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nixie-tubes
This has been amazingly helpful for managing my DGX Spark! Thank you for all your time and effort into this project!
redrove
Been running this on a few Asus GX10 machines with k3s on top, it’s been great. I’m running the new deepseek.

Thank you for your work!

neobrain
Just curious, has suspend (to RAM) been working for you?

For me the nvidia driver just keeps waking up the system instantly - but my setup is deviating from the upstream flake in a few ways, so I'm just wondering if it's worth setting up the system from scratch if it's working for other people.

Other than that, can fully second that the flake is working great. Only gotcha is that CUDA-enabled packages (including Firefox) require using the flox binary cache unless you want to compile them from source, but then the package versions can lag behind a bit (and debugging nix cache issues is surprisingly difficult).

thenobsta
This is incredible. I have a Jetson lying around and will try to it out on this. I use it to play with vision models, not LLMs, and have been wanting a better way to manage the machine.
haunter
Thanks for sharing, saving this for when I get a DGX Spark
hamandcheese
Slightly off topic, but Claude Code (and likely other models/harnesses) are incredibly effective at Nix. It can trivially self-verify, without side effects, which is a perfect match for an LLM.

If you've ever been put off by the difficulty of the language, it's worth checking it out again with AI assistance.

glaslong
This. One of the surprising delights of coding models has been trivially reworking my homelab into proxmox and nixos. It's a very good testable, repeatable flow for LLMs.
mkagenius
There is also a microvm.nix project which helped us support sandboxes with firecracker. So, whole ai workflow pipeline can now be nixos.