I love that OrangePi is making good hardware, but after my experience with the OrangePi 5 Max, I won’t be buying more hardware from them again. The device is largely useless due to a lack of software support. This also happened with the MangoPi MQ-Pro. I’ll just stick with RPi. I may not get as much hardware for the money, but the software support is fantastic.

At some point SBCs that require a custom linux image will become unacceptable, right?

Right?

Looks like the SoC (CIX P1) has Cortex-A720/A520 cores which are Armv9.2, nice.

I've still been on the hunt for a cheap Arm board with a Armv8.3+ or Arvm9.0+ SoC for OSDev stuff, but it's hard to find them in hobbyist price range (this board included, $700-900 USD from what I see).

The NVIDIA Jetson Orin Nanos looked good but unfortunately SWD/JTAG is disabled unless you pay for the $2k model...

Something in me wants to buy every SBC and/or microcontroller that is advertised to me.

One or two USB-C 3.2 Gen2 ports are all that's required - can then plug in a hub or dock. eg: https://us.ugreen.com/collections/usb-hub?sort_by=price-desc...

Can also plug in a power bank. https://us.ugreen.com/collections/power-bank?sort_by=price-d...

The advantage is that if the machine breaks or is upgraded, the dock and pb can be retained. Would also distribute the price.

The dock and pb can also be kept away to lower heat to avoid a fan in the housing, ideally.

Better hardware should end up leading to better software - its main problem right now.

This 10-in-1 dock even has an SSD enclosure for $80 https://us.ugreen.com/products/ugreen-10-in-1-usb-c-hub-ssd (no affiliation) (no drivers required)

I'd have another dock/power/screen combo for traveling and portable use.

Unfortunately only available atm for extremely high prices. I'd like to pick some up to create a ceph cluster (with 1x 18tb hdd osd per node in an 8 node cluster with 4+2 erasure coding)

Disappointing on the NPU. I have found it's a point where industry wide improvement is necessary. People talk tokens/sec, model sizes, what formats are supported... But I rarely see an objective accuracy comparison. I repeatedly see that AI models are resilient to errors and reduced precision which is what allows the 1 bit quantization and whatnot.

But at a certain point I guess it just breaks? And they need an objective "I gave these tokens, I got out those tokens". But I guess that would need an objective gold standard ground truth that's maybe hard to come by.