Synopsys (SNPS)’s collaboration with OpenAI marks the accelerating penetration of AI technology into the EDA sector upstream in the semiconductor industry chain. Through a “training subscription fee plus revenue sharing” business model, the two parties bind their interests to the actual improvement effects in chip design, which is expected to shorten design cycles and reduce trial-and-error costs. Although GPT-Synopsys still requires traditional tools for signoff verification, and key details such as the revenue-sharing ratio and data usage have not yet been disclosed, the collaboration has already triggered a positive market reaction, with Synopsys’s stock price rising by as much as 7% after the announcement.
OpenAI co-founder Greg Brockman said in a video announcing the news that OpenAI’s models will learn how to use Synopsys’s software tools to help engineers handle various trade-offs and optimizations in the chip design process, “thereby shortening the design process by weeks or months and bringing more chips into the world.”
Synopsys announced the deal at an investor summit. Company CEO Sassine Ghazi said the same day that Synopsys currently expects fiscal 2027 revenue growth of 15%, higher than the 11.19% analyst estimate shown by LSEG data. After the collaboration and financial forecast news were announced, Synopsys’s stock price rose by as much as 7%.
In an interview with Reuters, Ghazi said OpenAI will pay Synopsys a training subscription fee to learn how to use Synopsys’s tools. When Synopsys customers use the product, Synopsys and OpenAI will share revenue based on the degree to which the model improves chip design. Ghazi said, “The agreement we designed is structured so that it will not cannibalize our business. Given that we deliver more value to customers, this will become an upside factor for our business.”
However, Ghazi also emphasized that GPT-Synopsys’s work will still be reviewed by Synopsys using tools based on traditional computing technology to verify whether the chip can work properly. He said, “The model needs these guardrails to check physics. Verifying at the highest fidelity, what we call signoff or ground truth, is crucial.”
The core significance of this deal lies in the fact that AI is further penetrating from general-purpose large models into the EDA sector upstream in the semiconductor industry chain. Chip design is highly complex, involving multiple stages from circuit description, logic synthesis, placement and routing to physical verification, and engineers need to repeatedly weigh performance, power consumption, area, and cost. If AI models can learn and call Synopsys tools to automatically complete part of the optimization and trade-offs, in theory this can significantly shorten design cycles and reduce trial-and-error costs.
From a business model perspective, the collaboration between Synopsys and OpenAI is not simple software licensing, but a combination of “training subscription fee plus revenue sharing.” OpenAI first pays fees to learn how to use Synopsys tools; when Synopsys customers use GPT-Synopsys, the two parties then share revenue based on the degree to which the model improves chip design. This pay-by-results model helps reduce customers’ concerns about the uncertain value of AI tools, and also binds OpenAI’s interests to the actual returns of Synopsys customers. However, the two parties have not disclosed key details such as the revenue-sharing ratio, exclusivity arrangements, and how customer design data will be used, which will be key areas of subsequent market attention.
