A new potential candidate has joined the AI chip war. Qualcomm, which powers billions of smartphones around the world, has taken a bold leap into AI data center chips. In this market, Nvidia is minting money at an almost incredible rate, and wealth rises and falls with the promise of computational superiority.
On October 28, 2025, Qualcomm took on the challenge with its AI200 and AI250 solutions, rack-scale systems designed specifically for AI inference workloads. Wall Street’s reaction was immediate, sending Qualcomm’s stock up about 11% as investors bet that even a small slice of the exploding AI infrastructure market could change the company’s trajectory.
The launch of this product could redefine Qualcomm’s identity. The San Diego chip giant is synonymous with mobile technology and is riding the smartphone wave to the top. But as the market stagnates, CEO Cristiano Amon is making a calculated bet on AI data center chips, backed by a multibillion-dollar partnership with a Saudi AI giant that signals serious intentions.
2 chips, 2 different bets on the future
This is where Qualcomm’s strategy becomes interesting. Rather than release a single product and hope for the best, the company hedges its risk with two different AI data center chip architectures, each targeting different market needs and timelines.
Coming in 2026, the AI200 takes a pragmatic approach. Think of this as a Qualcomm effort, a rack-scale system with 768 GB of LPDDR memory per card.
Its massive memory capacity is essential for running today’s large, memory-hungry language models and multimodal AI applications, and Qualcomm is betting its low-cost memory approach can deliver the performance businesses demand while undercutting its competitors in total cost of ownership.
But the AI250, scheduled for 2027, is where Qualcomm engineers are really dreaming big. This solution introduces a near-memory computing architecture that promises to break traditional limitations with over 10x more effective memory bandwidth.
For AI data center chips, memory bandwidth is the bottleneck that determines whether chatbots respond instantly or keep users waiting. Qualcomm’s innovation here could be truly transformative if it can deliver on its promise.
“With Qualcomm AI200 and AI250, we are redefining what is possible with rack-scale AI inference,” said Durga Maradi, senior vice president and general manager of technology planning, edge solutions and data centers at Qualcomm Technologies. “Our innovative new AI infrastructure solutions will enable our customers to deploy AI at an unprecedented TCO while maintaining the flexibility and security required in modern data centers.”
The real battle: not just performance but economy
In the AI infrastructure arms race, raw performance specifications only tell half the story. The real war is fought on spreadsheets, where data center operators calculate electricity bills, cooling costs, and hardware depreciation. Qualcomm knows this, which is why both AI data center chip solutions are focused on total cost of ownership.
Each rack consumes 160 kW of power and employs direct liquid cooling. This is essential when delivering so much computational power through silicon. This system uses PCIe for internal scaling and Ethernet for connecting multiple racks, giving you deployment flexibility whether you’re running a small AI service or building your next ChatGPT competitor.
Security is not an afterthought either. Confidential computing capabilities are built in to meet the growing demands of enterprises to protect their proprietary AI models and sensitive data.
The Saudi connection: a billion-dollar test
Although partnership announcements are few and far between in the technology industry, Qualcomm and Humane’s deal carries some weight. The Saudi government-backed AI company has committed to deploying 200 megawatts of Qualcomm AI data center chips. Sanford C. Bernstein analyst Stacey Rasgon estimates that number translates to about $2 billion in revenue for Qualcomm.
Will $2 billion be transformative? This may seem modest given AMD’s $10 billion Humain deal announced the same year. But for companies looking to prove they belong in the AI infrastructure conversation, securing large-scale adoption commitments before the first product ships provides validation that money can’t buy.
“Together with Humane, we are laying the foundation for transformative AI-driven innovations that will power businesses, government agencies, and communities in the region and around the world,” Amon declared in a statement, positioning Qualcomm not only as a chip supplier but also as a strategic technology partner in the emerging AI economy.
The partnership, first announced in May 2025, will make Qualcomm the primary infrastructure provider for Humain’s ambitious AI inference services, helping establish key reference designs and deployment patterns for future customers.
Software stack and developer experience
Beyond hardware specifications, Qualcomm is betting on accelerating the adoption of developer-friendly software. The company’s AI software stack supports major machine learning frameworks and promises “one-click deployment” of models from Hugging Face, a popular AI model repository.
Qualcomm AI Inference Suite and Efficient Transformers Library aim to remove the integration friction that has traditionally slowed enterprise AI adoption.
David vs. Goliath (and another Goliath?)
Let’s be honest about what Qualcomm is fighting against. Nvidia’s market capitalization soared past $4.5 trillion. This is a valuation that reflects the years of AI dominance and an ecosystem so entrenched that many developers can’t imagine building on top of anything else.
Once a cantankerous challenger, AMD has managed to carve out a slice of the AI pie for itself, causing its stock to more than double by 2025.
Qualcomm’s late entry to the AI data center chip party means an uphill battle against competitors with proven products, mature software stacks, and customers already running large-scale production workloads.
Once the company’s biggest strength, its focus on smartphones now looks like strategic tunnel vision, which caused it to miss the nascent AI infrastructure boom. However, market analysts have not written an obituary for Qualcomm. UBS’s Timothy Arcuri captured the general sentiment on a conference call: “The tide is rising so fast and will continue to rise so fast that it’s going to lift all boats.” In short, the AI market is expanding so rapidly that there is room for multiple winners, even latecomers with attractive technology and competitive pricing.
Qualcomm is playing the long game, betting that continued innovation in AI data center chips can gradually win over customers looking for an alternative to the Nvidia-AMD duopoly. For companies evaluating AI infrastructure options, Qualcomm’s focus on inference optimization, energy efficiency, and TCO presents a noteworthy alternative, especially as the AI200 launch date approaches 2026.
(Photo provided by Qualcomm)
See: AI migration from Nvidia to Huawei: Opportunities and tradeoffs
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