NVIDIA Expands NVIDIA Agent Toolkit With NVIDIA PhysicsNeMo and CUDA-X Libraries to Transform How the World Engineers, Designs and Builds
Rhea-AI Summary
NVIDIA (NASDAQ: NVDA) expanded its NVIDIA Agent Toolkit for engineering by adding re-architected PhysicsNeMo AI physics libraries and updated CUDA-X libraries, giving autonomous AI engineering agents access to AI physics skills, accelerated sparse solvers (cuISS, cuDSS) and quantum chemistry capabilities (cuEST).
The company highlighted Nemotron 3 Ultra, which leads among open models in agentic RTL coding with the ACE-RTL agent. According to NVIDIA, industry leaders including Cadence, Siemens, Synopsys, Samsung, Silvaco, Keysight and TSMC are already using these accelerated computing and agentic AI technologies for workflows spanning chip design, verification, packaging, PCB, 3D-IC, thermal analysis, lithography and quantum chemistry, reporting speedups of up to 20x for multiphysics, over 10x for library characterization and up to 50x for key quantum-chemistry workloads.
Positive
- Expanded Agent Toolkit with PhysicsNeMo and CUDA-X adds AI physics, sparse solvers and quantum chemistry skills for engineering agents
- Nemotron 3 Ultra leads among open models in agentic RTL coding on a comprehensive Verilog benchmark
- Cadence reports up to 20x faster multiphysics performance for advanced packaging and PCB design using NVIDIA technologies
- Siemens agentic workflows deliver over 10x faster library characterization and more than 10x token cost reduction
- cuEST integration with Samsung, Synopsys and TSMC achieves up to 50x speedup in key quantum-chemistry workloads
Negative
- None.
News Explained
NVIDIA has announced an expansion of its Agent Toolkit with PhysicsNeMo and CUDA-X libraries. The disclosure therefore describes an evolving product offering, not a completed delivery or committed obligation.
Key Figures
Previous AI Reports
| Date | Event | Sentiment | 24h Move | Catalyst |
|---|---|---|---|---|
| Jul 25 | AI infrastructure expansion | Positive | +0.0% | Planned Korea infrastructure expansion with NAVER and Brookfield |
| Jul 23 | AI research partnership | Positive | -0.9% | Joint KAIST research lab with $300 million collaboration |
| Jul 20 | Agent toolkit expansion | Positive | +0.2% | Added Omniverse libraries for simulation-ready 3D agent workflows |
| Jul 16 | National AI infrastructure | Positive | -2.4% | Japan AI factory planned with 27,500 Rubin GPUs |
| Jul 15 | Physical AI expansion | Positive | -2.4% | Japanese robotics and manufacturing leaders adopted physical AI stack |
24h Move is the share-price change in the day after each event; other market factors may also have contributed.
AI-tagged history was mostly divergent, with three negative reactions to positive announcements and an average move of -1.1%.
Key Terms
electronic design automation (eda) technical
register-transfer level (rtl) technical
density functional theory (dft) technical
preconditioners technical
AI-generated analysis. How Rhea-AI works. Not financial advice.
News Summary:
- NVIDIA expands NVIDIA Agent Toolkit with re-architected NVIDIA PhysicsNeMo libraries and updated NVIDIA CUDA-X libraries, enabling software developers to build autonomous AI engineers with AI physics skills, accelerated solvers and quantum chemistry capabilities.
- NVIDIA Nemotron 3 Ultra leads among open models in agentic register-transfer level coding with the ACE-RTL agent from NVIDIA Research, helping enterprises build customizable AI agents for chip design and verification.
- Cadence, Siemens, Synopsys and other industry leaders are using NVIDIA accelerated computing and agentic AI technologies to advance autonomous engineering workflows across chip design, verification, packaging and systems.
LONG BEACH, Calif., July 26, 2026 (GLOBE NEWSWIRE) -- NVIDIA today 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 Adds AI Physics and Accelerated Computing Skills for Engineering Agents
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.
NVIDIA Nemotron 3 Ultra Open Model Advances Agentic Coding for Chip Design
Chip design depends on specialized register-transfer level (RTL) coding, which demands high accuracy, deep domain expertise and flexibility over deployment.
With ACE-RTL — an agent for designing hardware from NVIDIA Research — NVIDIA Nemotron™ 3 Ultra leads among open models in agentic RTL coding on the comprehensive verilog design problems benchmark across RTL coding tasks.
This represents how Nemotron 3 Ultra offers industry-leading accuracy and efficiency and can be post-trained on proprietary data — deployed locally or on premises — giving enterprises greater control, customization and data privacy as they build AI agents for chip design.
Developers can get started with Nemotron 3 Ultra using Cadence’s harness; Synopsys’ fully autonomous, long-running agents for design verification and analog and mixed-signal workflows; Siemens’ Questa One smart verification agentic toolkit; as well as on Hugging Face.
