NVIDIA Nemotron 3.5 Lightning and NeMo Switchyard Deliver Faster, Smarter, More Efficient Agentic AI
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- Kari Briski
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- Kari Briski
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- mixture-of-experts — A model built from many specialist sub-networks where only a few activate per token, giving big-model capability at small-model running cost.
- multi-agent — Using several AI agents on one problem — splitting work in parallel, checking each other, or filling different roles like planner and reviewer.
- AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
The primary source for a model release and a routing library that together target the execution layer of multi-model systems. Engineers building always-on agents can act on both today.
“The model delivers up to 4x faster output speed, leading to 30% faster agentic task completion compared with other models in its class.”
Kari Briski
“Internal benchmarks show that NeMo Switchyard maintains frontier-level accuracy while reducing task completion cost to nearly one-third of Opus 4.8 alone.”
Kari Briski
“If customers rely on one default model, they might either overspend or lose quality; if they manage routing manually, it becomes integration work that can slow down a deployment.”
Kari Briski
“With NeMo Switchyard, achieved 74% lower cost in 145 multi-turn Deep Agents tasks by routing only 7% of calls to a frontier model, at a 6% accuracy tradeoff.”
Kari Briski
“Used NeMo Switchyard to match a frontier model’s performance while cutting costs by 58% and runtime by 33% in Ramp SWE-Bench”
Kari Briski
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