Since 2009, this website has run on Drupal. Starting with Drupal 6, and progressing through major site upgrades and migrations to 7, 8, 9, and 10, I used the site as a way to dogfood the same CMS (Content Management System) I used in my day job for over a decade.

But as time progressed—especially after completing a grueling upgrade from Drupal 7 to 8—my enthusiasm for maintaining what's now a more enterprise-focused Digital Experience Platform or 'DXP' for a personal blog has waned.

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Last month, the stars aligned for me to bring the Mono Gateway (a 10 Gbps router that YouTuber Tomaž Zaman and his team at Mono built from scratch) on a trip to Phoenix, and test it with one of the most OP network test boxes I've ever seen, at the ServeTheHome HQ.

In this video, Patrick (from STH) and I put Gateway through a real-world torture test using CyPerf:

Mono Gateway

The Gateway is a small (1U/desktop) router with features like a 4-core Arm CPU, 8GB of ECC LPDDR RAM, and decent expansion options for a compact router.

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Dell sent me two of their GB10 mini workstations to test:

In this blog post, I'll cover the base system, just one of the two nodes. Cluster testing is ongoing, and I'll cover things like AI model training and networking more in depth next year, likely with comparisons to the Framework Desktop cluster and Mac Studio cluster I've also been testing.

But many of the same caveats of the DGX Spark (namely, price to performance is not great if you just want to run LLMs on a small desktop) apply to Dell's GB10 box as well.

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If you were 5 microseconds late today, blame it on NIST.

Their facility in Boulder Colorado just had its power cut for multiple days. After a backup generator failed, their main ensemble clock lost track of UTC, or Universal Time Coordinated.

But even if you used the NTP timing servers they run, they were never off by more than 5 microseconds.

5 μs might seem insignificant. But it is significant for scientists and universities who rely on NIST's more specialized timing signals.

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Ever since I got AMD, Intel, and Nvidia graphics cards to run on a Raspberry Pi, I had a nagging question:

What's the point?

The Raspberry Pi only has 1 lane of PCIe Gen 3 bandwidth available for a connection to an eGPU. That's not much. Especially considering a modern desktop has at least one slot with 16 lanes of PCIe Gen 5 bandwidth. That's 8 GT/s versus 512 GT/s. Not a fair fight.

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Apple gave me access to this Mac Studio cluster to test RDMA over Thunderbolt, a new feature in macOS 26.2. The easiest way to test it is with Exo 1.0, an open source private AI clustering tool. RDMA lets the Macs all act like they have one giant pool of RAM, which speeds up things like massive AI models.

The stack of Macs I tested, with 1.5 TB of unified memory, costs just shy of $40,000, and if you're wondering, no I cannot justify spending that much money for this. Apple loaned the Mac Studios for testing. I also have to thank DeskPi for sending over the 4-post mini rack containing the cluster.

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