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Run Local AI Agents with Faster Models and Multi-Node Clustering on NVIDIA DGX Spark

NVIDIA Technical Blog·Maitri Taneja·about 6 hours ago
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The rise of autonomous, long-running AI agents has introduced a new class of compute demand, namely tasks that maintain large context windows, spawn concurrent subagents, and iterate continuously without cloud dependency. Security and privacy concerns are also accelerating the shift toward local agents.

Developers, by running autonomous agents on hardware they own with NVIDIA NemoClaw orchestrating execution, can keep sensitive context on-device, retain direct control over what an agent can access and eliminate per-token costs.

NVIDIA DGX Spark is designed to build and run autonomous agents locally. At Computex 2026, NVIDIA is making it significantly easier to get there, introducing a streamlined path from unboxing to running AI agents in minutes (excluding initial model download, which depends on network speed).…

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