Running Crysis and LLMs: My Experience with the NVIDIA DGX Spark Daily Driver
Nvidia DGX Spark as a daily driver
I bought an NVIDIA DGX Spark as a daily driver and found it surprisingly capable for general computing, gaming, and local LLM inference. The compact ARM-based machine runs Ubuntu smoothly, handles AAA titles like Cyberpunk 2077 via Proton, and delivers impressive token speeds for models like Qwen 3.6 thanks to recent software optimizations. While not a dedicated gaming rig, its power efficiency and versatility make it a compelling choice for developers.
It turns out, it can totally run Crysis.
- cogman10
I strongly considered it, but the one thing that scares me away from wanting to do the spark is you basically have to use nvidia's linux (from what I've read) and it doesn't appear the nvidia is interested in upstreaming their kernel changes.
I'm avoiding where possible buying electronics where support is controlled by the manufacturer and not me.
- InTheArena
I have a DGX and a Ryzen AI Max 395 - while I love both of them, there are a few critical things that leave the DGX in use, while the Ryzen "just" is my primary homelab server. The biggest thing is prefil numbers, and the performance impact of higher context sizes. Qwen 27b is a great model, nemotron is decent, gemma is workable. But all of them need reasonable context for reasonable outputs.
Unfortunitly, as others have noted, the DGX OS experience... sucks. My hope is that the RTX Spark (which looks to be the exact same stack, sans the high capacity network interface) will help this get a bit more attention, but nVidia's long long long war with the open source community is not helping. Focusing on mainlining kernel support would go a long way to getting the community to be supportive.
Of course, a massive regression just hit Linux 7+/7.1 plus for ROCm hosts, so it's just rough everywhere.
- MrVitaliy
I do appreciate how Nvidia tries to say close to vanilla with Linux and Android (nvidia shield). Instead of trying to build a shitty moat like Samsung with all their garbage software.
If nvidia ever releases Android smartphone, I'd probably stand in line to get one.
- ciupicri
Somehow related: "The end of my AArch64 [Ampere Altra Q80-30] desktop experiment", https://news.ycombinator.com/item?id=48728599 / https://marcin.juszkiewicz.com.pl/2026/06/26/the-end-of-the-...
- jubilee33
This is an interesting review. I have a Chinese strix halo box that's isnt available in the west (favm faex1) I've been able to do some ok graphical gen, or some decent agentic tasks as a fallback for when some of the APIs are overloaded during business hours, but nothing amazing for sure, and also not both at the same time.
But here's the thing...it cost me 1800usd two months ago....and it's runs x86. I am struggling to see why people pay +2x more for the Arm Nvidia version, despite the slightly higher bandwidth it still does basically the same AI tasks and alot fewer high end general computing tasks...
I like my box but I wouldn't find it useful enough to pay more than I did for it or get more of them and cluster for instance.
Can anyone explain the allure of the Nvidia box, other than brand name?