Cadence launches in-house AI chip design models with Nvidia backing

Highlights

Cadence Design Systems launched Cadence Maestro, an AI suite for chip design built partly on Nvidia's Nemotron model and using Nvidia's OpenShell safety technology.
Cadence claims Maestro models, available to early-access customers in Q4, deliver up to 30% higher quality and five times better cost-efficiency than general-purpose models.
Cadence's in-house, model-agnostic approach contrasts with Synopsys, which partners with OpenAI for GPT-Synopsys hosted by OpenAI, underscoring a split in AI deployment strategies for chip design.

Maestro rollout expands Cadence AI strategy

As reported by Reuters, Cadence Design Systems on Monday introduced Cadence Maestro, a suite of AI models tailored for computer chip design and built in part on Nvidia's open-weight Nemotron model. The companies say the portfolio also uses Nvidia's OpenShell safety technology, extending a partnership aimed at giving chipmakers more control over how AI is deployed in sensitive design environments.

Cadence says customers can run the models on its own cloud or on any public cloud, while also keeping them fully in-house behind corporate firewalls and data centers. The company adds that customers can fine-tune the models on their own chip designs, with early results showing up to 30% higher quality and up to five times better cost-efficiency than general-purpose models.

The first Maestro models are scheduled to reach select early-access customers in the fourth quarter. Paul Cunningham, a senior vice president at Cadence, describes Maestro as model-agnostic and says the company is pursuing both open- and closed-weight approaches, including potential work with commercial AI labs, though he does not provide further details.

Competitive split emerges in chip design AI

Cadence's approach differs from that of larger rival Synopsys, which said on September 30 that it would develop an AI model with OpenAI and share revenue with the ChatGPT maker. Synopsys says that model, GPT-Synopsys, will run on OpenAI-hosted infrastructure.

The differing strategies highlight a broader divide in the electronic design automation sector over whether chipmakers will prefer tightly hosted AI services or systems they can operate inside their own infrastructure. For companies designing advanced chips with billions of transistors and strict cost and performance targets, the ability to keep data and model use in-house could become a significant operational and commercial consideration.

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