NVIDIA 发布 Nemotron 3.5 Lightning 开源 MoE 模型，面向长时智能体执行层

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NVIDIA Nemotron 3.5 Lightning Delivers Fast, Accurate Specialized Task Execution for Long-Running Agents

Aug 11, 2026

NVIDIA Nemotron 3.5 Lightning is an open 30B mixture-of-experts model with 3B active parameters optimized for high-volume, low-latency execution in long-running AI agents. The model includes speculative decoding with multi-token prediction baked in during pretraining, plus DSpark and DFlash draft models for inference optimization across serving scenarios. An NVFP4 quantized checkpoint ships alongside BF16, using specialized kernels that run on NVIDIA Blackwell, Hopper, and Ampere GPUs from data centers to DGX Spark. Developers can customize the model out of the box using LoRA or full SFT with NeMo Automodel and NeMo Megatron Bridge, plus reinforcement learning with NeMo RL and NeMo Gym . NVIDIA NeMo Switchyard routes requests to the most capable and efficient model, sending planning work to frontier models and execution work to Nemotron 3.5 Lightning. On the Artificial Analysis Intelligence Index, Nemotron 3.5 Lightning defines the accuracy-speed Pareto frontier for small open models, and on PinchBench it completes 10,000 tasks 30% faster than Qwen3.6 35B at comparable accuracy. Next Steps Try Nemotron 3.5 Lightning on build.nvidia.com to evaluate the model interactively. Download the model weights from Hugging Face for local deployment and customization. Read the Nemotron 3.5 Lightning cookbook for fine-tuning and deployment guides.

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Long-running AI agents spend most of their time on high-volume execution: tool calls, result validation, and subagent delegation. Using a frontier reasoning model for every execution step adds cost and latency.

NVIDIA Nemotron 3.5 Lightning is an open 30B mixture-of-experts (MoE) model with 3B active parameters built for that execution layer of always-on agents. It is designed for harnesses like OpenClaw and Hermes Agent—all supported by the NVIDIA NemoClaw open source security and management stack for running always-on AI agents.

The NVIDIA Nemotron open model family is like a software library, with each release continuously improving accuracy and speed. As these models evolve, the rapid maturation of model routing and orchestration is also underway.

This is important because developers increasingly build applications with a system of models . Frontier reasoning models such as Nemotron 3 Ultra handle orchestration and complex planning while smaller, more efficient models handle the high-volume execution layer.

This post introduces NVIDIA Nemotron 3.5 Lightning and explains how its smaller MoE design is optimized for high-volume, low-latency execution in autonomous agents. It also details the inference and training innovations that power it. Finally, the post also introduces NVIDIA NeMo Switchyard , a library that intelligently routes each task to the best model for the job.

Nemotron 3.5 Lightning is a customizable open 30B MoE model with 3B active parameters, providing optimal high-volume execution for autonomous agents. MoEs are fast and efficient because a router sends each token to just a few of its many experts, so only a fraction of the model’s parameters run per token. This provides the capacity of a larger dense model at the compute cost of a small one.

Nemotron 3.5 Lightning is the smallest member of the Nemotron 3 model family and ships with many of the same techniques proven across the family, including:

The result is a model built for execution-focused, high call volumes, and low latency—all at a size that deploys anywhere from an NVIDIA DGX Spark to a data center.

Models earn their place in specialized AI agent systems when they’re adapted to the job. And Lightning-class models are highly customizable: small models fine-tune faster, cheaper, and on far more modest hardware than their larger counterparts.

You can customize Nemotron 3.5 Lightning out of the box to fit your workload. As with every Nemotron open model launch, the weights, training data, and recipes are released as permissively as possible under OpenMDW-1.1, so you can:

This release includes Nemotron-RL Agentic Terminal Pivot , an open agentic reinforcement learning dataset used to train some of the coding agent capabilities.

While frontier models may win the headlines, models like Nemotron 3.5 Lightning earn their medals in the trenches. They handle requests like git pull, validate tool outputs, format results, and run the routine calls that dominate any long-running agent’s token budget.

Model routing and orchestration help make this division of labor more accessible. They are now available through NVIDIA NeMo Switchyard . Switchyard can expose Nemotron 3.5 Lightning as a routing target alongside your open and closed models, so every request lands on the most capable and efficient model that can handle it. Plans route up to the frontier, execution routes down to Lightning, ensuring that your tokens are spent efficiently and effectively.

Nemotron 3.5 Lightning delivers leading accuracy at the highest output speed in its class, winning the accuracy-versus-speed Pareto frontier on the Artificial Analysis Intelligence Index. This index combines nine evaluations to measure model performance across agentic tasks, coding, scientific reasoning, and general intelligence.

Nemotron 3.5 Lightning combines strong intelligence with up to 4x output speed of similar-sized models, placing it on the accuracy-speed Pareto frontier for high-volume agent workloads.

Figure 1. Nemotron 3.5 Lightning defines the accuracy-speed Pareto frontier for small open models on the Artificial Analysis Intelligence Index leaderboard

Agent efficiency ultimately comes down to how quickly a model completes useful work and not simply how fast it generates tokens. On PinchBench, Nemotron 3.5 Lightning reaches 86% accuracy while completing 10,000 tasks 30% faster than Qwen3.6 35B at similar accuracy.

Higher inference throughput and token efficiency places Nemotron 3.5 Lightning on the efficiency frontier, helping always-on agents finish high-volume work faster.

Figure 2. Nemotron 3.5 Lightning leads the efficiency frontier by completing agentic tasks up to 30% faster at comparable accuracies

How does Nemotron 3.5 Lightning deliver speed without compromising accuracy?

Nemotron 3.5 Lightning delivers speed and customization without compromising accuracy through speculative decoding, and quantization.

Nemotron 3.5 Lightning is built to quickly generate tokens and has the ability to generate multiple tokens through speculative decoding. This is a process whereby the model, or draft model, will draft some number of tokens which are efficiently reviewed. Nemotron 3.5 Lightning underwent a dedicated pretraining stage to bake multi-token prediction (MTP) into the model, as with Nemotron 3 Super and Ultra. After training, a dedicated MTP-boosting phase further improved MTP accuracy.

Beyond MTP, two draft models are provided with Nemotron 3.5 Lightning: DSpark , which is recommended for DGX Spark inference workloads and low concurrency data center workloads. MTP is best suited for medium to high concurrency, with the optimal draft length decreasing as concurrency increases. NVIDIA is also releasing a DFlash draft model, which can be measured against the others and may perform best for your workloads.

Nemotron 3.5 Lightning ships with an NVFP4 checkpoint alongside BF16, using the same specialized NVFP4 kernels that power Nemotron 3 Ultra across NVIDIA Blackwell, NVIDIA Hopper, and NVIDIA Ampere GPUs. The same file serves just as well in data centers as it does on your desktop DGX Spark.

Nemotron 3.5 Lightning makes capable agentic AI accessible on local systems including NVIDIA Jetson, GeForce RTX 5090, and DGX Spark.

NVIDIA has worked with a number of teams including EXO Labs to understand how this model performs on DGX Spark.

Figure 3. Nemotron 3.5 Lightning sits right on the Pareto frontier for small open models on the EXO Labs local.ai leaderboard

In addition, you can run Nemotron 3.5 Lightning across the industry standard set of tools, including LM Studio, llama.cpp, Ollama, and Unsloth.

Nemotron 3.5 Lightning is supported by a growing ecosystem of partners across harnesses, customization, deployment, and inference, including:

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