Nvidia is investing $3.5 billion into Taiwanese chipmaker MediaTek. As part of the deal, MediaTek will adopt Nvidia\u2019s technology that will help it design custom chips for AI companies and hyperscalers that can be plugged directly into Nvidia-based data centers.<\/p>\n
The deal comes as a growing number of AI companies and major cloud providers like Amazon, Google, Microsoft, OpenAI<\/a> and Anthropic<\/a> invest in building their own chips so they can be less reliant on Nvidia\u2019s GPUs. Deals like this one with MediaTek allow Nvidia to cede ground to custom silicon while still maintaining its lead as the dominant data center scaffolding.\u00a0<\/p>\n \u201cNvidia is an AI infrastructure company,\u201d Dion Harris, Nvidia\u2019s senior director of HPC and AI hyperscaler infrastructure solutions, said on Monday on a call with reporters. \u201cWe expanded beyond pure computing chips years ago.\u201d<\/p>\n The partnership underscores the circular nature of Nvidia\u2019s financing efforts over the past few years, which have often seen the chip giant investing in companies that flow back into its own ecosystem. The deal will give MediaTek access to Nvidia\u2019s NVLink Fusion ecosystem, including NVLink, the technology that lets any chips \u2014 even if they\u2019re not Nvidia\u2019s chips \u2014 communicate with each other quickly.\u00a0<\/p>\n Last week, Nvidia announced a similar partnership with Amazon Web Services, albeit without the direct investment. AWS will deploy<\/a> an additional 2 million Nvidia GPUs across its infrastructure, and also integrate NVLink Fusion.\u00a0<\/p>\n With the Nvidia partnership, MediaTek can continue to build custom chips designed by cloud companies or AI labs tailored to their workloads, leveraging Nvidia\u2019s \u201cproven scale-up and scale-out technology stack and ecosystem\u201d and \u201crack-scale architecture.\u201d<\/p>\n \u201cBasically, every cloud, every model builder is deploying our platform in some shape, form, or fashion,\u201d Harris said. \u201cSo by MediaTek being able to offer this extension to its customers, it allows them to standardize on the rack-scale infrastructure across their AI factories\u2026 and also deploy their [custom chips] right alongside those using the same standard platform.\u201d<\/p>\n \u201cThis is really about opening up this ecosystem to the entire MediaTek customer base,\u201d Harris continued.<\/p>\n MediaTek hasn\u2019t publicly shared information about its customer base as it relates to custom AI chips, but it\u2019s clear Nvidia aims to help it boost that side of the business so long as it can come along for the ride. MediaTek has been slowly building its custom data center ASIC (application-specific integrated circuit) operations, saying in June<\/a> that it expects the business to generate $2 billion in revenue in 2026, and hopes to target more of the market in the coming years.<\/p>\n Given MediaTek\u2019s expertise in developing custom chips that power smartphones<\/a>, smart homes, automobiles, and wireless communications, the company will also continue to collaborate with Nvidia on DGX Spark, the company\u2019s small developer-focused desktop AI computer. The companies have extended their collaboration with the RTX Spark, Nvidia\u2019s push to put its AI tech into consumer AI PCs.<\/p>\n MediaTek and Nvidia will also continue \u201cdeveloping platforms for AI-powered, software-defined vehicles<\/a> in the era of physical AI,\u201d per a press release. MediaTek\u2019s auto platforms rely on Nvidia\u2019s RTX graphics for intelligent vehicle cockpits and work, alongside Nvidia Drive AGX, the company\u2019s in-car computing platform for autonomous driving workloads.\u00a0<\/p>\n \u201cAI is transforming every computing platform \u2014 from the world\u2019s largest AI factories to the PC and the car,\u201d Jensen Huang, founder and CEO of Nvidia, said in a statement. \u201cTogether, we\u2019re building platforms that bring NVIDIA accelerated computing to new markets and give customers the freedom to create differentiated AI systems at enormous scale.\u201d<\/p>\n