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TSMC and NVIDIA are not interchangeable semiconductor companies. TSMC is a pure-play foundry: it manufactures chips designed by other companies. NVIDIA sells accelerated-computing platforms and products, with data-center demand driving most of its latest reported revenue. TSMC can fit an investment thesis built around advanced manufacturing capacity and diversified chip demand; NVIDIA can fit a thesis focused on accelerated computing and AI infrastructure. Neither company can be called the better or cheaper stock without same-date share prices, comparable valuation measures, growth expectations and an assessment of your risk tolerance.
The latest figures also cover different periods. TSMC’s cited annual results are for calendar 2025, while NVIDIA’s fiscal 2026 ended January 25, 2026. Keep those labels beside every number when comparing them.
What each company actually does
TSMC: manufacturing as a service
TSMC’s business is based on the pure-play foundry model. Customers design processors and other integrated circuits; TSMC develops manufacturing processes, operates fabrication plants and produces wafers at the technology nodes and volumes those customers order. It generally does not sell a branded end product to consumers. Revenue therefore depends on customers’ chip designs, production commitments, selling prices and the utilization of TSMC’s factories.
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This model gives TSMC exposure to many end markets at once. A customer may be designing an AI accelerator, smartphone processor, networking chip, automotive component or another specialized device. TSMC participates in the manufacturing economics of those products without having to win the end-market software, system or brand competition itself. The trade-off is a very large fixed-cost base: clean rooms, tools, buildings, utilities and highly trained staff must be paid for even when wafer demand weakens.
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NVIDIA: platforms and products for accelerated computing
NVIDIA describes its business as accelerated computing and AI platforms. Its fiscal 2026 filing identifies two reportable segments—Compute & Networking and Graphics—and four market platforms: Data Center, Gaming, Professional Visualization and Automotive. The company combines processors, networking, systems, software and developer tools into platforms intended to accelerate AI and other demanding workloads.
That approach gives NVIDIA more direct exposure to how customers deploy computing. Revenue can rise when cloud providers, enterprises and other buyers expand AI clusters, purchase networking equipment or adopt new generations of accelerated systems. It also means NVIDIA carries product-transition, platform-adoption and customer-concentration risks that are different from those of a foundry.
How the companies are connected
TSMC and NVIDIA can be viewed as links in the same supply chain rather than as direct substitutes. NVIDIA designs platforms and chips; TSMC is one of the manufacturers that can produce advanced semiconductors for customers such as NVIDIA. A stronger NVIDIA product cycle can increase demand for manufacturing capacity, although TSMC also serves many other customers and end markets.
On June 1, 2026, NVIDIA announced that TSMC uses NVIDIA computing and AI technologies in fab workloads including computational lithography, simulation, process control and inspection. That statement comes from NVIDIA’s announcement and should be read as a description of the companies’ technology collaboration, not as an independent performance test. The announcement is available at NVIDIA’s June 1, 2026 release.
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Latest reported financial snapshot
The table below places the reported figures beside their periods and currencies. They are company-reported results, not an independently calculated like-for-like comparison.
| Measure | TSMC | NVIDIA | How to read it |
|---|---|---|---|
| Annual period | Calendar 2025 | Fiscal 2026, ended January 25, 2026 | The periods do not align. |
| Revenue | US$122.42 billion | US$215.9 billion | Different fiscal periods and business mixes. |
| Net income | US$55.21 billion | US$120.067 billion | Reported net income for each company’s stated period. |
| Gross margin | 59.9% | 71.1% | Definitions and product mixes differ; do not treat the percentages as directly comparable. |
| Operating margin | 50.8% | Not stated in the cited NVIDIA figures | Use each company’s own filing definitions when extending the comparison. |
| Diluted EPS | Not stated in the cited TSMC figures | US$4.90 | Currency, share count and accounting period matter. |
| Data Center platform revenue | Not applicable as a reported NVIDIA platform measure | US$193.7 billion | Data Center represented most of NVIDIA’s fiscal 2026 revenue. |
TSMC also reported quarterly revenue of US$40.20 billion and a 67.7% gross margin for the second quarter of 2026. Those figures are a single quarter, not an annual run rate. The company’s quarterly release is at TSMC’s Q2 2026 results page.
