The Maestro portfolio delivers up to 30% better results and 5X token efficiency, with secure cloud and on-premises deployment options.
Cadence announced the Maestro AI Model Portfolio, which powers Cadence AI Super Agents across semiconductor and system design workflows. By integrating these models with reinforcement learning (RL) loops and its proven electronic design automation (EDA) and system design automation (SDA) tools, Cadence delivers a deeply integrated agentic engineering platform designed to improve results, accelerate time to market and continuously enhance performance through recursive self-improvement.
The Maestro technology offers customers a secure, Cadence-managed platform that combines exceptional domain-specialized intelligence and expertise with the control, choice, and flexibility they need to innovate with confidence. The Maestro portfolio spans multiple model sizes and architectures, combining domain-specialized post-trained large language models (LLMs), trained decision models and self-improving agent skills. Integrated with Cadence AI Super Agents—including AuraStack, ChipStack, InnoStack, and ViraStack AI Super Agents—as well as its proven EDA and SDA tools and reinforcement learning, the Maestro portfolio brings specialized intelligence to complex engineering workflows through an optimal blend of frontier, open-weight and domain-specialized models across cloud and on-premises environments.
A self-improving learning environment for engineering AI
Initial results show up to 30% improvement in quality of results and up to 5X greater token efficiency versus general-purpose foundation models. These gains come from a vertically integrated learning environment combining Cadence domain knowledge, curated engineering datasets, AI Super Agents, EDA and SDA tools, and evaluation harnesses. Cadence’s principled algorithms and deterministic solvers evaluate outputs against engineering objectives, constraints and ground truth, creating closed and verified feedback loops for reinforcement learning and recursive improvement.
Domain intelligence with intelligent model choice
The Cadence learning environment unifies complementary AI capabilities in a single workflow. Frontier and open-weight models provide broad language, reasoning and multimodal capabilities; the Maestro AI Model Portfolio provides domain expertise for complex chip and system design. Given a high-level objective, Cadence AI Super Agents interpret design intent, decompose tasks, orchestrate the Maestro portfolio with other leading frontier and open-weight models, and drive Cadence EDA and SDA tools. The combined solution interprets specifications, generates design content, analyzes results, evaluates tradeoffs and guides decisions based on engineering requirements, cost and security. The Maestro portfolio, including NVIDIA Nemotron and other models, can be further post-trained on a customer’s proprietary data, designs, and workflows and, by balancing EDA and SDA tool calls with LLM invocations, it significantly reduces token usage while maintaining execution efficiency.
The complete Cadence agentic environment—including AI Super Agents, Maestro AI Model Portfolio and EDA tools—can run on Cadence’s secure cloud platform, secure public clouds, or in a customer-controlled on-premises environment to meet data privacy, security and deployment requirements. Cadence and NVIDIA are also working together on agent security through integration with the NVIDIA OpenShell Reference Architecture.
Availability
The first Maestro models are available to select early access customers in the fourth quarter of 2026.
For more information, visit cadence.com.
