The Raspberry Pi CM4-powered ALPON X4 was introduced last April, but SixFab has now upped the ante with the ALPON X5 Edge AI computer based on a Raspberry Pi CM5, and equipped with a 25 TOPS DeepX DX-M1 AI accelerator capable of competing against NVIDIA Jetson solutions.
The fanless mini PC still offers dual Ethernet, WiFi 5, Bluetooth 5.0, and global 4G LTE connectivity, an HDMI video output, a GPIO RJ11 jack, and USB PD and 9V-30V DC power options. The new model also adds a camera input connector and features two USB 3.0 ports instead of USB 2.0 ones.
ALPON X5 specifications (“reverse-engineered”, because SixFab could not bother to list the specs…):
- SoM – Raspberry Pi CM5
- AI Accelerator – M.2 module based on DeepX DX-M1 25 TOPS (200 eTOPS) AI accelerator
- Storage – M.2 NVMe SSD support
- Video Output – HDMI output
- Camera – Micro HDMI (TBD) camera input connector
- Connectivity
- Gigabit Ethernet RJ45 port
- 10/100Mbps Ethernet RJ45 port
- WiFi 5 and Bluetooth 5.0 on the CM5 module
- Global 4G LTE Cat. 4cellular connectivity with eSIM + GNSS
- 4x external antennas for WiFi, Bluetooth, cellular, and GNSS
- USB – 2x USB 3.0 Type-A ports
- Expansion – RJ11 GPIO port
- Security – TPM 2.0 module
- Misc
- 4x LEDs
- Hardware watchdog
- Power Input
- USB PD Type-C port
- 9 to 30V DC via screw terminal block
- Dimensions – TBD
- Certifications – FCC, CE, RoHS, REACH
SixFab highlights support for select Hugging Face models: SCRFD face detection, VGG16 lane mask, YOLOPose pose detection model, YOLOv5, YOLOv7, and others. They claim that the ALPON X5 is cheaper and easier to use than the NVIDIA Jetson hardware as a ready-to-deploy platform and beginner-friendly software integration, thanks to ALPON Cloud and ALPON Edge. There’s limited information about those right now, but the documentation website should be updated once the systems ship to backers.
We’ve also given a comparison table with the NVIDIA Jetson AGX 32GB, Jetson Orin Nano Super Developer Kit, a system with Hailo-8 AI accelerator, and the ALPON X5. It somehow shows the X5 more or less matching the Jetson Orion AGX 32 performance with the Yolov5s (640×640) at a fraction of the energy, and it’s also quite faster than the computer with a 26 TOPS Hailo-8 M.2 module. There might be a trick here…
Target applications include smart surveillance, healthcare and safety monitoring, autonomous robots and vehicles, and DIY projects.
Instead of launching the ALPON X5 AI mini PC on its own website, SixFab decided to launch it through a crowdfunding campaign on Kickstarter this time around. Rewards start at $499 for a “Secret Perk” (for people notified by email only), while the early bird KS price is $549 with 100 units available and $599 for the regular pledge. Shipping adds $20 to the US and $30 to the rest of the world. Deliveries are scheduled to start by December 2025, if everything goes according to plan.
Jean-Luc started CNX Software in 2010 as a part-time endeavor, before quitting his job as a software engineering manager, and starting to write daily news, and reviews full time later in 2011.
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Interesting!
Article: “but the documentation website should be updated once the systems ship to backers.”
Trust us!
For 500 USD I would expect good-to-perfect documentation before pledging.
Sadly, that’s almost always the case with crowdfunded projects, especially those planned to ship several months after the campaign is over. They focus on having a product that works, and the documentation is being worked on when it’s closer to release.
The best we can do is look at the history of the company with regard to documentation and software support.
Totally fair point—solid docs should come before you hit “pledge.” We hear you.
Good news: thorough documentation is kind of our thing. Check out docs.sixfab.com and you’ll see full, step-by-step guides for every product we’ve ever shipped, including earlier ALPON models called X4.
The X5 AI docs are already drafted and will go live as soon as we lock the SDK—well before units ship. We’ve been onboarding early partners and alpha testers for a while, so everything’s getting battle-tested in real time. “Show, don’t just tell” is how we roll—and we hope our existing docs prove it.