What drives TSMC’s investment case
Exposure to advanced manufacturing demand
A TSMC thesis starts with the belief that customers will continue outsourcing leading-edge and specialized chip production and that TSMC can convert that demand into profitable wafer volume. The company’s 2025 annual report described robust AI-related demand entering 2026, while also acknowledging macroeconomic uncertainty. Advanced process technology, manufacturing scale and customer relationships are central variables to monitor.
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Because TSMC manufactures designs from many customers, its results are not tied to one branded platform. That breadth can cushion a downturn in one category, although it does not eliminate cyclicality: several customers can reduce orders at the same time when inventories rise or consumer demand slows.
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Operating leverage from factory utilization
Factories have substantial fixed costs. When utilization is high, those costs are spread across more wafers and margins can be strong. When demand falls, underused capacity can pressure margins quickly. TSMC’s 2025 results included a 59.9% gross profit margin and a 50.8% operating profit margin, but those historical margins should be evaluated alongside utilization and future demand rather than assumed to be permanent.
Risks specific to the foundry model
- Demand cycles: weaker smartphone, computing, automotive or other end-market demand can reduce orders.
- Average selling price pressure: competition or customer bargaining can limit the price TSMC receives for wafers.
- Yield and execution: difficulties ramping a new process or achieving expected yields can delay shipments and raise costs.
- Competition: rival foundries and customers’ decisions about internal manufacturing can affect share and pricing.
- Geopolitical and macroeconomic uncertainty: trade policy, regional tensions and economic slowdowns can disrupt demand or operations.
These risks are why a TSMC thesis should include assumptions about factory utilization, process execution and the durability of customer demand—not only the size of the AI opportunity.
What drives NVIDIA’s investment case
Concentration in data-center infrastructure
NVIDIA reported US$193.7 billion of Data Center platform revenue out of US$215.9 billion total revenue in fiscal 2026. That concentration makes the company a direct way to express a view on AI infrastructure and accelerated-computing deployment, but it also means spending decisions by a relatively small group of large customers can have an outsized effect on results.
Platforms rather than a single chip
NVIDIA’s offering spans accelerators, networking, systems and software. Customers buying a platform may incur switching costs and build applications around its tools, which can support demand when performance and ecosystem compatibility matter. The same platform structure makes product transitions significant: a delayed or difficult transition can affect several components of the business at once.
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Financial profile in fiscal 2026
For fiscal 2026, NVIDIA reported US$215.9 billion in revenue, US$120.067 billion in net income, a 71.1% gross margin and diluted earnings per share of US$4.90. Those numbers describe the period that ended January 25, 2026; they should not be combined with TSMC’s calendar-2025 results as though both companies had identical reporting calendars.
Risks specific to the platform model
- Customer capital and capacity: AI deployments require data-center space, electricity and financing. Customers may delay projects if any of those constraints tighten.
- Energy availability: power requirements can limit the pace at which new accelerated-computing clusters are built.
- Product transitions: new architectures and systems must move from design to volume production while customers adapt their infrastructure.
- Supply and manufacturing concentration: reliance on particular suppliers or manufacturing partners can create bottlenecks.
- Export controls: licensing rules can restrict sales to certain markets or require product changes.
- Inventory and purchase commitments: NVIDIA reported a US$4.5 billion charge related to H20 excess inventory and purchase obligations after export-licensing requirements affected demand.
These issues make NVIDIA’s growth outlook sensitive not only to AI enthusiasm but also to the practical ability of customers to fund, power and deploy the systems.
Which thesis fits which stock?
| If your central belief is… | The business that more directly expresses it | Questions to test the thesis |
|---|---|---|
| Advanced manufacturing capacity will remain scarce and valuable. | TSMC | Are leading-edge orders, yields and factory utilization supporting the expected returns on capacity? |
| AI and accelerated-computing deployments will keep expanding rapidly. | NVIDIA | Do customers have the capital, energy and data-center capacity to turn plans into shipped systems? |
| Chip demand will broaden across several end markets. | TSMC | How diversified are customer orders, and what happens if one major category weakens? |
| Platform software, networking and systems will reinforce accelerator demand. | NVIDIA | Are customers continuing to adopt the platform through product transitions and competitive alternatives? |
| You want a direct valuation call today. | Neither conclusion is supported by the cited evidence alone. | Obtain same-date prices, share counts, earnings estimates and comparable forward multiples first. |
The table is a decision framework, not a ranking. A portfolio can contain either company only if the position size and risk tolerance match the uncertainty in the underlying thesis.
