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On October 19, 2026, the n8n blog published a tutorial on how to deploy a complete model stack locally on a single NVIDIA DGX Spark, enabling n8n workflows to handle transcription, OCR, document Q&A, and image generation without calling cloud APIs. The tutorial states that the entire stack exposes an OpenAI-compatible endpoint through LiteLLM, with the main model being the NVFP4 version of Qwen3.6-35B-A3B, achieving a generation speed of 120 tokens/s for a single user and 359 tokens/s combined for eight users. The author's hands-on testing found that image generation reduces conversation speed to about one-third, and recommends that small teams queue image tasks or schedule them outside working hours. Currently, this content has only the n8n blog as its source.
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Oct 19
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How to run n8n AI workflows on NVIDIA DGX Spark without calling cloud APIs
n8n Blog published a tutorial on how to deploy a complete model stack locally on a single NVIDIA DGX Spark, enabling n8n workflows to perform transcription, OCR, document Q&A, and image generation without calling cloud APIs. The entire stack exposes an OpenAI-compatible endpoint through LiteLLM; the main model is the NVFP4 version of Qwen3.6-35B-A3B, with a single-user generation speed of 120 tokens/s and an aggregate of 359 tokens/s across eight users. The author's testing found that image generation reduces chat speed to about one-third, and recommends that small teams queue image tasks or schedule them outside working hours.