Qualcomm lands Meta and Microsoft for new AI chips as it targets $15 billion data center business

Qualcomm claims it's not too late for Dragonfly to land in datacenters

We knew it was coming, but now it's official: Qualcomm is making a major push into the datacenter market. And though it is late to the game, the mobile-chip giant believes it can make an impact by delivering a lower total cost of ownership and better performance per watt than rival platforms. It has to go somewhere, and the company is already dominating the chip space elsewhere, Qualcomm's datacenter EVP and GM Tony Pialis said during the company's Investor Day presentation on Wednesday. Pialis said that Qualcomm is already a winner in mobile, PC, and automotive, but will now be able to play in a market with well established competitors such as Nvidia. He started by addressing the obvious question of "are you too late" to the market. "When the company turns its attention to solve a new problem, we revolutionize the solution and push our way to the forefront," he said. "And folks I'm here to tell you today that is what we will and are doing in datacenter." Pialis' portion of the presentation included the formal unveiling of the Dragonfly compute platform we've been hearing about for weeks, the ... ahem ... core of which is the C1000 CPU he showed off. Pialis claimed that the new datacenter-grade chips offer 2x better performance per watt and 30 percent more speed than competitors' processors. The CPU cores, Pialis explained, are based on Qualcomm's custom Oryon architecture and will operate at more than 5 GHz in a chiplet-based design featuring more than 250 cores. Most interestingly, Pialis argued that the design of the C1000 chips addresses the memory bottleneck facing AI datacenters with what Qualcomm is calling "High-Bandwidth Compute" (HBC) technology. Pialis described HBC as combining compute and memory more closely by integrating an XPU beneath a DRAM stack, claiming it delivers SRAM-like performance advantages inside a high-bandwidth memory package while reducing data movement and improving performance per watt. Those Dragonfly C1000 processors are expected to enter production in the second half of 2028. Qualcomm plans to offer multiple C1000 variants targeting agentic AI, general-purpose computing, and AI head-node workloads. But CPUs alone do not a datacenter pivot make, and Pialis said that there are three other datacenter segments Qualcomm is targeting along with new CPUs: connectivity, custom silicon designed for individual customers, and AI accelerators. There are also the aforementioned AI accelerators, which Qualcomm says will use its HBC technology to address memory bottlenecks in AI workloads. Microsoft CEO Satya Nadella and Meta CEO Mark Zuckerberg made guest appearances during Investor Day. Qualcomm said Microsoft plans to use its HBC-based AI accelerators, while Meta separately announced plans to deploy Dragonfly C1000 CPUs under a multi-generation agreement. Pialis also detailed new connectivity technologies that form part of the Dragonfly portfolio. According to Pialis, Qualcomm wants to enable new distances in cluster-to-cluster optical connectivity up to 20 kilometers with its new QAM16 coherent-lite optical modules. "We have everything you need to scale from millimeter technology to tens of kilometers," Pialis said. As for custom silicon, that'll involve making bespoke chips for what Pialis said will be Qualcomm's "highest tier of customer" who needs someone to design and fabricate AI and cloud DC CPUs from end to end. What Qualcomm is bringing on the hardware side will be supplemented by Modular, a company that develops AI software stacks. Qualcomm announced on Wednesday that it had reached an agreement to acquire Modular in order to flesh out the software side of its Dragonfly endeavors, which the company said will give it access to hundreds of billions in new market space. ®

