According to a recent Reuters report, OpenAI is continuing with its moves in the custom silicon space, expanding beyond its reported talks with Broadcom to include a broader strategy involving multiple industry leaders. Broadcom is a fabless chip designer known for a wide range of silicon solutions spanning from networking, PCIe, SSD controllers, and PHYs all the way up to custom ASICs. The company behind ChatGPT is actively working with both Broadcom and TSMC to develop its first proprietary AI chip, specifically focused on inference operations. Getting a custom chip to do training runs is a bit more complex task, and OpenAI leaves that to its current partners until the company figures out all details. Even with an inference chip, the scale at which OpenAI works and serves its models makes financial sense for the company to develop custom solutions tailored to its infrastructure needs.

This time, the initiative represents a more concrete and nuanced approach than previously understood. Rather than just exploratory discussions, OpenAI has assembled a dedicated chip team of approximately 20 people, led by former Google TPU engineers Thomas Norrie and Richard Ho. The company has secured manufacturing capacity with TSMC, targeting a 2026 timeline for its first custom-designed chip. While Broadcom's involvement leverages its expertise in helping companies optimize chip designs for manufacturing and manage data movement between chips—crucial for AI systems running thousands of processors in parallel—OpenAI is simultaneously diversifying its compute strategy. This includes adding AMD's Instinct MI300X chips to its infrastructure alongside its existing NVIDIA deployments. Similarly, Meta has the same approach, where it now trains its models on NVIDIA GPUs and serves them to the public (inferencing) using AMD Instinct MI300X.