# NGC

Published articles for NGC.

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## Running the Latest vLLM on the NVIDIA DGX Spark

DevFeed: [Running the Latest vLLM on the NVIDIA DGX Spark](<https://devfeed.tech/articles/running-the-latest-vllm-on-the-nvidia-dgx-spark-10704.md>)

Original publisher: [Read original article](<https://technotim.com/posts/vllm-gb10-docker/>)

Author: Techno Tim

Published: 2026-05-21T13:00:00Z

Content type: tutorial

Language: en

Sources: [Techno Tim](<https://devfeed.tech/sources/techno-tim.md>)

Topics: [vllm](<https://devfeed.tech/topics/vllm.md>), [DGX Spark](<https://devfeed.tech/topics/dgx-spark.md>), [Docker](<https://devfeed.tech/topics/docker.md>), [Dockerfile](<https://devfeed.tech/topics/dockerfile.md>), [GitHub Actions](<https://devfeed.tech/topics/github-actions.md>), [NCCL](<https://devfeed.tech/topics/nccl.md>), [CUDA](<https://devfeed.tech/topics/cuda.md>), [PyTorch](<https://devfeed.tech/topics/pytorch.md>), [GitHub](<https://devfeed.tech/topics/github.md>), [NGC](<https://devfeed.tech/topics/ngc.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [Ubuntu](<https://devfeed.tech/topics/ubuntu.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [cuda](<https://devfeed.tech/tags/cuda.md>), [dgx-spark](<https://devfeed.tech/tags/dgx-spark.md>), [docker](<https://devfeed.tech/tags/docker.md>), [docker-image](<https://devfeed.tech/tags/docker-image.md>), [github](<https://devfeed.tech/tags/github.md>), [github-actions](<https://devfeed.tech/tags/github-actions.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [homelab](<https://devfeed.tech/tags/homelab.md>), [nccl](<https://devfeed.tech/tags/nccl.md>), [ngc](<https://devfeed.tech/tags/ngc.md>), [nvidia-dgx](<https://devfeed.tech/tags/nvidia-dgx.md>), [pytorch](<https://devfeed.tech/tags/pytorch.md>), [self-hosted](<https://devfeed.tech/tags/self-hosted.md>), [ubuntu](<https://devfeed.tech/tags/ubuntu.md>), [vllm](<https://devfeed.tech/tags/vllm.md>)

### AI overview

This tutorial presents a reproducible Docker image pipeline for running current vLLM releases on the NVIDIA DGX Spark's GB10 ARM64 platform. It explains why NVIDIA's NGC images can lag upstream and describes a GitHub Actions build on a self-hosted Spark runner with pinned inputs and generated lockfiles.

### Source excerpt

When I built my local AI cluster on a pair of ASUS Ascent GX10s, the hard part was not serving a model. The hard part was getting a working vLLM image with current components. NVIDIA's official image was already over a month behind by the time I needed it, and waiting on their release schedule was not an option. If you saw that post, you know the GX10 is an ARM64 machine built around NVIDIA's ...