NVIDIA details edge AI workflow for DGX Spark and TensorRT Edge-LLM

NVIDIA said developers can now prototype and serve edge AI models on DGX Spark with a few commands, using its TensorRT Edge-LLM runtime to prepare and run Nemotron-3.5 Lightning for embedded workloads. The company paired the tutorial with benchmark data showing faster token generation when DSpark speculative decoding is enabled, while keeping time to first token broadly unchanged. In a blog post published on 30 October 2026, NVIDIA said DGX Spark is available in a 64GB configuration and can be used to develop agents and physical AI applications that must operate within tight memory, power and latency budgets. The company said TensorRT Edge-LLM is a lightweight C++ inference runtime intended for embedded deployments and is designed to carry the same inference framework from Spark to platforms including Jetson Thor, DRIVE…

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