# Show HN：NixOS-DGX-Spark -- 在 DGX Spark 上运行 Nix 和 NixOS

- 来源：Hacker News 热门（buzzing.cc 中文翻译）
- 作者：graham33
- 发布时间：2026-08-03 11:20
- AIHOT 分数：60
- AIHOT 链接：https://aihot.virxact.com/items/cmsco9sj00g4rroeul8757vf1
- 原文链接：https://github.com/graham33/nixos-dgx-spark

## AI 摘要

NixOS-DGX-Spark 项目让用户在 NVIDIA DGX Spark 及 Asus Ascent GX10 上通过 Nix 或完整安装 NixOS 使用 DGX Spark playbooks，提供 USB 镜像和 NixOS 模块。

## 正文

Nix and NixOS on the DGX Spark

Try DGX Spark playbooks using Nix on DGX OS, or install NixOS on your DGX Spark for the full Nix experience. The repository provides USB images and a NixOS module with settings for DGX Spark systems.

This works on the NVIDIA DGX Spark itself and also on the Asus Ascent GX10.

See my 5 minute lightning talk from Planet Nix for an intro: https://youtu.be/AvK_gi_snJE?si=MPKv3iiuS9B5elIE

Using Nix on DGX OS (Ubuntu)

You can use the dev shells and playbooks in this repo on NVIDIA DGX OS (Ubuntu) without installing NixOS.

Setup

Install Nix using the official installer:

sh <(curl -L https://nixos.org/nix/install) --daemon

Alternatively, you can use the Determinate Nix Installer:

curl --proto '=https' --tlsv1.2 -sSf -L https://install.determinate.systems/nix | sh -s -- install

Enable flakes and nix-command by adding to /etc/nix/nix.conf:

experimental-features = nix-command flakes

Enable the graham33 Cachix cache — see Caching below.

Running on Non-NixOS (e.g. DGX OS)

On non-NixOS systems, Nix-built CUDA applications need nix-gl-host to find the host GPU drivers. The playbook devshells handle this automatically — container-based playbooks don't need it, and Nix-native playbooks wrap their commands with nixglhost so no manual intervention is required.

For other devshells (e.g. cuda), nixglhost is available and can be used to prefix commands manually:

nix develop .#cuda nixglhost deviceQuery

NixOS on the DGX Spark

[!WARNING] Only DGX OS can boot from the factory firmware. You need to update firmware before installing NixOS.

USB Boot Image

Build the USB image:

nix build .#usb-image sudo dd if=$(echo result/iso/*.iso) of=/dev/your_usb_disk_device bs=1M status=progress sync

The image includes two kernel options, selectable from the GRUB boot menu:

NixOS (default) - NVIDIA's specialised kernel for DGX Spark with full GPU support and working Ethernet

NixOS (standard-kernel) - Standard NixOS 6.17 kernel (Ethernet has problems)

Booting

Disable Secure Boot in the DGX Spark BIOS and boot from the USB drive.

You can then follow the installation instructions in the NixOS manual: https://nixos.org/manual/nixos/stable/#sec-installation-manual

Using the DGX Spark module

This module provides configurable DGX Spark hardware support with options for kernel selection.

Module configuration options

hardware.dgx-spark = { enable = true; # Enable DGX Spark hardware support useNvidiaKernel = true; # Use NVIDIA kernel (default: true) };

Using NVIDIA kernel

hardware.dgx-spark.enable = true; # Uses NVIDIA kernel by default

The NVIDIA kernel is a custom build optimised for NVIDIA DGX Spark systems. The kernel configuration is generated from NVIDIA's Debian annotations and compared with NixOS defaults to produce a minimal, maintainable configuration.

The module also enables the DGX Dashboard web interface at http://localhost:11000, providing GPU telemetry and system monitoring.

Using standard NixOS kernel (has some issues with networking)

hardware.dgx-spark = { enable = true; useNvidiaKernel = false; # Use standard NixOS 6.17 kernel };

Kernel configuration management

The kernel configuration is generated from NVIDIA's Debian annotations and stored in kernel-configs/nvidia-dgx-spark-<version>.nix. This terse configuration only contains options that differ from NixOS defaults, reducing verbosity by ~82%.

To regenerate the kernel configuration:

nix run .#generate-kernel-config

This:

Fetches the NVIDIA kernel source from GitHub

Builds the NixOS baseline kernel config

Compares NVIDIA's annotations with NixOS defaults

Generates a terse config file with only the differences

Regeneration is needed when:

NVIDIA kernel version changes (update kernel-configs/nvidia-kernel-source.nix)

NixOS common-config changes (nixpkgs update)

You can also use a local kernel source for development:

nix run .#generate-kernel-config -- --kernel-source /path/to/NV-Kernels

Importing in other projects

Other projects can import this flake and use the DGX Spark module:

{ inputs.dgx-spark.url = "github:graham33/nixos-dgx-spark";

outputs = { nixpkgs, dgx-spark, ... }: { nixosConfigurations.mySystem = nixpkgs.lib.nixosSystem { modules = [ dgx-spark.nixosModules.dgx-spark { # Enable DGX Spark support hardware.dgx-spark.enable = true; # Optionally use standard kernel: useNvidiaKernel = false; } # your other modules ]; }; }; }

Quick start NixOS template

For a complete NixOS configuration template specifically designed for DGX Spark systems, you can use the template:

