Muse agent frenzy ignites the "dual growth engine of device and cloud"! Snapdragon dual flagships help Qualcomm (QCOM.US) charge toward its best monthly gain since May.

Title context: Muse agent frenzy ignites the "dual growth engine of device and cloud"! Snapdragon dual flagships help Qualcomm (QCOM.US) charge toward its best monthly gain since May. Text: The semiconductor giant Qualcomm (QCOM.US), long focused on smartphone chips, is actively increasing its bets on self-developed AI inference chips and data center CPUs. The underlying logic behind Qualcomm's recent strong stock price is no longer just the single narrative of "the agent smartphone chip cycle bottoming out," but rather that the market has begun to reprice its potential core position in the two major AI computing investment themes: data center CPUs/self-developed AI inference chips + on-device AI agent devices. As of Monday's U.S. stock market close, Qualcomm's stock price has risen as much as 35% since August, with its market capitalization hovering near $210 billion, which is enough to show that the market has clearly begun to assign a strong premium to its positioning as an "emerging force in AI computing infrastructure," rather than valuing it solely as a traditional smartphone SoC chip company. Qualcomm's management is actively seeking to capture the growing demand for computing resources in the era of large-scale penetration of on-device AI and AI agents. After QUALCOMM Incorporated released its latest flagship Snapdragon processors, it is receiving active attention from retail traders. Some Wall Street analysts have pointed out that as the chip industry increasingly shifts toward AI agent computing demand/capacity, these chips focused on large-scale AI data centers are expected to become another growth driver for the company. As cutting-edge AI agent workflow systems such as Muse and Astra expand the range of business tasks that can be completed automatically, they also extend computing demand from single-turn Q&A to extremely complex agent workflows that require continuous, highly efficient operation. Global AI computing demand is expected to usher in a new round of expansion, and expectations for Qualcomm AI chip and data center CPU demand are showing a dual-line expansion trend in AI computing power, driving Qualcomm's stock price up more than 10% so far this week. Qualcomm's push into data center AI chips focuses on massive-scale AI inference workloads, with the technical breakthrough being to reduce data movement overhead and the cost per effective output token. The server CPU business allows Qualcomm to participate in another key link in agent computing. The Dragonfly C1000, using self-developed Oryon cores, targets task orchestration, general-purpose computing, and AI host nodes. Qualcomm has reached a multi-generation CPU cooperation with Meta, with the first-generation product planned to begin mass production in the second half of 2028, providing a customer base for its medium- to long-term demand expectations. It is reported that the first-generation C1000 CPU under Qualcomm's cooperation with Meta is planned to begin mass production in the second half of 2028. Seizing the growth opportunities of the AI era! Qualcomm's stock price is expected to post its best monthly performance since May. Qualcomm's management is actively seeking to capture the growing demand for computing resources in the era of large-scale penetration of on-device AI and AI agent technologies focused on complex agentic workflows. The company's stock price fell slightly by 0.4% in pre-market trading on Wednesday but remains very much on track to post its best monthly performance since May. Daniel Newman, CEO of Futurum Group, said that Qualcomm's data center business, covering AI inference chips and data center CPU capacity planning, has already benefited from the agentic AI boom, which may drive the market to raise expectations for data center high-performance CPUs, high-performance Ethernet networking equipment, and AI computing core accelerators. However, he said investors should not overlook opportunities in smartphones and other device areas. Newman posted on X: "It's hard to ignore this point: Qualcomm is also expected to benefit from the rapid rise of Muse, Grok Bot, and Instinct." He added that "agent-capable devices will get a boost," and no matter which application ultimately wins in the on-device agentic AI competition, it will create another growth driver for Qualcomm. Meta's newly launched Muse AI agent, as well as the personal AI agent Instinct, are prominent examples of the industry's shift toward autonomous AI. Instinct is known for handling real-world tasks such as email, and the company is reportedly seeking financing at a $10 billion valuation; meanwhile, Muse has received praise from users and analysts. Meanwhile, Neil Shah focused on Qualcomm's decision to launch two flagship tiers. He said on X: "This kind of product positioning and tiering for Qualcomm Snapdragon is quite interesting." He added that this strategy may make more sense as original equipment manufacturers, especially Chinese smartphone makers, consider how to differentiate their devices. The two Snapdragon chips are fully aimed at the era of on-device AI and AI agents. Qualcomm released the Snapdragon 8 Elite Extreme Gen 6 and Snapdragon 8 Elite Gen 6 at the Snapdragon Summit this week. 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, equipped with a 5GHz Oryon CPU, faster AI and graphics processing performance, and advanced gaming and imaging capabilities. The standard Gen 6 also reaches 5GHz, with CPU performance improved by 10%, GPU performance by 35%, and NPU performance by 14% compared with the previous generation. Shah said these differences "may not look significant on a spec sheet," but he believes advanced agentic AI and gaming features could become meaningful performance differentiators. In addition, it is worth noting that Qualcomm said it has hired Sergio Buniac, former president of Motorola's devices business, to lead the company's mobile, computing, and extended reality (XR) businesses. Buniac worked at Motorola for more than 30 years and became president of Motorola's devices business in 2018. His responsibilities also cover Qualcomm's next-generation AI devices. As Qualcomm tries to extend Snapdragon's reach