Qualcomm says Microsoft, Meta will use its new AI chips

June 24 (Reuters) - Qualcomm (QCOM.O), opens new tab said on Wednesday that Microsoft (MSFT.O), opens new tab and Meta Platforms (META.O), opens new tab will use its new AI chips and that it will make custom chips for two other unnamed "hyperscalers." The San Diego-based company, which is the industry leader in smartphone chips, held an investor presentation to showcase its move into supplying AI chips for data centers as it tries to gain a foothold in a market dominated by Nvidia (NVDA.O), opens new tab. The shift reflects mounting pressure in the smartphone market, which has been squeezed by a memory chip shortage driven by surging demand for ⁠AI infrastructure, and major customers such as Apple (AAPL.O), opens new tab and Samsung (005930.KS), opens new tab developing chips in-house. Qualcomm on Wednesday said Microsoft will use its new category of chips that relies on cheap memory chips used in smartphones and laptops, instead of the pricey high-bandwidth chips used by Nvidia and SRAM memory used by Cerebras Systems (CBRS.O), opens new tab. The company calls the new category "High Bandwidth Compute" or HBC. "That is a tremendous value that we deliver to the industry in terms of performance per cost advantage," said Tony Pialis, Qualcomm's data center chief. Qualcomm said Meta will use its new CPU called Dragonfly C1000 that it has designed specifically for AI data centers, entering a market where both Arm Holdings and Nvidia are courting customers. Pialis also said Qualcomm has won two major customers -- called "hyperscalers" in the computing industry -- for whom it will make custom chips, with revenue starting before ⁠the end of this calendar year. "I have not had to push my way into hyperscale customers; they've been pulling us in," Pialis said, without naming the customers. CROWDED DATA CENTER CHIP MARKET Qualcomm, which has attempted to boost its data-center business multiple times, is re-entering a fast-growing, but hyper-competitive AI market full of large incumbents such as Nvidia, the newly minted Cerebras and other custom chip options including Amazon's (AMZN.O), opens new tab Graviton and Google's (GOOGL.O), opens new tab Axion, Bank of America ⁠analysts warned in a client note on Tuesday. Qualcomm said in April that it plans to begin shipping processors and other AI chips for data centers by year-end. It also said it was working with customers on three kinds of chips: central processing units, inference accelerators, and custom application-specific integrated circuits (ASICs), a segment ⁠that has been booming for rivals such as Broadcom (AVGO.O), opens new tab and Marvell (MRVL.O), opens new tab. AI inference -- running trained AI models -- has emerged as a key battleground. BofA analysts said they expect modest revenue of roughly $2 billion to $5 billion annually from Qualcomm's data center push by fiscal 2027-2028. Investors will be ⁠watching for updated long-term financial targets at the event, including Qualcomm's growth ambitions for its non-handset businesses. Attention is also likely to focus on its $4 billion all-stock deal for AI software startup Modular, announced earlier on Wednesday, which positions Qualcomm against Nvidia's proprietary CUDA software that has locked in millions of developers. Reporting by Anhata Rooprai in Bengaluru; Editing by Sayantani Ghosh and Sahal Muhammed Our Standards: The Thomson Reuters Trust Principles., opens new tab

Qualcomm announces AI data center CPU, signs Meta as first major customer

Qualcomm on Wednesday revealed a central processing unit for data centers called Dragonfly C1000, and said that Meta would use it when it starts production in 2028. The chipmaker said that the new data center CPU was built for agentic AI and focuses on offering computing performance without using too much power. The announcement, made at a Qualcomm presentation to investors, is another sign that the chipmaker best known for smartphone processors and modems is aggressively targeting the data center market. On Wednesday, Qualcomm said that it has a roadmap to target the quickly-growing market with several different products, including an AI chip and a product that will tie multiple chips together. "We just been executing, collecting assets, and when we got to this point, we feel that we have a comprehensive portfolio to enter the next phase of the data center," Qualcomm CEO Cristiano Amon said at the investor day. Shares of the chipmaker were down in trading on Wednesday. Qualcomm CFO Akash Palkhiwala said in an interview that Qualcomm already has business with nearly every hyperscaler through its smartphone chips and other existing products. "This is not a new relationship. It's the benefit of what we've delivered to them already on the edge, combined with the scale and the expertise and the confidence in Qualcomm, is what makes them engage with us on data center," Palkhiwala said.

