OwO what's this?
This is my new Raxda Rock 5T
And it runs GNU Guix of course!
Honestly, I'm really suprised by how well and smooth my transition from x86_64 to arm64 went, everything pretty much just works.
Huge thanks to Collabora for their efforts on upstreaming RK3588 and these boards specifically!
Literally no one: –
Me: how about having some unnecessary #BGA #soldering practice in the shape of upgrading #RAM on a #Radxa 4B Plus from 2GB to 4GB? 🤣
Well that did not go as planned.
I used Samsung K4F6E3S4HMMGCJ 2GB RAM chips from #RaspberryPi 4B. With those Radxa would power on, but won't boot and won't go into recovery mode. Only Maskrom works but I wasn't able even to flash a firmware.
Originally it has two HYNIX H9HCNNN8KUMLHR-NME chips - I wonder what makes those different... 🤔
CIX ClawCore Armv9.2 CPU family targets OpenClaw deployments
OpenClaw was just introduced a few months ago, but we've already seen several low-footprint implementations, and some companies even ship mini PCs preloaded with OpenClaw. But today, I was just informed that CIX had gone further, and introduced the ClawCore Armv9.2 CPU family specifically designed/optimized for OpenClaw. The family will be comprised of three main SKUs: ClawCore-P (勁螯芯 "Powerful Claw") - High-performance model with 12-core CPU @ 3.2GHz, Immortalis-G720 GPU, 45 TOPS AI compute, and support for up to 64GB LPDDR5 RAM. Aimed at high-parallelism, large-capacity scenarios. Shipping starts now in March 2026. ClawCore-A (智螯芯 "AI/Smart Claw") - Octa-core CPU @ 3.0GHz, 80 TOPS AI compute (expandable to 200 TOPS via PCIe AI card), up to 64GB LPDDR5. It's designed for 24/7 use, supports full-chain ECC, hardware security (encryption/key management), and enables up to 50% reduction in model token costs via local inference. In practise, 80 to 90% of requests
This Tiny Board Can Replace Your #RaspberryPi 5
#Radxa Cubie A7Z is all looked at in detail.
👉Watch the full video : https://youtu.be/1nyaeCO8pH0
Radxa AICore DX-M1M M.2 2242 low-power AI module delivers 25 TOPS of edge AI performance for just 3W of power
Radxa AICore DX-M1M is a compact, low-power M.2 edge AI acceleration module built around the DeepX DX-M1M neural processing unit (NPU) and delivers up to 25 TOPS (INT8) of AI performance while consuming only 3W of power. Designed for industrial robot arms, autonomous mobile robots (ARM), edge servers, drones, and AIoT devices, the module delivers high-performance AI and ML capabilities without blowing the power budget. It relies on a PCIe Gen3 x2 interface and works with both x86 and Arm systems, including the Raspberry Pi 5 and Radxa ROCK SBCs. AICore DX-M1M specifications: AI Accelerator – DeepX DX-M1M neural processing unit (NPU) with up to 25 TOPS AI System Memory – 1GB LPDDR4X @ 4266 MT/s (on-chip, supports up to 8GB according to DeepX) Storage – 1Gbit QSPI NAND / NOR flash Host Interface - PCIe Gen 3.0 x4 (supports Gen 1/2/3 and x1/x2) via M.2 M + B Key connector
AICore DX-M1M Module Provides 25 TOPS Edge AI Acceleration in M.2 Form Factor
Productive evening at @metalab :) managed to get the first iteration of the top plate for my #Cyberdeck project sorted.
The SBC fits nicely, now I have to see how I can get along with the keyboard layout. Gonna grab some Kailh low profile switches for this build.
And I also discovered a cool way of cloning your #Radxa setup into an image using their ready made script.
Works really cool and pretty fast - maybe due to the fact it's running on an eMMC instead of a micro SD card.
An image of a 32GB eMMC ended up as a
7.4GB uncompressed image, which then can go down to like 3-4 GB archived. Sweet.
The script is here btw:
https://github.com/radxa/backup-sh
#radxa #radxarock #radxarockpi #radxarockpi4bplus #rockpi #rockpi4bplus #sbc #linux
Far from perfect, but #ChatGPT can be helpful faster than #Radxa support.
I got some Radxa Rock 4B+ boards with AW‑NB197SM WiFi module and turns out it was some custom batch or smth.
So they removed support for this module in Radxa OS r4 and onwards, though it works on r3.
Also WiFi works great on #DietPi and #Armbian, so not a hardware fault.
After fiddling for quite a while ChatGPT made me a shell script that fixes - feel free to use it: https://github.com/in-sympathy/radxa_rock_4bplus_wifi_fix
Alexei Edelweiss
in_sympathy
cnx-software.com
Smart Home Circle
LinuxGizmos.com
boxxbeidl
Ben Zucker 🍰