# Create a new directory for your NixOS configuration mkdir my-dgx-spark-config cd my-dgx-spark-config

# Initialise with the DGX Spark template nix flake init -t github:graham33/nixos-dgx-spark#dgx-spark

This creates a complete NixOS configuration with:

flake.nix - Flake configuration that imports the DGX Spark module

configuration.nix - Main system configuration optimised for DGX Spark

hardware-configuration.nix - Hardware configuration template

Customising the template

After initialising the template, you need to:

Generate hardware configuration and update template:

# Generate hardware config to a temporary location to get the real UUIDs sudo nixos-generate-config --root /mnt --dir /tmp/nixos-config

# Copy the real hardware UUIDs and settings from the generated file # Replace the placeholder UUIDs in hardware-configuration.nix with actual # values from /tmp/nixos-config/hardware-configuration.nix

Edit configuration.nix to customise:

Change hostname from dgx-spark to your preferred name

Update username from nixos to your preferred username

Add your SSH public keys for remote access

Set your timezone and locale preferences

Add any additional packages you need

Deploy the configuration to /etc/nixos:

# Copy your configuration to /etc/nixos sudo cp -r . /etc/nixos/

# Apply the configuration sudo nixos-rebuild switch --flake /etc/nixos#dgx-spark

Firmware updates

As noted in #32, only DGX OS can boot from the factory firmware. If NixOS can't boot from the factory firmware, you need to update firmware from DGX OS first.

The module enables fwupd for firmware updates. NVIDIA publishes DGX Spark firmware to the Linux Vendor Firmware Service (LVFS). To check for available updates:

fwupdmgr get-updates

To install available updates:

fwupdmgr update

Playbooks

This repository includes devshells for NVIDIA DGX Spark playbooks from https://build.nvidia.com/spark:

Playbook Description Type Tested on NixOS Tested on DGX OS

ComfyUI Run ComfyUI with Stable Diffusion 1.5 for AI image generation 🟢 Full Nix² ✅ ✅

Connect Two Sparks Connect two DGX Spark systems via QSFP 🟢 Full Nix² ✅ ☑️¹

DGX Dashboard Set up DGX Dashboard for system monitoring 🟢 Full Nix² ✅ ☑️¹

FLUX.1 Dreambooth FLUX.1 Dreambooth LoRA fine-tuning 🟠 Container³ ✅ ✅

Multi-Agent Chatbot Build and deploy a multi-agent chatbot 🟠 Container³ ✅ ✅

Multi-modal Inference Run multi-modal inference with vision-language models 🟠 Container³ ✅ ✅

NCCL for Two Sparks Multi-node GPU communication with NCCL 🟢 Full Nix² ✅ ☑️¹

NVFP4 FP4 model quantisation with TensorRT Model Optimizer 🟠 Container³ ✅

OpenShell Secure long-running AI agents with OpenShell sandbox 🔵 Nix + Container⁴ ✅

PyTorch Fine-tuning Container Fine-tune models with PyTorch on DGX Spark 🟠 Container³ ✅

PyTorch Fine-tuning Nix Fine-tune models with PyTorch (Nix native, no containers) 🟢 Full Nix² ✅ ✅

Speculative Decoding Speculative decoding for faster inference 🟠 Container³ ✅

TRT-LLM TensorRT-LLM for optimised inference 🟠 Container³ ✅ ✅

vLLM Container Run vLLM inference server with Qwen2.5-Math-1.5B-Instruct model 🟠 Container³ ✅ ✅

vLLM Nix Run vLLM inference server natively (Nix native, no containers) 🟢 Full Nix² ✅ ✅

¹ Pre-installed on DGX OS ² Full Nix: Fully reproducible — all dependencies installed via Nix ³ Container: Nix provides podman, but containers are pulled/built at runtime ⁴ Nix + Container: CLI tools packaged via Nix, but containers are managed by the tool at runtime

Caching

Flox CUDA binary cache (recommended)

Flox distributes pre-built CUDA packages for aarch64-linux with NVIDIA's permission. This includes cudatoolkit, nccl, cuDNN, PyTorch, and other CUDA dependencies — dramatically reducing build times.

If you use the DGX Spark NixOS module, the Flox cache is configured automatically as a substituter.

For standalone Nix (e.g. on DGX OS), add to /etc/nix/nix.conf:

extra-substituters = https://cache.flox.dev extra-trusted-public-keys = flox-cache-public-1:7F4OyH7ZCnFhcze3fJdfyXYLQw/aV7GEed86nQ7IsOs=

graham33 Cachix cache

For packages built by this repo (e.g. dgx-dashboard, openshell):

cachix use graham33

Install cachix first if needed: https://docs.cachix.org/installation

See https://nixos.wiki/wiki/CUDA for general CUDA caching details.

nixos-anywhere (Experimental)

[!WARNING] This has not been tested yet. Use at your own risk.

You can install NixOS on a DGX Spark remotely using nixos-anywhere. This is useful for headless setups where you have SSH access to the target machine.

nix run github:nix-community/nixos-anywhere -- --flake github:graham33/nixos-dgx-spark#dgx-spark root@<ip>

This partitions the NVMe disk and installs NixOS with the DGX Spark module enabled. You may want to customise nixos-anywhere/configuration.nix (e.g. to add SSH keys or change the hostname) — clone the repo and point --flake at your local checkout instead.

To test the disk configuration in a VM without installing:

nix run github:nix-community/nixos-anywhere -- --flake .#dgx-spark --vm-test

See the nixos-anywhere documentation for full details and requirements.

License

MIT License - see LICENSE for details.