Qualcomm lands Meta as first named customer for its Dragonfly data centre chips

Qualcomm signed Meta as the first customer for its Dragonfly C1000 data centre chip, due in 2028, and confirmed a $3.9bn Modular acquisition. Qualcomm has signed Meta as the first named customer for its new Dragonfly C1000 data centre processor, the strongest signal yet that the mobile chipmaker is serious about competing in the AI infrastructure market. The company announced the deal at its investor day in New York on Wednesday, alongside a new AI300 accelerator chip and its confirmed acquisition of AI software startup Modular for roughly $3.9 billion in stock. The Dragonfly C1000 is a general-purpose server processor designed to sit inside data centres alongside Qualcomm's AI accelerator chips. Meta has committed to using the C1000 and its successors across its facilities. The chip will not be available until 2028, meaning the partnership is a forward-looking commitment rather than an immediate deployment. The Dragonfly brand, which Qualcomm first revealed at Computex in early June alongside an ASIC supply deal with ByteDance, covers three product categories: data centre CPUs, AI inference accelerators, and custom silicon built with hyperscalers. Wednesday's event filled in the product details that the Computex teaser left out. On the accelerator side, Qualcomm added an AI300 chip to a lineup that already included the AI200 and AI250. The AI200, built on Qualcomm's Hexagon neural processing unit technology with direct liquid cooling and up to 768GB of LPDDR memory, is on track for initial customer shipments later this year. The AI250 is expected to follow in 2027. These accelerators are designed for inference, the process of running trained AI models at scale rather than training them from scratch. Qualcomm argues that its decades of mobile chip design give it an advantage in power efficiency, a claim that matters as data centres strain electricity grids worldwide. Whether that mobile expertise translates to data centre performance remains unproven at scale. The Modular acquisition, which TNW reported was nearing completion on Monday, is now confirmed at roughly four billion dollars in an all-stock transaction. Qualcomm will issue roughly 19 million shares to Modular's owners. The deal is expected to close in the second half of this year. Modular makes the Mojo programming language and the MAX inference engine, software that lets AI models run across chips from Nvidia, AMD, Intel, and Qualcomm without developers rewriting code for each processor. That is a direct challenge to Nvidia's CUDA platform, the software layer that has locked AI developers into Nvidia hardware for two decades. Breaking that lock-in is the central challenge for every company trying to compete with Nvidia in AI infrastructure. The strategic logic is straightforward. Qualcomm can design competitive chips, but without a software ecosystem that makes developers want to use them, the hardware alone is not enough. Modular's cross-platform tooling could give Qualcomm the kind of developer on-ramp it currently lacks. CEO Cristiano Amon framed the deal as part of an industry movement toward open, multi-vendor architectures. That framing positions Qualcomm as the anti-Nvidia, offering flexibility where Nvidia's CUDA demands loyalty. Qualcomm's ambition is large but its data centre track record is thin. The company generates the vast majority of its revenue from smartphone processors and modems, and its previous attempt to enter the server market with the Centriq processor in 2017 ended in a shutdown. The current push has more institutional support, a named hyperscaler customer in Meta, and a clearer market opportunity in AI inference, but the gap between investor day announcements and shipped revenue remains wide. The Meta partnership is notable for what it implies about diversification. Meta currently builds AI infrastructure primarily around Nvidia GPUs and has also invested in its own custom MTIA chips. Adding Qualcomm to that mix suggests Meta wants more supplier options as it scales inference, not that it is replacing Nvidia, which announced a multiyear strategic partnership with Meta earlier this year. Qualcomm shares have climbed about 30 percent this year on expectations that AI would open a second growth engine beyond smartphones. The investor day was designed to turn that expectation into a roadmap. With the Modular acquisition providing the software layer, Meta providing the first marquee customer, and the AI200 approaching shipments, the pieces are assembling on paper. Whether they assemble in practice depends on execution over the next two years. The C1000 does not ship until 2028, the Modular deal has not closed, and the AI accelerator lineup has no published benchmarks against Nvidia's current or upcoming hardware. Qualcomm is making the right moves to enter the market, but it is entering a race where Nvidia has a commanding lead and every major cloud provider is also designing custom silicon.

Qualcomm's AI Leap: New chips, meta partnership and the road ahead - Qualcomm's Biggest AI Bet Yet

