tested and chose
What we evaluated
- Real-world performance: CPU, GPU, and I/O under representative workloads (media playback, compilation, containerized services, and inference for AI boards).
- Connectivity and expandability: USB, PCIe/M.2, Ethernet, Wi‑Fi/Bluetooth, camera and display interfaces.
- Power and thermals: typical power draw, throttling behavior, and cooling needs.
- Software and ecosystem: OS support (mainline Linux, vendor SDKs), drivers, community resources, and availability of accessories.
- Price and value: cost per capability, long-term maintainability, and accessory ecosystem.
Inputs used
- Hands-on benchmarks and sustained load testing.
- Expert reviews (industry outlets and community maintainers).
- Consumer feedback (issues reported, common use cases, and accessory availability).
How this shaped rankings
We prioritized boards that combine stable software ecosystems with predictable thermal and power behavior. For niche, high-performance AI tasks we favored capability and SDK support; for hobbyist and general-purpose use we emphasized ease of use, community support, and cost-effectiveness.
4GB Pi 5 SBC
A compact, general-purpose SBC with a speedy Cortex‑A76 quad-core CPU, modern GPU, dual-band Wi‑Fi, and USB 3.0 ports. It’s an affordable entry to desktop-class ARM computing for hobbyists, media centers, and home servers, with excellent community support and accessories.
Overview
The 4GB Pi 5 offers desktop-grade performance in a familiar Raspberry Pi ecosystem. With a 2.4GHz quad‑core Cortex‑A76 and VideoCore VII GPU, it handles light desktops, media playback, and small servers well. Key strengths are its strong community support, broad accessory compatibility, and a modest price point.
Standout features & analysis
- CPU/GPU: Quad‑core Cortex‑A76 gives a noticeable step up over previous Pi generations for compiling and web workloads.
- I/O: 2 × USB 3.0 + 2 × USB 2.0 supports fast storage and peripherals; Gigabit Ethernet is standard.
- Connectivity: Dual‑band Wi‑Fi and Bluetooth 5.0 cover common wireless needs.
- Software: Excellent first‑party OS support and wide third‑party images (Ubuntu, Raspberry Pi OS).
When to pick this
Choose the 4GB Pi 5 if you want an affordable, well-supported SBC for desktop‑light tasks, media centers, learning Linux, or home automation projects. It’s the most approachable, budget‑friendly way to access modern ARM performance.
NVIDIA Jetson Orin Nano
A premium edge-AI developer kit delivering up to 67 TOPS of inference performance. It pairs a powerful Ampere GPU with a multi-core ARM CPU and full JetPack software stack, ideal for robotics, vision AI, and demanding embedded inference tasks.
Overview
The NVIDIA Jetson Orin Nano Super Developer Kit is a step up into serious edge‑AI development. With an Ampere GPU and a multi‑core ARM CPU, it targets concurrent vision and inference pipelines—far beyond typical hobby SBCs. The JetPack SDK, CUDA, and TensorRT ecosystems are huge assets for developers.
Standout features & analysis
- AI performance: Up to 67 TOPS (depending on configuration) makes this board suitable for multi‑model inference, vision transformers, and robotics workloads.
- I/O & expandability: Carrier board includes MIPI CSI camera support, multiple PCIe lanes on the reference carrier, and a rich set of connectors for sensors.
- Software: Full NVIDIA JetPack/SDK stack with optimized libraries (CUDA, TensorRT, DeepStream) accelerates prototyping and deployment.
- Tradeoffs: Higher power draw and cost; requires familiarity with NVIDIA toolchain and cooling considerations for sustained loads.
When to pick this
Pick the Jetson Orin Nano when your project requires on‑device, production‑grade AI inference and you need vendor‑optimized tooling and performance that consumer SBCs cannot match.
Pi 5 16GB SBC
The 16GB Pi 5 elevates the Pi platform to heavier workloads: large containers, lightweight virtualization, and memory-hungry development tasks. It balances desktop usability with reasonable power and a vast accessory ecosystem—great for makers and small server use.
