NVIDIA is launching Nemotron 3.5 Lightning, a 30-billion-parameter model optimized for agentic AI workloads, alongside N
As AI shifts from chatbots to autonomous agents, open models are meeting market demand for full control over deployment location and evolution. NVIDIA is expanding its Nemotron 3 model family with Nemotron 3.5 Lightning, the highest-efficiency model in its class for long-running agentic AI workloads, building on earlier releases of Nemotron 3 Nano and reflecting NVIDIA's commitment to improving open models for greater accuracy and speed.
Nemotron 3.5 Lightning is a 30-billion-parameter mixture-of-experts model built for specialized tasks within larger multi-agent systems, enabling smarter and more efficient agentic applications. The model delivers up to 4x faster output speed, leading to 30% faster agentic task completion compared with other models in its class. Because it is open and customizable, organizations can post-train Nemotron 3.5 Lightning with NVIDIA NeMo on their own domain data, tools and workflows to improve accuracy for specialized tasks.
NVIDIA is also releasing NeMo Switchyard, an open source library for smart routing inside popular agent tools. This technology routes prompts to the most capable and efficient model for each step of an agent workflow automatically, based on specific needs. Enterprises can build routers matched to their priorities such as quality, latency and cost requirements. Internal benchmarks show that NeMo Switchyard maintains frontier-level accuracy while reducing task completion cost to nearly one-third of Opus 4.8 alone. When deployed, NeMo Switchyard can intelligently direct each request to the most suitable model across developers' own mix of open, proprietary and NVIDIA models without requiring application rewrites.
Modern agentic systems increasingly operate as systems of models, or model ensembles, with different models specialized for different tasks. NVIDIA Nemotron models are designed for this architecture, where a frontier reasoning model such as Nemotron 3 Ultra or GPT-5.6 may plan and orchestrate a workflow, while smaller specialized models like Nemotron 3.5 Lightning perform targeted tasks such as code review, tool use, security alert monitoring and answering billing questions.
AI leaders across industries are already customizing Nemotron 3.5 Lightning for their workloads, including CrowdStrike for cybersecurity, Harvey with Trajectory for legal services and CodeRabbit with Baseten for code review. Lila Sciences is improving reasoning capabilities for agentic tasks across physical and life sciences, and Fastino Labs customized the model and is seeing leading accuracies for software development, finance and healthcare workloads.
Nemotron 3.5 Lightning can run on local AI systems including NVIDIA RTX PCs, NVIDIA DGX Spark, NVIDIA DGX Station and NVIDIA Jetson to maximize existing infrastructure investments, or scale across edge AI devices, NVIDIA RTX PRO workstations, data centers and cloud environments for enterprise use cases. This gives organizations control over privacy and deployment for high-volume specialized tasks requiring fast responses.
NVIDIA is publishing as much of the training data and techniques as licensing permits to allow for traceability, auditing and training of other models. Alongside Lightning, NVIDIA is releasing Nemotron-RL-Agentic-Terminal-Pivot, an agentic reinforcement learning dataset for post-training the model for coding agent capabilities.
Nemotron 3.5 Lightning is available on Hugging Face, ModelScope, OpenRouter and build.nvidia.com as an NVIDIA NIM microservice as well as through a broad ecosystem of NVIDIA Cloud Partners, post-training platforms, inference platforms and cloud service providers. NeMo Switchyard is available on GitHub and coming to partner platforms soon.