Qualcomm's AI Leap: New chips, meta partnership & the road ahead 1/10 Qualcomm's Biggest AI Bet Yet Qualcomm has unveiled a new family of AI data center chips and systems, marking its biggest expansion beyond smartphones. With Meta signing on as its first major hyperscale customer, the company is positioning itself to compete directly with Nvidia in the booming AI infrastructure market. Qualcomm believes data center chips could become a multi-billion-dollar business by the end of the decade. (Sources: CNBC, Reuters, Financial Times, Yahoo Finance) 2/10 Breaking Free from Smartphones For decades, Qualcomm's fortunes have largely depended on the smartphone industry. Now, with handset growth slowing, the company is aggressively diversifying into AI infrastructure, enterprise computing, automotive and custom silicon. Management believes AI data centers represent its biggest long-term growth opportunity outside mobile devices. 3/10 Meet the Dragonfly C1000 At the center of Qualcomm's strategy is the Dragonfly C1000 CPU, designed specifically for AI data centers. Built on the company's Oryon CPU architecture, the processor is optimized for AI inference workloads. Qualcomm says the chip delivers high performance while using smartphone-inspired memory technologies that can reduce costs and improve power efficiency for cloud providers. 4/10 Meta Becomes the First Big Win Meta has emerged as Qualcomm's first major hyperscale customer for its new AI data center processors. The social media giant plans to begin deploying the chips in its AI infrastructure from late 2028. Qualcomm also revealed that two additional hyperscale customers have committed to using its custom chips, although their identities have not yet been disclosed. 5/10 Chasing a Massive AI Opportunity Qualcomm has significantly raised its long-term financial ambitions. The company expects its data center business to generate around $5 billion in revenue by fiscal 2027 and grow to $15 billion annually by 2029. It also projects that non-smartphone revenues will nearly double to $40 billion by the end of the decade, reflecting its confidence in AI-driven growth. 6/10 The Competition Is Fierce Qualcomm is entering one of the technology industry's most competitive markets. It will compete against established players such as Nvidia, AMD, Broadcom, Marvell, Amazon and Google, all of which are investing heavily in AI infrastructure. As demand for AI inference grows rapidly, chipmakers are racing to deliver faster, more efficient and cost-effective solutions for cloud customers. 7/10 More Than Just CPUs Qualcomm's strategy extends beyond traditional processors. The company is developing AI CPUs, AI inference accelerators and custom AI chips tailored to the specific needs of cloud providers. This broader product portfolio is designed to help Qualcomm address multiple segments of the AI infrastructure market while offering customers greater flexibility. 8/10 Software Matters Too To strengthen its AI ecosystem, Qualcomm has acquired AI software startup Modular. The acquisition will help developers run AI models efficiently across different chip architectures without rewriting software. By expanding its software capabilities, Qualcomm hopes to build a stronger platform that can better compete with Nvidia's well-established CUDA ecosystem 9/10 Investors Cheer the Strategy Investors responded positively to Qualcomm's AI roadmap. The company's higher revenue targets, major customer wins and expanding product portfolio boosted confidence in its long-term growth strategy. The announcement also helped lift sentiment across semiconductor stocks, highlighting continued optimism around AI infrastructure spending. 10/10 Key Takeaways Qualcomm is making its most ambitious move yet into AI data centers with the launch of the Dragonfly C1000 platform and a growing portfolio of AI chips. Meta's adoption of the technology provides an important early validation of the company's strategy. If Qualcomm achieves its revenue targets, AI infrastructure could become a major growth engine and significantly reduce its reliance on the smartphone business.

Qualcomm Dragonfly Ecosystem Enables AI Accelerators, Custom Silicon, Networking To Empower Next-Gen AI Factories With A One-Stop & Scaled Compute Platform