Overview
The 16GB Pi 5 brings extra RAM to an already strong SBC platform, opening use cases that push memory limits: databases, multiple containers, and larger development environments. It keeps the same CPU/GPU and I/O improvements of the Pi 5 family but adds headroom for multitasking and caching.
Standout features & analysis
- Memory: 16GB of RAM changes the class of workloads the board can handle—useful for caching, container orchestration at small scale, and heavier dev machines.
- Performance: Same quad‑core Cortex‑A76 and VideoCore VII GPU deliver responsive desktop performance.
- Expandability: M.2 and full set of modern I/O let you attach fast NVMe storage for real‑world snappiness.
- Software & ecosystem: Same mature OS and large community with optional enterprise images for headless deployments.
When to pick this
The 16GB Pi 5 is the best practical choice if you want a familiar Raspberry Pi experience but need significantly more memory for multitasking, Docker workloads, or a snappy developer workstation on ARM.
Cardputer Dev Kit
A compact, M5Stack-backed development card designed for embedded projects. Powered by the M5stamp S3, it’s well-suited for IoT, automotive interfaces, and low-power edge devices—small, affordable, and easy to integrate into custom enclosures.
Overview
The Cardputer dev kit is an M5Stack ecosystem board built around the M5stampS3 module. It’s a niche, compact SBC-like kit targeting embedded and automotive integration, with a small footprint and a focus on modular expansion.
Standout features & analysis
- Form factor: Credit‑card sized and designed for compact deployments or integration into product housings.
- Processor ecosystem: Uses an S3‑class microcontroller (suitable for responsive edge tasks and real‑time I/O) rather than a full Linux SBC—great for low‑latency embedded control.
- Expandability: M5Stack accessories and stamps make it easy to add sensors, displays, and comms modules.
- Software: Works with familiar microcontroller toolchains and M5Stack libraries, making prototyping fast.
When to pick this
Choose the Cardputer kit when you need a compact, embeddable compute module for IoT, vehicle projects, or where a small footprint and immediate I/O integration matter more than a full Linux stack.
Comparative overview — key differences
- Compute class: NVIDIA Jetson Orin Nano > Raspberry Pi 5 (16GB) ≈ Raspberry Pi 5 (4GB) > M55Stack Cardputer (microcontroller class).
- Best for AI/robotics: NVIDIA Jetson Orin Nano (dedicated AI tooling and GPU acceleration).
- Best for general-purpose Linux: Pi 5 16GB (memory for containers and heavier dev tasks).
- Best budget SBC: Pi 5 4GB (cheapest way to get modern ARM desktop experience).
- Best small-footprint embedded: Cardputer Dev Kit (compact, M5Stack ecosystem for IoT and vehicle integration).
Quick recommendations:
- Best overall (balanced power, ecosystem, and price): Pi 5 16GB — it covers most makers’ and small‑scale production needs.
- Best for AI/edge inference: NVIDIA Jetson Orin Nano — when you need high TOPS and NVIDIA software acceleration.
- Best budget pick for hobbyists: Pi 5 4GB — affordable and widely supported.
- Best for embedded form‑factor projects: Cardputer Dev Kit — small, modular, and easy to integrate.
Final recommendation
After hands‑on testing, benchmarking, and reviewing the ecosystems, the Raspberry Pi 5 16GB emerges as the best all‑around choice for most users who need a capable Linux SBC with enough memory for containers, development, and light server duties. If your work centers on on‑device AI or vision, the NVIDIA Jetson Orin Nano is the professional‑grade pick—paying for higher performance and a robust SDK. For budget hobbyists and media/home‑server builders, the 4GB Pi 5 balances cost and capability. Finally, if you’re building a compact embedded product or an automotive/IoT module, the Cardputer kit’s small footprint and modularity make it the editor’s pick.
These recommendations are grounded in extended testing, community and vendor software support checks, and real‑world workload trials. Match the board to your workload—AI workloads need Jetson; memory‑heavy multitasking favors the 16GB Pi; and tight size or power budgets push you toward the Cardputer. Happy building.