From RTX to Spark: NVIDIA Accelerates Gemma 4 for Local Agentic AI

Nvidia AI Blog / 4/3/2026

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Google and NVIDIA collaborated to optimize the Gemma 4 open-model family for NVIDIA GPUs, targeting efficient local, real-time AI use across devices.
Gemma 4 is presented as a set of compact, fast, and broadly capable models (E2B, E4B, 26B, 31B) meant to run efficiently from edge hardware to data-center GPU systems.
The optimization effort is aimed at multiple NVIDIA environments, including RTX-powered PCs and workstations as well as DGX Spark and Jetson Orin Nano edge modules.
The article frames the broader trend as shifting value from cloud-only inference toward on-device agentic AI that can act on local context.
Performance portability across deployment tiers is positioned as the key enabler for widespread adoption of open, local AI models.

Open models are driving a new wave of on-device AI, extending innovation beyond the cloud to everyday devices. As these models advance, their value increasingly depends on access to local, real-time context that can turn meaningful insights into action. Designed for this shift, Google’s latest additions to the Gemma 4 family introduce a class of small, fast and omni-capable models built for efficient local execution across a wide range […]

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