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.
Absolutely. Running NixOS is a wonderful experience for this reason. NixOS + LLMs make it a breeze to make changes to your system, install and configure new software, and debug issues. Having every aspect of your system defined in a git repo is the perfect fit for agent harnesses.
I'll admit, even with LLMs to help, the Nix language and NixOS did have a rather steep learning curve, because it's quite different from anything I'd experienced before. But after getting the hang of it, I can't imagine going back to a "normal" OS and I'm very happy I put in the time to get over the initial friction.
You can also push deployments to remote systems which is great for servers and headless devices like raspberry pis. I use colmena and deploy-rs on different projects because they have some nice features but you can also do it with bare nix.
I have a repo for kiosk appliances that can build an SD card image for a specific device in a fleet (so no on device configuration is required) but it can also push out updates or changes at runtime. NixOS isn't perfect for embedded devices yet but works well for cases like this in my experience.
If you are using an Apple Silicon laptop and you want to deploy to an x86-64 Linux box, this can get a bit annoying due needing to deal with cross compilation in nix.
And to add to that, LLMs start with fresh context on each conversation, so they don't have the understanding of your system that human employees do. Nix lets you naturally encode that understanding in code (and in comments), making sure it never drifts from what the state of the system really is.
I never saw much point in Nix, but if you put it like that... now I want to try.
Nix (& NixOS) are very much in the same "as code" as Terraform. -- You put in extra effort now, to save effort later.
This isn't traditionally 'practical'. It's quicker to just install the package, compared to writing a declaration that says to make the package available. (And for ops, Docker images won out in terms of practicality).
Nix also quite a steep learning curve.. I expect a beginner just wants to learn how to write a package in Nix, and not learn about 'derivations', 'instantiation', etc.
Interesting to see LLM coding agents adjust that trade-off: significantly reducing the cost to "write something in Nix", so the benefits become much cheaper.
I got curious one Saturday and ported our monorepo to use Nix for build and test and release. It was a very pleasant process. I had to put aside to tackle more pressing things but I'm all in on using Nix in that capacity.
I set up my homelab server running NixOS entirely using Claude and what would have likely taken me months (if not years) doing it the old fashioned way, got reduced to a few hours of back and forth iteration.
Same for Bazel. It has historically been a very difficult to understand/adopt/rollout tool for a lot of engineering orgs but is going swimmingly for the organization I currently work for.
Agreed, Claude has helped a lot with this project, and being able to iterate without side effects for system configuration changes is really a game changer for agents.
i also used nixos as the base, but i went a little overboard with it, this is 7.1.2 supporting all devices and a custom driver that fixes the UMA page leak issues, and the wallpapers are all kernels at or above parity with what you can get out of the box.
i'm not quite ready to OSS the whole thing, it's got a few rough edges, but if anyone wants to alpha test, caveat emptor and it's yours.
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.
If you've ever been put off by the difficulty of the language, it's worth checking it out again with AI assistance.
I'll admit, even with LLMs to help, the Nix language and NixOS did have a rather steep learning curve, because it's quite different from anything I'd experienced before. But after getting the hang of it, I can't imagine going back to a "normal" OS and I'm very happy I put in the time to get over the initial friction.
I have a repo for kiosk appliances that can build an SD card image for a specific device in a fleet (so no on device configuration is required) but it can also push out updates or changes at runtime. NixOS isn't perfect for embedded devices yet but works well for cases like this in my experience.
I never saw much point in Nix, but if you put it like that... now I want to try.
This isn't traditionally 'practical'. It's quicker to just install the package, compared to writing a declaration that says to make the package available. (And for ops, Docker images won out in terms of practicality).
Nix also quite a steep learning curve.. I expect a beginner just wants to learn how to write a package in Nix, and not learn about 'derivations', 'instantiation', etc.
Interesting to see LLM coding agents adjust that trade-off: significantly reducing the cost to "write something in Nix", so the benefits become much cheaper.
Thank you for your work!
I’ve been running a custom VLLM image with b12x as well as nvfp4_ds_mla.
I would say it’s quite fantastic in day to day, I use it mostly in Hermes and sometimes for coding.
I have qwen 3.6 27b on an rtx 6000 pro as well so I use that as a workhorse in pi with DS as a reviewer/planner.
[0] https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731
Edit: I think you may have misread my post. k3s is NOT kimi k3, and I did mention I was running deepseek.
I have to do like, low paying web dev to fund it, so I can't promise timelines, but it's coming and it will be free to anyone and fast as fuck.
I estimate about 20 bucks an hour at current spot rates in the hundreds if not thousands of tokens per second.
i'm not quite ready to OSS the whole thing, it's got a few rough edges, but if anyone wants to alpha test, caveat emptor and it's yours.
https://www.youtube.com/shorts/mCUZ9XHIogw
https://youtu.be/WXcElxvSevM?si=HHbnzSNddIcPGCll
If anyone is also interested on Nix/CUDA/Capital Markets/Flox, we recently did another case study in the space - https://flox.dev/blog/deploying-hardened-flox-nvidia-cuda-st...