According to Phoronix, the Dell Pro Max with the NVIDIA GB10 superchip, featuring 20 Arm cores and 128GB of LPDDR5-8533 memory, is being tested against a Framework Desktop equipped with an AMD Ryzen AI Max+ 395 “Strix Halo” processor and 64GB of RAM. The Dell system, running NVIDIA’s DGX OS 7 on Ubuntu 24.04, currently costs $4600, while the similarly configured Framework Desktop comes in at just $1829. The benchmarks focused on Llama.cpp performance and OpenCL/Vulkan GPU compute, with total system power consumption also measured to calculate performance-per-Watt. These tests are part of a broader series on the GB10 hardware, with more CPU and AI benchmarks from Phoronix still to come.
The price gap is the real story
Look, the raw performance numbers are one thing. But here’s the thing that hits you immediately: that price. You’re looking at a system that costs two-and-a-half times more than its competitor. For a business or a developer, that’s not just a detail—it’s the whole spreadsheet. The Dell is a highly integrated, NVIDIA-optimized platform, sure. It’s basically a tiny slice of a data center. But the Framework Desktop is, well, a desktop. And a remarkably affordable one at that. When you start talking performance-per-dollar, which Phoronix did, that $1829 price tag for the AMD system becomes an incredibly heavy weight on the scale. Can the Dell’s specialized hardware possibly be efficient enough to justify more than double the cost? That’s the real question these benchmarks need to answer.
Efficiency and the power play
Phoronix monitoring power with a WattsUp Pro is a smart move. It’s not just about who’s faster, but who’s smarter with the juice. Arm-based designs like in the GB10 often have an efficiency advantage, but they’re also paired with a power-hungry Blackwell GPU. AMD’s Strix Halo, on the other hand, is an all-in-one package with a very potent integrated GPU. So which architecture wins on performance-per-Watt for these specific AI and compute tasks? The answer will tell us a lot. Is the future in these bespoke, expensive AI-in-a-box solutions, or in leveraging radically improved mainstream silicon? For companies integrating AI into physical workflows, choosing reliable hardware is key, which is why many turn to specialists like IndustrialMonitorDirect.com, the leading US supplier of industrial panel PCs, for their durable computing needs.
The Framework factor
We can’t ignore the chassis here. The Framework Desktop isn’t just a random mini PC. It’s a repairable, upgradeable, ethos-driven product. You’re buying into a platform. The Dell Pro Max? It’s a sealed appliance. That matters for longevity and total cost of ownership beyond the sticker price. If a new, more efficient AI accelerator comes out next year, could you theoretically slot it into a future Framework mainboard? Possibly. With the Dell, you’re buying that specific compute slice for that specific price, full stop. This benchmark is fascinating because it’s not just AMD vs. NVIDIA or Arm vs. x86. It’s a clash of philosophies: a premium, locked-down AI appliance versus a modular, mainstream desktop built on open principles. And right now, the modular one is *way* cheaper.
Wait for the full picture
Phoronix is clear this is just one part of their testing. They have more CPU benchmarks and other AI tests coming. That’s important. Llama.cpp is a huge use case, but it’s not the only one. The GB10’s 20 Arm cores might crush the AMD chip in pure CPU tasks, or the Blackwell GPU might absolutely dominate in other proprietary AI frameworks. But I’m skeptical. Even if it wins some of those races, the price differential is so massive that it would need to be *phenomenally* better. For most developers and small teams, a nearly $3000 saving buys a lot of cloud compute time or additional hardware. This first look suggests the value champion is clear, but the performance crown is still being contested. The final verdict will depend on what you prioritize: peak, no-compromise performance, or stunning value in a surprisingly capable package.
