The nvcr.io/nvidia/vllm Docker image fails to load the Qwen3-Next-80B-A3B-Instruct-FP8 model on a DGX Spark machine. Installing vLLM from the GitHub repository results in an AssertionError: VLLM_USE_PRECOMPILED is only supported for CUDA builds. (zh) qichen@spark-2b79:~/zh/vllm$ VLLM_USE_PRECOMPILE…

As far as I can tell, the official vLLM does not support the DGX Spark. I’ve made an issue requesting this to be added. [Feature]: DGX Spark sm121a support opened 01:34PM - 05 Nov 25 UTC (UTC) [image] …

Hi, please check out our playbook on how to run vLLM on Spark [image] vLLM for Inference | DGX Spark Install and use vLLM on DGX Spark

This container is outdated and can’t run Qwen3-Next model that OP wants to run. Better to follow the other thread on compiling vllm from source.

By the way, I was able to run nvidia/Nemotron-Nano-12B-v2-VL-BF16 on the spark using vLLM

I have already referred to this tutorial and this container, but they cannot run the new model architecture. Both this container and the sglang container (lmsysorg/sglang:spark) encounter the issue of the Triton kernel not supporting models with fp8e4nv precision.

Hello, I’d like to ask: Are you using the Docker vllm image or building from source code?

Did you only have to build the VLLM from source or Pytorch with CUDA, also because it seems like aarm64 compatible pytorch isnt available.

I'd like to learn how to use the latest vLLM on DGX Spark

Accelerated Computing DGX Spark / GB10 User Forum DGX Spark / GB10

raphael.amorim November 5, 2025, 2:37pm 2

Please check Run VLLM in Spark - #21 by johnny_nv

1 Like

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I'd like to learn how to use the latest vLLM on DGX Spark

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