By Hamza Faisal
Synopsys has struck a revenue-sharing deal with OpenAI to develop an artificial intelligence model built specifically for designing computer chips, the two companies announced on Wednesday.
The model, called GPT-Synopsys, will be trained to handle the full arc of chip design, from describing a chip's circuits in a code-like language to laying out billions of transistors on a small square of silicon.
The announcement came at a Synopsys investor summit, where the company said OpenAI's model will learn to operate Synopsys's own software tools so engineers can work through design trade-offs and optimizations faster.
“To be able to shave off weeks, months from the design process and to bring more chips to the world,” OpenAI co-founder Greg Brockman said in a video announcing the news.
An unusual revenue model
Synopsys CEO Sassine Ghazi told Reuters that OpenAI will pay Synopsys a training subscription fee for teaching the model to use its tools. Once Synopsys customers deploy the product commercially, the two companies will split revenue based on how much the model improves the resulting chip designs.
“We structured the agreement in a way that it will not be cannibalizing our business,” Ghazi said in an interview. “It will be an upside to our business given we’re delivering more value to the customer.”
At the same summit, Ghazi raised Synopsys’s outlook, saying the company now expects 15% revenue growth for fiscal 2027, well above the 11.19% analysts had projected, according to LSEG data. Shares rose as much as 7% following the partnership and forecast announcements.
Guardrails still in place
Despite the push toward automation, Synopsys says the AI’s output will not go unchecked. The GPT-Synopsys model’s work will be double-checked by Synopsys tools that use traditional computing techniques to verify whether a chip will actually work.
“The model needs these guardrails in order to check the physics,” Ghazi said. “The need for validating with the highest level of fidelity, what we call sign-off or ground truth, is essential.”
The deal underscores how quickly generative AI is moving into the highly specialized world of semiconductor engineering, where a single design cycle can take months and cost tens of millions of dollars. If AI can compress that timeline meaningfully, the competitive advantage for chipmakers could be substantial.