Qualcomm Dragonfly brings a robust platform of AI Compute accelerators, CPUs, breakthrough technologies, networking, & custom-silicon under one roof. Enter The Dragon - Qualcomm's New Dragonfly Brand Is Primed For AI, Offering A Full-Stack Datacenter Portfolio, Encompassing Connectivity, CPU, and AI Accelerators The Computex 2026 teaser of the Dragonfly brand is now being officially unveiled as a full-stack data center ecosystem, driving next-generation AI and general-purpose compute. In our previous posts, we talked about the Dragonfly C1000 CPU and the Dragonfly HBC memory solution. Now, we will look at what the initiative has on offer beyond those two technologies, and to start, we first have the Qualcomm Dragonfly AI accelerators. Qualcomm Dragonfly AI300 (Card and Rack) The Qualcomm AI platform already saw the introduction of the AI200 and AI250 accelerators last year. The AI200 accelerators are being sampled now, and AI250 is on track for 2027. The AI250 AI accelerator will be the first to accommodate the HBC Gen1 solution, offering up to 43TB of LPDDR capacities in air and direct-liquid cooling designs. While the capacities remain the same as AI200 (LPDDR5X), with HBC, AI250 will offer an 18x boost in effective bandwidth and 5x the bandwidth per watt. By 2028, Qualcomm is expected to sample its next-generation AI300 compute accelerator series. These will retain the air and direct-liquid cooling rack options, and the breakthrough will be the introduction of the second-generation HBC called HBC Gen2. This further raises the bar of what HBC can do with a 54x boost in effective bandwidth versus the AI200 and 8x bandwidth per watt versus HBM-based solutions. For AI300, Qualcomm is also investing in scale-up architectures with the inclusion of UALink (Ultra Accelerator Link) and ESUN (Ethernet Scale-Up Networking), & Scale out with copper and optical infrastructure. The following are the full highlights: * Third-generation, air- and direct-liquid-cooled rack-level AI inference platform - following the introduction of the AI200 and AI250 solutions last October * AI300 integrates breakthrough Qualcomm HBC Gen 2 technology for compute acceleration with integrated memory and increased effective memory bandwidth, designed for disaggregated inference deployments (AI250 uses HBC Gen 1) * Enables industry-leading memory capacity and effective bandwidth, enabling high-throughput, low-latency performance for large language & multimodal model (LLM, LMM) inference and agentic AI workloads * Expecting 4x-8x better performance-per-watt compared to existing GPU-based architectures on memory bandwidth per watt per card * Scale up with UALink (Ultra Accelerator Link) and ESUN (Ethernet for Scale-Up Networking); scale out with copper and optical * Commercial sampling is expected in 2028 Qualcomm Dragonfly Connectivity Platform On the connectivity front, Qualcomm aims to broaden its solution offering with die-to-die, copper, optical, and campus reach interconnects. The company will harness leading-edge process nodes to deliver 112 Gbps, 224 Gbps, and up to 448 Gbps SerDes through active electrical cables within & between the racks. We also see the mention of Co-Packaged Optics & Network Packaged Optics, which shows that Qualcomm is also keen on entering the silicon photonics race, which is already being set up between the likes of NVIDIA and AMD. For Scale-Out, a new QAM16 Coherent-lite optical solution is being developed with a range of up to 20 kilometers, while PAM4 Optical SerDes enables optical speeds at up to 2km. In the 2026-2027 timeline, Qualcomm's Dragonfly Connectivity lineup will see the addition of the O200 (1.6T Optical Modules/ACOs) and CU200 (1.6T AECs), while 2028 will see the introduction of next-generation CO1600 (1.6T-LR/3.2T-FR2), O400 (3.2T Optical Modules), and CU400 (3.2T AECs). * Broad connectivity portfolio spanning die-to-die, copper, optical, and campus-reach interconnects for next-generation AI data centers * Supports high-bandwidth 800G and 1.6T connectivity across optical, AOC, and AEC applications, from intra-data-center links to campus-reach deployments up to 20 km * Combines Qualcomm Technologies' SerDes, PAM4, coherent-lite DSP, signal integrity, and telemetry capabilities to support scalable, high-performance AI infrastructure * Addresses data movement bottlenecks that are central to AI data center performance in increasingly distributed, disaggregated, and bandwidth-intensive infrastructure Custom-Silicon Solutions Available To All Qualcomm is also going big in the custom-silicon space. The company will offer performance-optimized silicon, end-to-end co-design capabilities, advanced packaging solutions, a proven IP stack, and full execution (including design and high-volume production) to its customers. We've already seen reports about Qualcomm working with custom chip design with Chinese firms, & the official announcement means that the company is already talking to multiple firms for custom-silicon development. * Performance-optimized silicon at scale for next-generation AI and cloud data center infrastructure * Bespoke custom silicon for agentic AI and other specialized workloads * End-to-end co-design capabilities across silicon, system, and software to address customer-specific performance, power, and integration requirements * Advanced packaging and modular architectures designed to improve performance, power efficiency, and scalability * Proven IP and streamlined design execution to support faster time-to-market and reduced execution risk * Execution from design through high-volume manufacturing, supported by ecosystem and supply chain relationships Qualcomm's Dragonfly platform marks a bold and comprehensive entry into the AI data center space, delivering a true full-stack solution that brings together high-performance AI accelerators, next-generation connectivity, advanced memory, and custom silicon under one roof. As the Dragonfly ecosystem matures through 2027-2028, it has the potential to become a powerful, cost-effective alternative for hyperscalers and enterprises seeking high-performance, power-efficient AI solutions. The Dragon has officially entered the arena. Follow Wccftech on Google to get more of our news coverage in your feeds.

