The Muse AI craze ignites the "Dual Growth Engine of Cloud and Edge"! Snapdragon dual flagships help Qualcomm (QCOM.US) achieve the best monthly increase since May

According to Zhitong Finance APP, long known for focusing on smartphone chips, semiconductor giant Qualcomm (QCOM.US) is now actively increasing its stake in self-developed AI inference chips and data center CPUs. The underlying logic behind Qualcomm’s recent strong stock performance is no longer merely the “smartphone chip cycle bottoming out”; instead, the market is starting to reprice its potential core position in the two main AI computing investment lines—data center CPUs/self-developed AI inference chips and on-device AI agent hardware. As of the U.S. stock market close on Monday, Qualcomm’s share price has surged up to 35% since August, with its market cap hovering around $210 billion. This clearly shows that the market is starting to assign Qualcomm a significant premium as a “rising force in AI computing infrastructure,” rather than valuing it simply as a traditional smartphone SoC chip company.

Qualcomm’s management is actively seeking to capitalize on the ever-growing demand for computing resources in the era of large-scale proliferation of on-device AI and AI agent technology. Following the release of Qualcomm’s latest flagship Snapdragon processor, the company has attracted significant attention from retail traders. Some Wall Street analysts have pointed out that as the chip industry increasingly shifts towards AI agent computing demand and capacity, chips targeting large-scale AI data centers are poised to become another growth driver for the company.

With state-of-the-art AI agent work systems such as Muse and Astra expanding the scope of business tasks that can be automated, computing demands are now extending beyond single Q&A interactions to highly complex, continuously running intelligent agent workflows. This global expansion of AI compute demand is expected to drive a new boom, with Qualcomm’s AI chip and data center CPU demand anticipated to simultaneously expand along both AI computing lines. This has sent Qualcomm’s stock price up by over 10% so far this week.

Qualcomm’s entry into data center AI chips centers around targeting massive AI inference workloads, with a technological breakthrough focusing on reducing data transfer overhead and the cost per effective output token. The server CPU business enables Qualcomm to participate in another key phase of agent computing. The Dragonfly C1000, using Qualcomm’s self-developed Oryon core, is targeted at task orchestration, general-purpose computing, and AI host nodes. Qualcomm has reached a multi-generation CPU collaboration agreement with Meta, with the first generation slated for mass production in the second half of 2028, providing a customer base for mid- to long-term demand expectations. Notably, the first-gen C1000 CPU co-developed by Qualcomm and Meta is scheduled for mass production in the second half of 2028.

Seizing Growth Opportunities in the AI Era! Qualcomm’s Stock Set for Best Monthly Performance Since May

Qualcomm’s management is actively working to capture the growing demand for computing resources in the age of widespread on-device AI and agent-style workflows. The company’s stock dipped slightly, by 0.4%, during pre-market trading on Wednesday, but it remains well positioned to post its strongest monthly performance since May.

Daniel Newman, CEO of Futurum Group, noted that Qualcomm has already benefited from the intelligent agent AI boom through its data center business, which covers AI inference chips and data center CPU capacity planning. This could prompt the market to raise expectations for high-performance CPUs, high-performance Ethernet network equipment, and AI computing core accelerators in data centers. However, he emphasized that investors should not overlook opportunities in the smartphone and other devices sectors.

Newman wrote on X: “It’s hard to ignore this point: Qualcomm is also set to benefit from the rapid rise of Muse, Grok Bot, and Instinct.” He added, “Devices with agent functions will get a boost”—regardless of which application ultimately leads in the on-device AI agent competition, it will create a new growth driver for Qualcomm.

Meta’s newly launched Muse AI agent, as well as the personal AI agent Instinct, exemplify the industry’s shift to autonomous AI. Instinct is known, for example, for handling real-world tasks such as managing emails, and reportedly the company is seeking funding at a $10 billion valuation, while Muse has won acclaim from users and analysts alike.

Meanwhile, Neil Shah is focused on Qualcomm’s decision to introduce two Snapdragon flagship tiers. He wrote on X: “This kind of product positioning and segmentation by Snapdragon is quite interesting.” He added that, as OEMs—particularly Chinese smartphone manufacturers—consider how to differentiate their devices, this strategy could become increasingly meaningful.

The two Snapdragon chips are squarely targeting the era of on-device AI and AI agents. At the Snapdragon Summit this week, Qualcomm announced the Snapdragon 8 Elite Extreme Gen 6 and Snapdragon 8 Elite Gen 6. Both chips use a 2nm process and support on-device AI, gaming, imaging, and connectivity features.

The Snapdragon 8 Elite Extreme Gen 6 is Qualcomm’s top-tier chip, featuring a 5GHz Oryon CPU with faster AI and graphics processing, as well as advanced gaming and imaging capabilities. The standard Gen 6 model also clocks at 5GHz, with a 10% CPU uplift, 35% GPU gain, and 14% NPU improvement over the previous generation.

Shah noted that these differences “may not look huge on the spec sheet,” but he believes that advanced agent AI and gaming features could provide tangible performance differentiation.

