AEM Holdings Ltd: Read-through from AMD’s earnings beat and upbeat outlook
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- The chip combines a Blackwell-class RTX GPU with a Grace CPU and is designed to run Windows on ARM
- Extends AI hardware from data centres to edge and personal devices, with impact likely most pronounced in ultra-premium PCs
- Beneficiaries include leading-edge fabrication, Arm-based architecture and premium OEM platforms; adoption depends on compatibility, pricing and compelling edge AI use cases
- For Singapore-listed names, AEM is the key read-through, with ultra-premium client CPU risk mitigated by rising edge AI test intensity
RTX Spark sparks a rethink of the semicon value chain. Nvidia is extending its AI stack from data-centre GPUs into premium client devices, broadening AI demand beyond cloud infrastructure into edge and AI personal computing. We are of the view that this creates new opportunities across the value chain in silicon and fabrication, chip design, and OEMs & device makers.
Source: DBS
RTX Spark, an arm-based chip will be available in fall 2026. The chip combines a Blackwell-class RTX GPU with a Grace CPU and is designed to run Windows on ARM. The first systems are expected from major vendors including Dell, Lenovo, HP, ASUS, Microsoft Surface and MSI, positioning RTX Spark as a premium AI PC platform and part of Nvidia’s broader push to move AI computing from a cloud-only model to a cloud, edge and personal AI model.
Is RTX sparking a return to its Consumer / Gaming roots?
| Segment Revenue | FY23 | FY26 | FY27F | |||
USD’mn | % mix | USD’mn | % mix | USD’mn | % mix | |
| Data Center | 15,005 | 55.6% | 193,737 | 89.7% | 362,091 | 92.8% |
| Gaming | 9,067 | 33.6% | 16,042 | 7.4% | 15,539 | 4.0% |
| Professional visualization | 1,544 | 5.7% | 3,191 | 1.5% | 6,458 | 1.7% |
| Automotive | 903 | 3.3% | 2,349 | 1.1% | 3,168 | 0.8% |
| Others | 455 | 1.7% | 619 | 0.3% | 3,008 | 0.8% |
| Total | 26,974 | 100% | 215,938 | 100% | 390,264 | 100% |
Source: DBS, VisibleAlpha
Why is Nvidia entering the CPU space? Nvidia is targeting USD20bn in CPU revenue this year, against a total addressable market it estimates at USD200bn. This raises two questions: (1) Why enter CPUs when GPUs remain its core strength, and (2) Why revisit the client/consumer market when data centres now account for more than 90% of revenue? In our view, the answer lies in the next phase of AI compute. Agentic AI is expected to drive a structural increase in CPU demand, as orchestration, memory management and system-level coordination become more important alongside GPU acceleration. While the guided USD20bn would account for only around 5% of FY27F consensus revenue, Nvidia is positioning early to capture a larger role in a CPU market that both AMD and Intel have highlighted as entering a faster growth phase.
Industry bellwethers are bullish on CPU demand/prospects
| Company | Management commentary on the CPU market |
Nvidia
| “Vera CPU opens a brand-new $200 billion TAM for NVIDIA, a market we have never addressed before, and every major hyperscale and system maker is partnering with us to get it deployed. We have visibility to nearly $20 billion in total CPU revenue this year, setting us up to become the world's leading CPU supplier” |
AMD
| “In November, we outlined the server CPU market growing at approximately 18% annually over the next 3 to 5 years. Based on the demand signals we are seeing today and the structural increase in CPU compute requirements driven by agentic AI, we now expect the server CPU TAM to grow at greater than 35% annually, reaching over $120 billion by 2030.” |
Intel
| “In recent months, we have seen clear signs that the CPU is reinserting itself as the indispensable foundation of the AI era…the ratio of CPU to GPU used to be 1 and 8, and now it's 1 to 4 on and I think towards parity or even better.” |
| Arm | “As Agentic AI scales, data centers will require more than 4x today's CPU capacity, creating a data center CPU market opportunity of more than $100 billion by 2030” |
Qualcomm
| “Agent orchestration is predominantly CPU bound and Qualcomm has the world's best-performing CPU across smartphones, PCs, auto and soon the data center” |
Source: DBS, Companies
Can Nvidia resolve windows compatibility issues on Arm? Qualcomm’s Windows PC push remains relatively nascent, making Apple’s M-series a more useful benchmark for what a successful ARM-based transition can achieve with an integrated operating system. As such, the success of RTX Spark will depend not only on hardware performance, but also on whether Windows-on-Arm can deliver a seamless experience across legacy applications when systems launch.