AI chips: Qualcomm forecasts $15 billion data center chip sales by 2029, shares soar

Qualcomm also said it expects $40 billion in revenue from chips outside its smartphone stronghold by 2029, up from previous estimates of $22 billion, ⁠and ⁠with handsets only making up a third of its chip revenue by then. Qualcomm said it expects to generate $15 billion in sales from its data center business by 2029 as it moves beyond its core smartphone chips, sending shares more than 12% higher in after-hours trading on Wednesday. Chief Financial Officer Akash Palkhiwala said at an investor presentation that the data center business will bring in $5 billion for fiscal 2027, with $1 billion coming from the new custom-chip customers. Qualcomm also said it expects $40 billion in revenue from chips outside its smartphone stronghold by 2029, up from previous estimates of $22 billion, ⁠and ⁠with handsets only making up a third of its chip revenue by then. "We will be truly diversified," Palkhiwala said. Arm Holdings, which supplies underlying technology for many Qualcomm chips, also rose 5% after the forecast. Bank of America analysts had earlier said they expect modest revenue of roughly $2 billion to $5 billion annually from Qualcomm's data center push by fiscal 2027-2028. META, MICROSOFT AMONG CUSTOMERS Earlier in the day, Qualcomm said Microsoft and Meta Platforms will use its new AI chips and that it will make custom chips for two other unnamed "hyperscalers." Qualcomm's shift to AI chips reflects mounting pressure in the smartphone market, which ⁠has been squeezed by a memory chip shortage driven by surging demand for AI infrastructure, and major customers such as Apple and Samsung developing chips in-house. The chipmaker on Wednesday said Microsoft will use its new ⁠category of chips that relies on cheap memory chips used in smartphones and laptops, instead of the pricey high-bandwidth chips used by Nvidia and SRAM memory used by Cerebras Systems. The company calls the new category "High Bandwidth Compute" or HBC. "That is a tremendous value that we deliver to the industry in terms of performance per cost advantage," said Tony Pialis, Qualcomm's data center chief. Qualcomm said Meta will use its new CPU called Dragonfly C1000 that it has designed specifically for AI data centers, entering a market where both Arm Holdings and Nvidia are courting customers. Pialis also said Qualcomm has won two major customers - called "hyperscalers" in the computing industry - for whom it will make custom chips, with revenue starting before the end of this calendar year. "I have not had to push my way into hyperscale customers; they've been pulling us in," Pialis said, without naming the customers. CROWDED DATA ⁠CENTER CHIP MARKET Qualcomm, which has attempted to boost its data-center business multiple times, is re-entering a fast-growing, but hyper-competitive AI market full of large incumbents such as Nvidia , the newly minted Cerebras and other custom chip options including Amazon's Graviton and Google's Axion, Bank of America analysts warned in a client note on Tuesday. Qualcomm said in April that it plans to begin shipping processors and other AI chips for data centers by year-end. It also said it was working with customers on three kinds of chips: central processing units, inference accelerators, and custom application-specific integrated circuits (ASICs), a segment that has been booming for rivals such as Broadcom and Marvell. AI inference - running trained AI models - has emerged as a key battleground.

Qualcomm Claims Single-Core Leadership for Its First Server CPU, the Dragonfly C1000, Delivering 250+ Cores & 5 GHz By 2028

Qualcomm has introduced its first-ever CPU designed for Data Centers, the Dragonfly C1000, which leverages the Oryon architecture. Qualcomm Enters The Agentic AI CPU Race With Dragonfly C1000 Chip, Oryon-Based With Over 5 GHz Clocks, Over 250 Cores, & Aims To Achieve Single-Core Leadership One of the biggest announcements by Qualcomm today was its first release of a CPU for the data center segment, called the Dragonfly C1000. This is a chip purpose-built for Agentic AI & General-Purpose workloads, delivering best-in-class power efficiency and TCO. As per Qualcomm, the Dragonfly C1000 is based on a custom-designed Oryon core architecture that is optimized for core performance and delivers frequencies beyond 5 GHz, offering superior performance in agentic workloads deployed at scale. Qualcomm also claims that the chip is going to offer leadership single-threaded performance. In terms of specifications, the Qualcomm Dragonfly C1000 CPU will offer a multi-chiplet design, allowing it to align with leading-edge advanced packaging technologies for performance and IO scaling. The primary CPU chiplet will feature over 250 cores, offering throughput and scale while delivering the aforementioned "exceptional per-core" performance. Performance-wise, the chips are said to be over two times better in terms of perf/watt when compared to existing server CPUs. The company doesn't disclose any direct comparisons or benchmarks yet. Each CPU will offer over 2 TB/s of PCIe Gen7 connectivity, CXL connectivity & support for next-generation accelerators such as Qualcomm's very own AI series products. CPU portfolio includes: agentic CPU designed for high-throughput agentic orchestration and low latency interactive AI use cases; general-purpose CPU designed for optimal performance-per-TCO for first-party workload and performance-per-vCPU for third-party usage elasticity; AI head node CPU designed to maximize XPU utilization of XPU for generative AI compute through low overhead host processing through high-speed CPU Just like its AI accelerator portfolio, the Dragonfly C1000 CPUs will come with an optional HBC attach to boost their memory capacity and bandwidth capabilities. From a security standpoint, the C1000 chips will integrate advanced reliability, availability, and serviceability (RAS) features, including ECC memory correction, fault isolation, and error recovery. The first platforms based on these chips will feature both air and liquid cooling support in OCP ORv2 compliant racks and servers. Qualcomm has set the commercial availability of C1000 for 2028. Qualcomm is all set to enter the $200B CPU server TAM by the time Dragonfly C1000 launches, bringing a multi-generational portfolio that is expected to win major hyperscaler adoption. Follow Wccftech on Google to get more of our news coverage in your feeds.