beyond smartphones and further into the emerging agentic AI ecosystem, this appointment brings the company an executive with extensive experience in driving consumer devices from design to commercialization. As of early Wednesday U.S. Eastern Time, Qualcomm retail sentiment on the Stocktwits platform was "bullish," unchanged from the beginning of the week. As of press time, the stock ranked among the top ten on the platform's trending list. A veteran retail trader said on Stocktwits: "Samsung is expected to be the first major partner to launch devices equipped with the standard chip, and related reports list the Galaxy S27 and Galaxy Z Fold 9 as the first models." "In addition to Samsung, Xiaomi, OnePlus, and iQOO are also rumored to be expected to receive these new chips earlier." Agents drive computing expansion: Qualcomm welcomes dual opportunities on-device and in the cloud. The core change brought by cutting-edge agents such as Muse and Astra is expanding a single Q&A into a complete workflow that includes continuous reasoning, tool invocation, code execution, and result validation. Deriving from the system architecture, as more tasks are handed over to agents, accelerators need to handle model computation, CPUs need to handle task orchestration, browser operations, software tools, and execution environments, while memory and networking are responsible for storing context and transmitting data. This expands growth in AI infrastructure demand across more chip types and also opens market space for Qualcomm's inference accelerators and server CPUs. Therefore, regarding the expansion of data center CPU demand that will be brought by the global rise of AI agents, the key to the bullish investment logic for Qualcomm is this: improved agent capabilities expand the range of commercially viable tasks, and more users, higher usage frequency, and longer task workflows together drive growth in demand for computing resources. Qualcomm's published Dragonfly roadmap has already listed agent processing, inference acceleration, and high-speed interconnect as core directions for its data center business. On the device side, agents need to continuously perceive personal context, respond quickly, and invoke applications, while also meeting smartphones' strict battery life and thermal constraints. Therefore, performance per watt, heterogeneous computing scheduling, and local processing capability directly affect the user experience. Qualcomm's Oryon CPU, Adreno GPU, and Hexagon NPU can share control, graphics, and adaptive AI computing tasks: lightweight inference and personal data processing are completed on-device, while more complex tasks call cloud models through the network. This device-cloud collaboration adds new product value to the Snapdragon platform. According to Qualcomm's published generational comparison, the flagship Extreme model's NPU performance is improved by 35%, and performance per watt is improved by up to 33%. Its commercial significance is to enable more complex AI functions to run continuously within limited battery and thermal space. In addition, compared with NVIDIA Corporation/AMD AI GPU computing systems and Alphabet Inc. Class C TPU computing systems in AI chips, Qualcomm's push into data center AI chips focuses on inference, with the technical breakthrough being to reduce data movement overhead and the cost per effective output token. The world's most cutting-edge AI large models and AI agents focused on agentic workload workflows need to repeatedly read model weights when generating answers and access a key-value cache that grows with context; especially in low-batch, low-latency decoding scenarios, memory bandwidth and capacity can easily become bottlenecks. This is why Qualcomm's AI200 AI chip adopts a high-capacity, low-power memory route, while the AI250 further introduces HBC near-memory computing, using 3D integration to more tightly combine computing and memory and reduce the energy consumption of data movement. Its most core potential competitiveness lies in this: while meeting output quality, latency, and throughput requirements, it increases the amount of inference service that can be delivered per unit of power, thereby improving total cost of ownership in data centers. According to the official roadmap, the AI250 equipped with first-generation HBC is expected to begin commercial sampling in mid-2027. The data center server CPU business allows Qualcomm to participate in another key link in agent computing. The Dragonfly C1000, using self-developed Oryon cores, targets task orchestration, general-purpose computing, and AI host nodes. Qualcomm has reached a multi-generation CPU cooperation with Meta, with the first-generation product planned to begin mass production in the second half of 2028, providing a customer base for its medium- to long-term demand expectations. In addition, in September Qualcomm announced a multi-generation custom chip cooperation with Amazon.com, Inc., focused on AI inference and covering optical interconnect solutions up to 1.6T and beyond. The investment transmission formed by these latest developments for leaders in the AI computing industry chain such as Qualcomm is this: on-device agents enhance the value of high-end Snapdragon platforms, while cloud agents broaden the market space for inference accelerators, server CPUs, and interconnect products; as customer projects gradually enter mass production, Qualcomm has the opportunity to convert the low-power design capabilities accumulated in mobile computing into data center revenue and expand its long-term growth sources. On Wall Street, one analyst has set a 12-month price target of $400 for Qualcomm, corresponding to about 101.75% potential upside, and this target is also the highest price target on Wall Street. Tristan Gerra, an analyst from Baird, recently raised Qualcomm's price target from $300 to $400, maintaining an "Outperform" rating. The analyst's $400 target bets on earnings growth and valuation re-rating brought jointly by "data centers opening new markets + revenue structure diversification + agent smartphone upgrades." Gerra expects Qualcomm's fiscal 2027 data center revenue to reach $5 billion, accounting for about 11% of its total revenue forecast, meaning the AI infrastructure business is about to begin having a material impact on overall performance.