Meta and Broadcom to Co-Develop Custom AI Silicon

April 15, 2026
Meta has announced an expanded partnership with Broadcom to co-develop multiple generations of its Meta Training and Inference Accelerator (MTIA) chips, aiming to strengthen its AI infrastructure across apps and services.
Meta and Broadcom to Co-Develop Custom AI Silicon

Meta has expanded its collaboration with Broadcom Inc. to co-develop multiple generations of custom AI silicon, announced in a press release. The partnership focuses on advancing Meta’s Meta Training and Inference Accelerator (MTIA) chips, which power AI across its platforms.

Under the agreement, Broadcom will work with Meta on chip design, advanced packaging, and networking, leveraging its XPU platform to optimize Meta’s AI infrastructure. The collaboration includes an initial commitment exceeding one gigawatt of compute capacity, marking the first phase of a planned multi-gigawatt rollout.

The MTIA chips are designed for large-scale inference and recommendation workloads, as well as emerging generative AI applications. Broadcom’s Ethernet technology will also support high-bandwidth networking across Meta’s growing AI compute clusters.

As part of the expanded partnership, Broadcom CEO Hock Tan will step down from Meta’s board of directors and transition to an advisory role, providing input on Meta’s custom silicon roadmap and infrastructure strategy.

We hope you enjoyed this article.

Consider subscribing to one of our newsletters like Silicon Brief or Daily AI Brief.

Also, consider following us on social media:

Subscribe to Silicon Brief

Weekly coverage of AI hardware developments including chips, GPUs, cloud platforms, and data center technology.

Market report

AI’s Time-to-Market Quagmire: Why Enterprises Struggle to Scale AI Innovation

ModelOp

The 2025 AI Governance Benchmark Report by ModelOp provides insights from 100 senior AI and data leaders across various industries, highlighting the challenges enterprises face in scaling AI initiatives. The report emphasizes the importance of AI governance and automation in overcoming fragmented systems and inconsistent practices, showcasing how early adoption correlates with faster deployment and stronger ROI.

Read more