Qualcomm introduces Dragonfly C1000 data center CPU, Dragonfly AI300 Accelerator and more

At its annual Investor Day, Qualcomm Technologies, Inc. announced a major expansion into full-stack data center infrastructure, debuting a roadmap of AI-focused processors, custom silicon solutions, and high-speed connectivity products. The hardware portfolio -- spanning the Qualcomm Dragonfly C1000 CPU, Dragonfly AI300 inference accelerator, and an architecture dubbed Qualcomm High Bandwidth Compute (HBC) -- marks the company's formal push to challenge incumbent silicon providers in hyperscale data center infrastructure. Alongside the product reveals, Qualcomm announced a multi-generation agreement to supply its upcoming data center CPUs to Meta. The Silicon Portfolio: Powering Agentic AI Qualcomm is positioning its new lineup as an "inference-first" platform optimized for agentic AI -- autonomous AI workloads requiring high token throughput, continuous reasoning, and minimal latency. Qualcomm Dragonfly C1000 CPU The bedrock of the compute announcement is the Dragonfly C1000, a purpose-built data center CPU. * Core Architecture: Built using custom-designed Qualcomm Oryon CPU cores, the chip utilizes a multi-chiplet architecture featuring a core count of over 250 cores. * Clock Speeds: Core frequencies are rated at greater than 5 GHz to handle high-throughput agentic orchestration and general-purpose server workloads. * I/O and Interconnects: The architecture delivers greater than 2 TB/s of PCIe Gen 7 and CXL connectivity to facilitate next-generation memory disaggregation. * Efficiency: Qualcomm estimates the platform will achieve greater than 2x better performance-per-watt compared to existing benchmarked competitive server CPUs. * Timeline: Commercial availability for the Dragonfly C1000 is targeted for 2028. Qualcomm High Bandwidth Compute (HBC) To bypass traditional memory data movement bottlenecks, Qualcomm introduced High Bandwidth Compute (HBC), a near-memory 3D-stacked silicon architecture intended as an alternative to High Bandwidth Memory (HBM). According to Qualcomm, HBC is designed to offer a 6x increase in bandwidth-per-watt compared to standard HBM specifications normalized at the card level, alongside a 200x increase in capacity-per-watt versus SRAM at the rack level. * HBC Gen 1: Integrated into the previously announced AI250 accelerator, it is designed to achieve 133 TB/s per card -- an 18x effective memory bandwidth increase over LPDDR5X-based AI200 solutions. Commercial sampling begins in mid-2027. * HBC Gen 2: Integrated into the newly announced AI300, it is designed to offer a 54x increase in effective bandwidth over the AI200 line. Qualcomm Dragonfly AI300 Accelerator The Dragonfly AI300 represents Qualcomm's third-generation rack-level AI inference platform. Compatible with Ultra Accelerator Link (UALink) and Ethernet for Scale-Up Networking (ESUN), the AI300 is designed for large language model (LLM) and multimodal model inference. The platform is projected to yield a 4x to 8x performance-per-watt advantage over existing GPU-based architectures on memory bandwidth metric scales. Commercial sampling is expected in 2028. Custom Silicon and High-Speed Connectivity Expanding beyond standard platforms, Qualcomm disclosed an end-to-end custom silicon business to design and manufacture bespoke chips for specific cloud infrastructure workloads. This initiative leverages the company's existing IP portfolio and packaging pipelines to manage execution risks from initial design to high-volume manufacturing. Supporting this infrastructure is a new optical and copper connectivity portfolio. Capable of handling high-bandwidth 800G and 1.6T networking, these interconnects scale from short-reach intra-data-center links up to campus-reach deployments spanning 20 kilometers. The networking stack utilizes Qualcomm's internal SerDes, PAM4, and coherent-lite DSP technologies to maintain signal integrity across distributed, disaggregated environments. Meta Partnership and Ecosystem Adoption A cornerstone of Qualcomm's data center strategy is a newly solidified, multi-year collaboration with Meta. Under the agreement, Qualcomm will act as a silicon supplier for Meta's data center CPUs, with the Dragonfly C1000 slated to power portions of Meta's next-generation scale-out server fleet. Beyond Meta, Qualcomm highlighted ecosystem backing from over 35 technology hardware, infrastructure, and semiconductor partners. The list includes server manufacturers, memory vendors, and testing providers such as: * Infrastructure & Hardware: Supermicro, Lenovo, GIGABYTE Technology, Foxconn, Arista, and Quanta. * Memory & Storage: Samsung SDS, Micron Technology, SK hynix America, and Nanya Technology. * Semiconductor & Design Ecosystem: Microchip Technology, Advantest, Teradyne, and UMC. Qualcomm stated that it remains committed to an annual cadence for its data center roadmap, focusing future updates on compounding metrics for AI inference execution, energy efficiency, and total cost of ownership reduction. Cristiano Amon, President and CEO, Qualcomm Incorporated, said: Agentic AI is driving a significant increase in demand for AI inference in the data center. As these become the dominant workloads, infrastructure has to deliver much higher performance at lower power and cost. That plays directly to Qualcomm's strengths, and we're well positioned for this shift. With Qualcomm Dragonfly, we're bringing our high-performance, low-power computing into the data center, with multi-year, multi-generation agreements with leading customers.

