Sep 24, 2026 · 18 min
Open Nemotron models bring AI workflows closer to the workstation
Accelerate AI Workflows with Nemotron
The episode examines how open-weight models, intelligent routing, and local NVIDIA-powered systems could make agentic AI more adaptable and economical.
- 1Nemotron combines open models, datasets, and techniques to help developers build specialized and agentic AI applications.
- 2Nemotron 3.5 Lightning activates 3 billion parameters within a 30-billion-parameter mixture-of-experts model for faster inference.
- 3NeMo Switchyard routes tasks to appropriate models, balancing capability, cost, and local-versus-cloud deployment needs.
Don't miss
Patel explains how NeMo Switchyard can route requests to the right model, replacing indiscriminate multi-model querying with a more economical policy.
The brief
NVIDIA’s Chintan Patel introduces Nemotron as a family of open models, datasets, and techniques aimed at specialized and agentic AI workloads.
The case for open-weight models is strategic as well as technical: researchers can iterate, startups can build, and enterprises can adapt systems to domain-specific needs.
Nemotron 3.5 Lightning uses a mixture-of-experts design with 30 billion total parameters but 3 billion active parameters, targeting faster and more efficient inference.
NeMo Switchyard adds a policy layer that routes each request to an appropriate model instead of querying several models indiscriminately, sharpening the local-versus-cloud tradeoff.
For developers starting on Dell Pro Max systems with NVIDIA hardware, Patel recommends a personal agent or digital chief of staff, while smaller models extend Nemotron toward edge deployments.