NVIDIA AI Releases Nemotron 3.5 Lightning: A 30B Open MoE with 3B Active Parameters, and NeMo Switchyard Model Router

AI Releases Nemotron 3.5 Lightning: A 30B Open MoE with 3B Active Parameters, and NeMo Switchyard Model Router">

NVIDIA introduced open technologies for building always-on AI agents from systems of specialized models. Two artifacts shipped together. Nemotron 3.5 Lightning is a lightweight, customizable open model built for high-volume agentic tasks, and NeMo Switchyard is an open source routing library that directs each step of an agent workflow to the most capable and efficient model available. The problem both address is structural: long-running agents spend most of their time on tool calls, result validation, and subagent delegation, and sending every one of those steps to a frontier reasoning model adds cost and latency. Lightning is a 30B mixture-of-experts model with 3B active parameters, built on a hybrid Mamba-2 + MoE + Attention architecture with a 1M-token context window. NVIDIA reports up to 4x faster output speed than similar-sized models, and 30% faster completion of 10,000 PinchBench tasks than Qwen3.6 35B at comparable accuracy. Many industry players like CrowdStrike, Harvey, CodeRabbit, Fastino Labs, and Lila Sciences are already customizing it for cybersecurity, legal, coding, finance, and healthcare workloads.

Yes . Nemotron 3.5 Lightning is generally available under the permissive OpenMDW-1.1 license, with open weights, training data, and recipes. NVIDIA states the model is ready for commercial use.

Long-running agents spend most of their time on high-volume execution. Tool calls, result validation, and subagent delegation dominate the token budget. Routing every one of those steps to a frontier reasoning model adds cost and latency.

Nemotron 3.5 Lightning targets that execution layer. It is a 30B mixture-of-experts model with 3B active parameters, built on a hybrid Mamba-2 + MoE + Attention architecture. Context length reaches 1M tokens. Pre-training covered more than 20 trillion tokens using an NVFP4 recipe.

The model is the smallest member of the Nemotron 3 family. Frontier models such as Nemotron 3 Ultra handle orchestration and planning, while Lightning handles the routine calls beneath them.

NVIDIA reports up to 4x output speed versus similar-sized models. On PinchBench, it reports 86% accuracy while completing 10,000 tasks 30% faster than Qwen3.6 35B at comparable accuracy.