Qualcomm Pivots to Datacentre Chips, Forecasts $15Bn in Sales by 2029

The shift from smartphones to datacentre solutions is a result of companies like Apple using their own processors in their handheld devices Tech giant Qualcomm would be expanding into the lucrative AI and datacentre market with a new range of processors under the Dragonfly range. The company is expecting to generate $15 billion in sales from this business by 2029 as it broadens beyond its core smartphone chips offerings due to pressures in the smartphone markets. These offerings include the Dragonfly C1000 CPU, Qualcomm High Bandwidth Compute (HBC) and the Dragonfly AI300 inference accelerator, in addition to some custom silicon products. Over the next four years, the company expects sales to mobile phone industry to drop to about a third of its total turnover. In fact, the company expects $40 billion in revenues from chips outside the smartphone suite, up from previous estimates of around $22 billion. Chief Financial Officer Akash Palkhiwala told investors that the datacentre business will accrue $5 billion in 2027. "We will be truly diversified," Palkhiwala said. Amidst these reports, Qualcomm also note that both Microsoft and Meta Platforms would be using their new AI chips whereas it would also be designing and producing custom chips for two other hyper-scalers. However, the company did not name who they are. The company also indicated that Microsoft would be using the new category of chips that relies on lower cost memory used in smartphones and laptops instead of the high-priced chips sold by Nvidia and the SRAM memory provided by Cerebras Systems. The company has christened the new category as "High Bandwidth Compute" or HBC. Of the $40 million revenues targeted by 2029, Qualcomm hopes to raise $10 billion from the automotive segment, more than $14 billion from IoT applications like personal computers, robotics and industrial equipment, and over USD 15 billion from datacentres. The company's new Dragonfly CPU range is built on the Oryon CPUs where Qualcomm has made inroads into the PC market with their Dragonfly C1000 already optimized for core performance and frequencies over 5GHz to support large agentic workloads. They claim that these can deliver 2x better performance per watt compared to current benchmarks. "That is a tremendous value that we deliver to the industry in terms of performance per cost advantage," said Tony Pialis, Qualcomm's datacentre boss. Additionally the company hopes to generate revenues from before the end of 2026. "I have not had to push my way into hyperscale customers; they've been pulling us in," Pialis said. Qualcomm had announced their first AI inference chips last year with the AI200 and AI250 that would rollout sometime in 2026 and 2027 respectively. Now, the company is coming out with its next version in the form of AI300 that should start shipping in 2028. Qualcomm believes that this should deliver four to eight times better performances.