NVIDIA Expands NVIDIA Agent Toolkit With NVIDIA PhysicsNeMo and CUDA-X Libraries

• 27 Jul 2026
• TM Team
• 0 Comments

NVIDIA announced an expansion of NVIDIA Agent Toolkit for engineering, now adding NVIDIA PhysicsNeMo and CUDA-X libraries as agent-ready tools and skills built to transform how the world designs and develops products.

Building the next generation of chips and systems requires teams to connect physics, simulation and performance analysis across increasingly complex design cycles. A new class of autonomous AI engineers is emerging to help take on that complexity — using specialized tools, running simulations and generating high-fidelity data to help scale chip design, verification, packaging and systems. 

Now included in NVIDIA Agent Toolkit, NVIDIA has re-architected PhysicsNeMo into a set of agent-friendly libraries and added new and updated CUDA-X libraries to support complex engineering work. PhysicsNeMo provides AI physics skills for training and deploying models, while CUDA-X libraries bring accelerated solvers and quantum chemistry capabilities into agentic engineering workflows.

"Engineering has reached an inflection point. AI can now work with tools of physics, simulation and design," said Timothy Costa, vice president and general manager of computational engineering at NVIDIA. "With NVIDIA Agent Toolkit, developers can build agentic engineers that reason using physics, run complex simulations and generate high-fidelity data to become a new engine for innovation in chip and system design."

NVIDIA Agent Toolkit helps developers build specialized engineering AI assistants connected to domain-specific tools, models and data. With the addition of NVIDIA PhysicsNeMo and CUDA-X libraries, these agents can now use AI physics skills, accelerated solvers and quantum chemistry capabilities for chip, system and industrial engineering. 

Key capabilities include:

• AI physics skills: NVIDIA PhysicsNeMo libraries help agents train and deploy customizable AI physics models for complex design and simulation tasks, turning model architectures into callable tools for engineering workflows.
• Iterative sparse solvers: New NVIDIA cuISS (CUDA Iterative Sparse Solvers) library accelerates large sparse linear systems in physics-based and engineering simulations. Designed for flexibility and performance on GPUs, its modern, composable solvers and preconditioners help developers build scalable, production simulation engines for agentic engineering workflows. 
• Direct sparse solvers: NVIDIA cuDSS (CUDA Direct Sparse Solvers) accelerates large, complex sparse linear systems central to electronic design automation (EDA) and scientific simulation. It delivers high performance and numerical robustness for critical workloads like device, circuit and system simulations with scalability to multi-GPU and multi-node deployments in production environments.
• Quantum chemistry: NVIDIA cuEST (CUDA Electronic Structure Theory) brings high-accuracy quantum chemistry simulations to device-relevant scales, enabling density functional theory (DFT) and post-DFT methods to be integrated into production workflows at scale. cuEST brings production value to customers by supporting a wide range of modern functionals and making increasingly large ground-state and excited-state simulations manageable on NVIDIA GPUs.