While model and agent evaluation are inextricably linked, their technical benchmarks and metrics for success are fundamentally different.
Mastering Agentic Techniques: AI Agent Evaluation | NVIDIA Technical BlogUsing the toolkit for this specific use case provides multiple benefits: Config-driven workflows The toolkit helps shift the project from a rigid script to a flexible research platform. Instead of hard-coding the interactions between agents, you define the system’s logic—including personas, tools, and constraints—entirely within a YAML configuration. This modularity makes it trivial to swap models for different tasks. For example, you can assign a high-reasoning model to handle hypothesis generation while using a faster, more cost-effective model for the code agent without modifying the underl
Automating and Optimizing Financial Signal Discovery with Multi-Agent Systems | NVIDIA Technical BlogAgentic AI / Generative AI Optimize Supply Chain Decision Systems Using NVIDIA cuOpt Agent Skills May 04, 2026 By Adi Geva , Rajath Narasimha and Sylendran Arunagiri Discuss 0 Discuss 0 L T F R E AI-Generated Summary Like Dislike Agentic AI integrates LLM reasoning with NVIDIA GPU-accelerated solve… …
… To ensure it produced logically sound results rather than “hallucinating” math, we provided it with a structured library of mathematical calculators as building blocks. Each calculator is a dictionary containing a name, signature, and meaning. …
Agentic AI / Generative AI Mastering Agentic Techniques: AI Agent Evaluation May 19, 2026 By Edward Li , Vanessa Bellotti , Nicola Sessions and Rebecca Kao Discuss 0 Discuss 0 L T F R E AI-Generated Summary Like Dislike Evaluating AI models focuses on assessing the foundation model's capabilities u… …
Agentic AI / Generative AI Build with Kimi K2.5 Multimodal VLM Using NVIDIA GPU-Accelerated Endpoints Feb 04, 2026 By Anu Srivastava Discuss 0 Discuss 0 L T F R E AI-Generated Summary Like Dislike Kimi K2.5 is a multimodal vision language model trained using the Megatron-LM framework, supporting ta… …
… Conventionally, obtaining \ \phi \mathbf{r} \ and \ \Sigma \mathbf{r} \ requires solving the neutron transport equation using high-fidelity Monte Carlo methods. …
Agentic AI / Generative AI Run High-Throughput Reinforcement Learning Training with End-to-End FP8 Precision Apr 20, 2026 By Guyue Huang , Shuang Yu , Zhaopeng Qiu , Oleg Rybakov , Wenwen Gao and Sylendran Arunagiri Discuss 0 Discuss 0 L T F R E As LLMs transition from simple text generation to com… …
Developer Tools & Techniques Build Next-Gen Physical AI with Edge‑First LLMs for Autonomous Vehicles and Robotics NVIDIA TensorRT Edge‑LLM introduces support for MoEs, Cosmos Reason 2, and Qwen3-TTS/ASR on NVIDIA Jetson and NVIDIA DRIVE Mar 12, 2026 By Lin Chai , Luxiao Zheng , Fan Shi , Maximilien… …
… Nemotron 3 Nano 30B A3B Nemotron 3 Nano offers 4x faster throughput compared to Nemotron 2 Nano Leading accuracy for coding, reasoning, math and long context tasks Perfect for agents that need to deliver highest accuracy and efficiency for targeted tasks Nemotron 3 Nano Omni 30B A3B Single model fo… …
Agentic AI / Generative AI Mastering Agentic Techniques: AI Agent Customization May 20, 2026 By Edward Li , Vanessa Bellotti and Rebecca Kao Discuss 0 Discuss 0 L T F R E AI-Generated Summary Like Dislike Customizing AI agents enhances their performance on specialized tasks by refining reasoning, t… …
… Parameters: ally entity : The ally to command enemy entity : The enemy to target Example: set target warrior, nearby 1 SLM-generated code for “target the nearest enemy”: local enemies = get enemies ally.position, 10 local closest = nil local min dist = math.huge for , enemy in ipairs enemies do loc… …