RTX Spark laptops start above USD2,500 and scale to USD5,000, positioning itself in the ultra-premium segment. For example, NVIDIA’s DGX Spark desktop, which uses the GB10 Grace Blackwell superchip and 128GB of unified memory, is priced at USD4.7k. This suggests the platform is aimed at AI developers, creators, small workstations and SMB or enterprise users running local inference or agent workloads, rather than mainstream consumers. Its closest competitors are likely Apple’s high-end MacBook Pro, such as the 14-inch M5 Max at USD3.6k, the Mac Studio ecosystem, and premium creator workstation lines from Dell, Lenovo, HP and ASUS. In contrast, NVIDIA is not yet a direct volume competitor to Qualcomm’s lower-priced Snapdragon X2, which starts at USD599, or Snapdragon C, which targets USD300 AI PCs. Qualcomm remains focused on the broader volume PC opportunity. This premium positioning also limits the near-term revenue risk to Intel and AMD, as ultra-premium PC users account for less than 5-10% of their revenue by our estimates.
Revenue exposure of Intel and AMD
| Tier | Intel | AMD |
| Ultra-premium PC | <5-10% | <5-10% |
| Premium PC | c.20% | c.10% |
| Mass-market PC | c.>30% | <c.15% |
Source: DBS estimates
We highlight the potential winners and losers of the RTX spark launch below.
Layer 1: Fabrication
TSMC: RTX Spark adds another leading-edge AI silicon programme to its 3nm-class pipeline. Volumes may start small, but any meaningful AI PC ramp would further entrench its role as the foundry of choice for advanced compute.
Layer 2: Chip design and architecture
Nvidia: Strengthens Nvidia’s position in chip design by extending its GPU-led AI architecture from data centres into premium client devices. The near-term financial impact may be modest, but it broadens its role across cloud, edge and personal AI compute.
Intel: Nvidia’s entry adds a new competitive watchpoint for Intel’s client CPU franchise, but RTX Spark’s ultra-premium positioning and Windows-on-Arm compatibility hurdles should limit near-term disruption. Intel remains well anchored in the Windows x86 ecosystem, particularly across enterprise and volume PC segments.
AMD: Nvidia’s RTX Spark introduces fresh competition in premium AI PCs, adding another front to AMD’s existing rivalry with Intel in client processors. However, the impact is more balanced, as AMD is more diversified across CPUs, and GPUs.
MediaTek: The partnership provides strategic validation from co-designing the CPU component with Nvidia.
Arm: Nvidia’s push brings Windows-on-Arm deeper into premium AI PCs. Success would strengthen the architecture’s position beyond smartphones and Apple Macs, although software compatibility remains the key gating factor.
Qualcomm: The read-through is mixed, as RTX Spark could validate Windows-on-Arm but also raise the performance bar. Qualcomm’s PC push remains early-stage, and more focused on cost-effective and power-efficient AI PCs rather than high-end workloads.
Layer 3: OEM and design makers
Dell, HP, Lenovo, ASUS: Gives major PC OEMs a new premium AI PC platform to differentiate beyond the traditional Intel and AMD x86 refresh cycle. The opportunity is to sell higher-value creator, developer and AI power-user devices, although adoption will depend on pricing and Windows-on-Arm compatibility.
Microsoft: Supports Microsoft’s push to make Windows a credible platform for local agents and on-device AI. The key upside is a stronger Windows-on-Arm ecosystem, but Microsoft will need to close the gap on app compatibility and enterprise readiness.
Apple: RTX Spark gives Windows OEMs a more credible rival in the premium PC category, particularly for creators and developers. The risk is mitigated by Apple’s strong ecosystem stickiness, tighter hardware-software integration and proven M-series transition, which should help defend its premium Mac franchise.
Local read through
AEM: RTX Spark introduces some downside risk for AEM through potential share shifts in client CPUs where its major customers are active. However, the most pronounced impact is likely confined to the ultra-premium PC segment, which accounts for less than 5-10% of its major customers’ revenue by our estimates, while adoption barriers such as Windows-on-Arm compatibility remain meaningful. The read-through is therefore not purely negative, as RTX Spark also reinforces the broader move toward more complex AI silicon at the edge, where higher compute density could support rising test intensity over time.
Overall, RTX Spark has broader implications across the semiconductor value chain in ultra premium PCs. The beneficiaries are in leading-edge manufacturing, Arm-based design, and premium OEM platforms, while incumbent x86 chipmakers face a higher competitive bar in the ultra-premium AI PC segment. Adoption will ultimately hinge software compatibility and whether local AI agents become compelling enough to justify higher price points of RTX Spark devices.
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