# How Qualcomm could ease the AI hardware crisis > Source: > Published: 2026-06-29 23:40:24+00:00 Qualcomm may have the open platform answer to disrupting Nvidia's death grip on the AI ecosystem. The chip company, best known for its work in mobile devices, made a series of announcements over the past week that make it clear it's plowing full steam into AI, data centers, and playing a role in alleviating the compute crisis caused by AI. "We're now in this transition to what we're going to do in the next five years," Qualcomm CEO Cristiano Amon told investors on June 24 at Qualcomm Investor Day in New York City. Qualcomm's big moves include: **Launching Dragonfly as its AI data center brand**: Qualcomm now has the Dragonfly C1000 CPU, a Dragonfly AI300 inference accelerator, and a new memory technology called High Bandwidth Compute (HBC). These are especially designed to run AI workloads efficiently, saving power and reducing costs.**Acquiring Modular to create an open platform**: Modular lets developers write AI software once and run it on any type of chip. That will now include Qualcomm chips, as well as potentially AMD, Intel, and others. This will free AI builders from Nvidia's lock-in.**Signing Meta as its first customer**: Meta remains a big AI spender and signed a multi-generation deal in which Qualcomm's Dragonfly C1000 CPU will power Meta's next-generation servers, with production starting in the second half of 2028.**A Hugging Face deal for deploying AI**: Qualcomm signed a deal with Hugging Face to enable its 16 million developers to run its giant library of over 3 million open AI models on Qualcomm chips, from phones to laptops to cars to AI data centers. "From a high-performance compute solution standpoint, we have four different kinds of solutions that actually feed into the data center business," Qualcomm's GM of data center solutions Durga Malladi told The Deep View, referring to XPUs, custom CPUs, HBC memory, and Alphawave for networking. Although the least flashy thing that Qualcomm announced was the Modular acquisition, it's potentially the most significant. With Modular's software, Qualcomm can create an open platform that allows companies to run a "multi-silicon token factory," as Qualcomm called it during its Investor Day presentation. For many AI businesses, that could provide a degree of freedom from Nvidia, as Modular is a more modern competitor to Nvidia's CUDA software, which most of today's AI models use to access GPUs. Modular's software can access Nvidia GPUs faster and can access processors from other chipmakers as well. "CUDA and these 20-year-old C++ technologies are gatekeeping GPUs," Chris Lattner, CEO of Modular, told The Deep View in March at Nvidia GTC. "Our software runs on CPUs, it runs on GPUs, and it can run ASICs, and you can have a consistent experience across all of them… We have the first software stack that can actually scale across heterogeneous compute." ## Our Deeper *View* Nvidia is estimated to hold about 80% to 90% of the market for AI GPUs used to train and run AI models. As much as AMD, Intel, Amazon's Tranium, Google's TPUs, Cerberus, and others have tried to compete with Nvidia, the company continues to dominate the landscape for powering frontier models. Qualcomm jumping into the fray on AI chips could ease some of the demand and put downward pressure on prices by using Modular at the software layer, enabling companies to mix and match hardware from various chipmakers. That's a good sign for the long-term potential to drive down the cost of AI. And don't worry too much about Nvidia. It reportedly has a 12-month backlog of orders for its chips. And it's been expanding aggressively into other technologies such as robots, self-driving cars, world models, open models, and digital twins. It's well aware that the CUDA lock-in won't last indefinitely.