Nemotron

Sep 21, 2026

How to Evaluate AI Agents From Tool Calls to Task Completion

When you ship an AI agent, the key question is whether it can execute a chain of work across dozens of sequential tool calls against a live environment, and...
11 MIN READ
Sep 16, 2026

How to Use AI Agents to Prepare 3D Scenes for Simulation

Agentic AI workflows can be used to prepare and validate digital twins for physical AI systems. Agents can inspect 3D scenes, author simulation-relevant data...
18 MIN READ
Sep 15, 2026

Dense vs. MoE Models: Active Parameters, Throughput, and When to Choose Each

How can a 30B-parameter model activate only 3B parameters per token, and still use the capacity of the larger model? Nemotron 3.5 Lightning illustrates the...
9 MIN READ
Sep 10, 2026

How Full-Stack NIM Optimizations Deliver 2.5x More Users on Nemotron 3 Ultra

Deploying a large language model is only the first step toward production-ready serving. Production teams also need to serve as many concurrent users as...
6 MIN READ
Sep 10, 2026

From Wafer-Out to First Token: Codifying Supply Chain Expertise with Nemotron and Palantir Foundry

NVIDIA has one of the largest and most complex supply chains in the world, and its performance is measured from wafer-out to first token. The interval is in...
12 MIN READ
Sep 04, 2026

Building a Memory-Driven Agent with NVIDIA NemoClaw

Enterprise work spans messages, decisions, projects, and obligations that change over time. An AI agent that starts without this context must reconstruct it...
6 MIN READ
An illustration showing agentic security.
Sep 01, 2026

Building an Adaptive Agentic Cybersecurity System with NVIDIA Nemotron

AI is changing the pace of cybersecurity. Agentic systems can coordinate work and pursue complex objectives over long horizons. Security teams are beginning to...
11 MIN READ
Aug 24, 2026

NVIDIA Vera Rubin and Blackwell Set a New Standard for Agentic AI Performance per Watt 

AI agents have expanded inference from single-turn interactions into multi-step workflows that reason, invoke tools, coordinate subagents, and carry growing...
9 MIN READ
Aug 21, 2026

GPU-Accelerated Clustering for Financial Instruments at Scale

Use AdaptGrow, a GPU-accelerated matrix factorization algorithm, to turn rolling correlation and tail-dependence matrices into hard clusters, soft factor...
13 MIN READ
Aug 17, 2026

Developing Nemotron 3.5 Lightning NVFP4 with QAD Using NVIDIA Model Optimizer

Teams customize their models to hit their targets for latency, speed, memory, and compute. With the open NVIDIA Nemotron family of models, developers can find...
18 MIN READ
Aug 11, 2026

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

Long-running AI agents spend most of their time on high-volume execution: tool calls, result validation, and subagent delegation. Using a frontier reasoning...
8 MIN READ
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Aug 11, 2026

Route AI Agent Workloads Across Models with NVIDIA NeMo Switchyard

Building an AI agent does not end with choosing a single model. Each model has its own strengths, weaknesses, and cost profile, which can shift from one...
12 MIN READ
Jul 26, 2026

NVIDIA Nemotron 3 Ultra Leads Open Models on Accuracy and Efficiency in Agentic RTL Coding

Modern chip design is increasingly limited by engineering time. Register transfer level (RTL) development and verification require specialized hardware...
9 MIN READ
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Jul 23, 2026

Start Customizing NVIDIA Nemotron 3 Nano with Prime Intellect Lab in Minutes

Customization is what enables developers to take a general model and tailor it to use cases, domains, languages, and more. However, customization comes with a...
13 MIN READ
Jul 14, 2026

Lessons From the Leaderboard: What 5,000+ Kagglers Taught Us About Improving AI Reasoning

The NVIDIA Nemotron Model Reasoning Challenge invited the Kaggle community to explore a focused question: What techniques can improve reasoning accuracy when...
11 MIN READ
Jul 09, 2026

Synthetic Data Generation for Financial AI Research with NVIDIA NeMo

Fine-tuning LLMs for financial natural language processing (NLP) is constrained by limited, imbalanced data. Real-world financial news overrepresents earnings...
13 MIN READ