Software Leaders Build Autonomous AI Engineers With NVIDIA
Industrial engineering leaders are already using the new and expanded NVIDIA Agent Toolkit components to develop autonomous AI engineers.
Cadence is using NVIDIA Nemotron, accelerated computing and CUDA-X libraries with the recently launched Cadence AuraStack AI Super Agent and the Cadence Millennium M2000 platform to autonomously drive advanced packaging and printed circuit board (PCB) design from exploration through signoff, delivering up to 20x faster multiphysics performance. This joins Cadence’s complete portfolio of silicon design super agents which collectively cover the chip design workflow end to end, from architecture through manufacturing signoff.
In addition, the collaboration extends from agentic design to the underlying compute as Cadence’s portfolio of EDA and system design automation tools, including Cadence Jasper, a formal verification platform, is being optimized for the NVIDIA Vera CPU to help engineering teams validate advanced chip designs faster.
Synopsys is using the NVIDIA Agent Toolkit, NVIDIA NIM™ microservices, Nemotron open models, the NVIDIA NeMo™ Gym library and NVIDIA NemoClaw™ blueprints with Synopsys AgentEngineer to build secure, accelerated agentic workflows across chip and system design. Leveraging Ansys Icepak, Synopsys’ agentic workflow autonomously executes simulation setup, and pre- and post-processing for complex GPU cooling design optimization. Synopsys is developing NVIDIA cuISS use cases to accelerate simulation workloads.
The collaboration extends from agentic workflows to the underlying compute platform as Synopsys VCS, a high-performance functional verification solution used to simulate and validate complex chip designs before fabrication, is being optimized for the NVIDIA Vera CPU to help improve verification throughput.
Siemens is using NVIDIA NeMo Gym, Nemotron open models and CUDA-X libraries with the Siemens Fuse EDA AI Agent to orchestrate multi-tool and multi-agent workflows across semiconductor, 3D-IC, PCB and system design, from conception through signoff. In Siemens Solido Characterization Suite, these agentic AI workflows are delivering more than 10x faster library characterization while reducing token costs by more than 10x.
Samsung is using NVIDIA cuLitho and CUDA-X libraries to achieve up to 20x greater performance for computational lithography and applying NVIDIA PhysicsNeMo to perform chip-scale thermal-stress analysis with numerical solver-level accuracy across domains containing up to 10 billion cells.
ChipAgents is using NVIDIA Agent Toolkit to build domain-specific AI agents for chip design and verification. The team is fine-tuning NVIDIA Nemotron models for complex end-to-end semiconductor design and verification workflows including debug, formal verification, coverage and more.
Silvaco is using NVIDIA accelerated computing to scale high-accuracy 3D optical simulation in the Silvaco Victory Device. Running on 32 NVIDIA GPUs interconnected by NVIDIA NVLink™ technology, it completed a 3.2-billion-mesh-node photonic edge coupler simulation in under four hours, a workload beyond the practical limits of CPU-based simulation.
Keysight is harnessing NVIDIA cuDSS to accelerate electromagnetic simulations by up to 10x, while Samsung, Synopsys and TSMC are integrating NVIDIA cuEST into its GPU-accelerated pipeline to achieve up to a 50x speedup for key quantum-chemistry workloads.
Learn more by joining NVIDIA at DAC.
About NVIDIA
NVIDIA (NASDAQ: NVDA) is the world leader in AI and accelerated computing.
For further information, contact:
Paris Fox
Corporate Communications
NVIDIA Corporation
press@nvidia.com
Certain statements in this press release including, but not limited to, statements as to: With NVIDIA Agent Toolkit, developers being able to 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; expectations with respect to growth, performance, availability, and benefits of NVIDIA’s products, services and technologies, and related trends and drivers; expectations with respect to NVIDIA’s third party arrangements, including with its collaborators and partners; expectations with respect to technology developments, and related trends and drivers; projected market growth and trends; expectations with respect to AI and related industries; and other statements that are not historical facts are forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended, which are subject to the “safe harbor” created by those sections based on management’s beliefs and assumptions and on information currently available to management and are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic and political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; the impact of technological development and competition; development of new products and technologies or enhancements to NVIDIA’s existing products and technologies; market acceptance of NVIDIA’s products or NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA’s products or technologies when integrated into systems; NVIDIA’s ability to realize the potential benefits of business investments or acquisitions; and changes in applicable laws and regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its Annual Report on Form 10-K and Quarterly Reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.
Many of the products and features described herein remain in various stages and will be offered on a when-and-if-available basis. The statements above are not intended to be, and should not be interpreted as a commitment, promise, or legal obligation, and the development, release, and timing of any features or functionalities described for our products is subject to change and remains at the sole discretion of NVIDIA. NVIDIA will have no liability for failure to deliver or delay in the delivery of any of the products, features or functions set forth herein.
© 2026 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, CUDA-X, NemoClaw, Nemotron, NVIDIA NeMo, NVIDIA NIM, NVLink and PhysicsNeMo are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.
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