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The available company reports establish business exposure and historical results, but they do not establish which security was cheaper on October 13, 2026. A defensible valuation comparison requires data captured on the same date and converted consistently.
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- Record the market inputs together: use the same closing date for each share price, diluted share count, market capitalization and enterprise value.
- Align the earnings period: decide whether you are comparing trailing results or forward estimates, and apply the same period to both companies.
- Choose comparable measures: price-to-earnings, enterprise-value-to-operating-profit and free-cash-flow yields can each tell a different story. Do not compare NVIDIA’s forward earnings multiple with TSMC’s trailing multiple and call the result neutral.
- Normalize currency and accounting: TSMC reports in U.S. dollars in the cited figures, while fiscal calendars and accounting classifications still differ. Check whether an estimate is GAAP, IFRS or an adjusted measure before using it.
- Stress-test growth: model slower AI infrastructure spending, lower foundry utilization, margin pressure and a higher cost of capital. A lower multiple may reflect greater risk rather than a bargain.
- Compare the implied expectations: ask what revenue growth, margin and reinvestment assumptions are already embedded in each price. The stock with the lower multiple is not automatically the one with the lower expectations.
Until those steps are completed with current data, the responsible conclusion is that valuation is unresolved.
A practical research checklist before buying either stock
For a TSMC thesis
- Read the latest annual and quarterly reports for wafer demand, utilization, process ramps and capital spending.
- Track customer concentration and the mix of leading-edge versus mature-node production.
- Check whether average selling prices and gross margin are moving because of mix, pricing or temporary utilization effects.
- Define how a geopolitical disruption or a prolonged end-market downturn would change your position size.
For an NVIDIA thesis
- Separate Data Center growth from the smaller Gaming, Professional Visualization and Automotive platforms.
- Monitor customer capital budgets, power availability and construction schedules for data centers.
- Follow product-transition timing, system availability and supplier constraints rather than relying on announced demand alone.
- Review export-control changes and their effect on eligible products, inventory and purchase commitments.
- Test whether the valuation still works if growth decelerates from the latest exceptional rate.
For either thesis
- Use reported fiscal periods beside every historical number.
- Distinguish management expectations from delivered results.
- Set a time horizon and an explicit reason the thesis would be invalidated.
- Account for portfolio concentration, currency exposure and the possibility that semiconductor cycles turn before the long-term story does.
Scenario analysis: how the same industry trend affects each company
AI infrastructure accelerates
NVIDIA may see the most immediate benefit because Data Center is its principal platform and its products sit directly in accelerated-computing deployments. TSMC can benefit as customers order more advanced wafers, but the effect depends on customer designs, capacity allocation, yields and the timing of factory ramps.
AI spending pauses
NVIDIA could face a sharper revenue and inventory response if customers defer cluster purchases or lack power and capital. TSMC would also be exposed through lower customer orders and utilization, although its broader customer base could moderate the impact.
Manufacturing capacity tightens
Scarcity can support foundry pricing and utilization, favoring the economics of TSMC’s model. For NVIDIA, constrained supply can limit shipments even when customer demand is strong, potentially shifting revenue between periods and increasing execution pressure.
Export restrictions expand
NVIDIA’s direct sales exposure to restricted markets makes policy a first-order variable. TSMC can be affected through customer mix, equipment restrictions and regional operations, but the exact impact depends on which customers and processes are covered.
Bottom line for an investment decision
Choose TSMC when your thesis is primarily about owning a scaled, advanced foundry that serves many chip designers and can earn attractive returns when its factories are well utilized. Choose NVIDIA when your thesis is primarily about sustained investment in accelerated computing and AI infrastructure, and you accept concentrated exposure to data-center spending, energy, product transitions, supply and export policy.
The companies’ strong reported results do not settle the decision. TSMC’s calendar-2025 revenue was US$122.42 billion and net income was US$55.21 billion; NVIDIA’s fiscal-2026 revenue was US$215.9 billion and net income was US$120.067 billion. Those figures come from different periods and business models. Use the TSMC 2025 annual report, the NVIDIA fiscal 2026 Form 10-K and the NVIDIA fiscal 2026 annual report and proxy summary to verify assumptions, then add same-date valuation data before deciding which security fits your portfolio.
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