Additionally, it’s worth noting that Qualcomm has hired Sergio Buniac, former president of Motorola’s devices business, to lead its mobile, compute, and Extended Reality (XR) business. Buniac worked at Motorola for more than 30 years and became president of the device division in 2018.

His responsibilities will extend to Qualcomm’s next-generation AI devices. As Qualcomm seeks to expand the reach of Snapdragon beyond smartphones and further into the emerging on-device AI agent ecosystem, this appointment brings the company an executive with deep experience in taking consumer devices from design to commercialization.

As of early Wednesday Eastern Time, retail sentiment for Qualcomm on Stocktwits remains “bullish,” unchanged from earlier in the week. At the time of writing, the stock ranks among the top ten hottest on the platform.

A senior retail trader posted on Stocktwits: “Samsung is expected to be the first major partner to launch devices with the standard edition chip, with reports naming Galaxy S27 and Galaxy Z Fold 9 as the inaugural models.” “Besides Samsung, Xiaomi, OnePlus, and iQOO are also rumored to be early adopters of these new chips.”

Agent-driven Compute Expansion: Qualcomm Embraces Dual Opportunities in Edge and Cloud

The core shift brought by cutting-edge agents such as Muse and Astra is expanding one-off Q&A tasks into full workflows involving continuous inference, tool calling, code execution, and results verification. From a system architecture perspective, as more tasks are offloaded to agents, accelerators must handle model computation, CPUs coordinate orchestration, browser operations, software tools, and execution environments, while memory and networking store context and transfer data. This is driving the need for AI infrastructure to span more chip types, opening the market for both Qualcomm’s inference accelerators and server CPUs.

For the AI agent hype fueling the expansion of data center CPU demand globally, the key bullish investment logic on Qualcomm lies in: improved agent capabilities expanding the scope of monetizable tasks, more users, higher usage frequency, and longer workflows all together boosting compute resource demand. Qualcomm’s disclosed Dragonfly roadmap now lists agent processing, inference acceleration, and high-speed interconnect as the core vectors of its data center business.

On the edge, agents must continuously sense personal context, respond quickly, and call apps, all while meeting strict mobile constraints for battery life and heat dissipation. Thus, performance per watt, heterogeneous compute scheduling, and local processing capacity directly affect user experience. Qualcomm’s Oryon CPU, Adreno GPU, and Hexagon NPU can assign AI compute tasks relating to control, graphics, and adaptation: lightweight inference and personal data processing occur on-device, while more complex tasks are handled by calling cloud models via the network. This edge-cloud collaboration adds new product value to the Snapdragon platform. According to Qualcomm’s generational comparisons, the flagship Extreme model’s NPU performance is up 35% and performance per watt up to 33%, meaning more complex AI features can run continuously within tight power and thermal limits.

Compared with Nvidia/AMD’s AI GPU compute systems and Google’s TPU compute architecture, Qualcomm’s focus in data center AI chips is inference, with the technological breakthrough centering on reducing data shuttling overhead and cost per effective output token. State-of-the-art AI foundation models and agent workflows increasingly require frequent reading of model weights and growing key-value caches as context expands; especially in low-batch, low-latency decoding scenarios, memory bandwidth and capacity often become bottlenecks.

This is why the Qualcomm AI200 AI chip employs a large-capacity, low-power memory approach, and the AI250 further introduces HBC near-memory computing, using 3D integration to bring computation and memory closer, thus reducing the energy associated with data transfer. Its core competitive edge lies in: by meeting output quality, latency, and throughput requirements, it increases the inference throughput per unit of power, thereby improving total data center ownership cost. According to the official roadmap, the first HBC-equipped AI250 is expected to reach commercial sampling in mid-2027.

The data center server CPU business also enables Qualcomm to participate in another key stage of agent computing. The Dragonfly C1000, featuring Qualcomm’s in-house Oryon core, targets task orchestration, general-purpose processing, and AI host nodes. Qualcomm has reached a multi-generation CPU deal with Meta, with the first-gen product due for mass production in the second half of 2028, building the customer base for mid- to long-term demand expectations.

Additionally, in September, Qualcomm announced a multi-generation custom chip partnership with Amazon, focusing on AI inference and supporting up to 1.6T and future optical interconnect solutions. These latest moves by AI computing ecosystem leaders like Qualcomm underline this investment thesis: On-device agents add value to high-end Snapdragon platforms, while cloud-based agents broaden the market for inference accelerators, server CPUs, and interconnect products. As customer projects begin volume production, Qualcomm is positioned to translate low-power design expertise from mobile computing into data center revenue, expanding its long-term growth drivers.

On Wall Street, some analysts have set a 12-month price target of $400 for Qualcomm—implying potential upside of about 101.75% and marking the highest street target. Baird analyst Tristan Gerra recently raised Qualcomm’s target from $300 to $400 and maintained an “Outperform” rating. Gerra's $400 target bets on the combined benefits of “opening new markets for data centers + revenue diversification + upgraded agent smartphones,” driving both earnings growth and a re-rating. Gerra projects Qualcomm’s data center revenue will hit $5 billion in fiscal 2027—roughly 11% of total revenue—meaning the AI infrastructure business is about to make a material impact on overall results.