I built an open-source Linux-capable single-board computer with DDR3

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I've made an ARM based single-board computer that runs Android and Linux, and has the same size as the Raspberry Pi 3! Why? I was bored during my 2-week high-school vacation and wanted to improve my skills, while adding a bit to the open-source community :P These were the specs I ended up with: - H3 SoC - Quad-Core Cortex-A7 ARM CPU @ 1.3GHz - Mali400 MP2 GPU @ 600MHz - 512MiB of DDR3 RAM (Can be upgraded to 1GiB) - WiFi, Bluetooth & Ethernet PHY - HDMI display port - 1080p resolution - 5x USB Slots: 2x USB-A, 1x USB-C Host, 1x USB-C Host & OTG, 1x USB-C PD for power (Negotiating up to 25W. No power socket, yay!) - 32 GB of eMMC 5.1 storage (Optional) - 3.5mm audio jack - SD Card slot - Lots of GPIO I've picked the H3 CPU mainly for its low cost yet powerful capabilities, and it's pretty well supported by the Linux kernel. Plus, I couldn't find any open-source designs with this chip, so I decided to contribute a bit and fill the gap. A 4-layer PCB was used for its lower price and to make the project more challenging, but if these boards are to be mass-produced, I'd bump it up to 6 and use a solid ground plane as the bottom layer's reference plane. The DDR3 and CPU fanout was truly a challenge in a 4-layer board. The PCB was designed in KiCAD and open-source on the Github repo with all the custom symbols and footprints ( https://github.com/cheyao/icepi-sbc ). You can also check it out online with kicanvas: https://kicanvas.org/?github=https%3A%2F%2Fgithub.com%2Fchey... At large quantities, the price can probably reach less than 20$! (exc. taxes, tariffs and other costs) It has been a wild journey, even making me learn how to use crypto as I needed to pay someone to download some "confidential" files from a baidu drive... Read about more details on Github! Everything is open-source under the Solderpad license, aka do what you want: sell it, build it, modify it! :-)

Visit product View on Hacker NewsDec 24, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: computer, single, open · Missing: mac, agents, macos

85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

83%83% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

83%83% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: plus, host · Missing: platform, intuitive, reviews

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: crypto, audio · Missing: web3, chat, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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