Amazon and Synopsys announced a multi-year partnership valued at over $1 billion, giving Amazon exclusive licenses to Synopsys' AI-accelerated chip design tools.
Amazon and chip design tool maker Synopsys are entering a multi-year agreement worth over a billion dollars to deepen their cooperation on AI chip design and optimize their tools for each other's platforms. Under the deal, Amazon will license Synopsys' intellectual property and expand its use of Synopsys' electronic design automation (EDA) software tools for AI chip design and agentic AI technologies.
The partnership runs both directions. Synopsys will optimize its multiphysics solutions for Amazon's Trainium and Graviton chips, adopt AWS cloud computing and storage services, and use Amazon Bedrock to build and deploy AI applications and agents for its own development work.
While the arrangement involves mutual benefit, Synopsys and its competitors are steadily automating greater portions of the chip design process. By ensuring that process is optimized for Amazon hardware, Amazon gains significant advantage in a landscape where chip design is becoming faster and easier—particularly relevant as major AI companies race to develop their own inference hardware to reduce dependence on costly Nvidia GPUs.
Major AI developments in 2026 have centered on agentic AI applications, driving hardware shortages and a competitive push to fill that gap with optimized solutions. The Synopsys-Amazon partnership positions both companies to capitalize on this trend through better-integrated chip design and development, benefiting customers who use both companies' services and components.
The deal's core centers on chip design collaboration. Amazon will expand its use of Synopsys' application-optimized IP—silicon designs it can incorporate into its own chips—and leverage Synopsys' AI-powered engineering software to accelerate custom AI chip development and AWS infrastructure hardware. Amazon's existing Graviton 5 already serves CPU-intensive agentic AI workloads; accelerating next-generation designs could strengthen its position competing with Nvidia in AI data center deployment. The announcement also cites Trainium chips for AI training and Nitro for cloud security, networking, and storage, suggesting the collaboration could enhance multiple chip lines.
Beyond the chip design process itself, Amazon and Synopsys will collaborate on applying AI within their own workflows, optimizing the silicon-to-system process to accelerate and improve chip design. Amazon will deploy Synopsys' AI-powered EDA, physics-based simulations, and agentic AI solutions to enhance its engineering teams' capabilities, with both companies claiming this will help them design, analyze, optimize, and validate new chip designs more efficiently.
"As our chip designs grow more ambitious and AI reshapes the engineering process itself, Synopsys helps us move faster across the design cycle, helping us deliver more capable, efficient computing for customers worldwide," said Amazon SVP Peter DeSantis.
With Synopsys and competitors Cadence and Siemens all pursuing faster, more autonomous chip design, enterprise hardware design cycles could shorten significantly. Companies like Amazon and Synopsys will need to keep pace with that acceleration.
Synopsys will adopt AWS compute and storage services to accelerate its own IP and software development, and will use Amazon Bedrock to build and deploy AI applications and agents for its product offerings. This embeds Amazon cloud services deeper within Synopsys' engineering workflows while Synopsys' intellectual property becomes more integrated into Amazon's custom silicon. Their joint plan to optimize Synopsys' multiphysics solutions on Amazon's Trainium and Graviton could make Amazon's hardware more attractive to customers running engineering workloads.
The IP agreement introduces a license-plus-royalty model, offering Synopsys financial upside as production volume increases. With Amazon as its lead customer for application-optimized IP, this deal serves as a strong endorsement of its chip design blueprints, potentially making it easier to pitch its AI-powered tools to other chip developers.
For Amazon, the partnership should accelerate its custom chip designs while strengthening the case for AWS services through optimized Synopsys tools, with both companies benefiting from jointly advancing the chip design process through agentic AI augmentation. Faster chip design does not necessarily translate to better chips or shorter time to market, but even modest performance or efficiency improvements could make AWS infrastructure more attractive and competitive.
However, with no announced timeline for new chip development, both firms must demonstrate the partnership's effectiveness before the billion-dollar valuation can be properly assessed.