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Compare AI chip stocks with a like-for-like scorecard, not a leaderboard of headline revenue growth. Normalize each company to the same fiscal period, currency, and accounting basis; separate disclosed AI or Data Center sales from total revenue; then test margins, cash conversion, valuation, customer concentration, export exposure, manufacturing constraints, and execution risk.
That method matters because these companies are economically different. One may sell accelerators and systems, another may combine semiconductors with infrastructure software, and another may manufacture chips designed by customers. The fastest-growing stock is not automatically the best investment if its price already discounts years of growth or if a single customer, country, product generation, or manufacturing node drives the forecast.
What an AI-chip stock comparison should measure
Start by defining the comparison universe and the period. Use reported financial statements for the same quarter or fiscal year, convert currencies consistently, and label every figure as GAAP, IFRS, non-GAAP, or adjusted. A scorecard that mixes a quarterly number from one company with a full-year number from another can look precise while being economically meaningless.
Next, distinguish the business model. AMD reports Data Center, Client and Gaming, and Embedded segments. NVIDIA reports Data Center as a major segment. Broadcom combines semiconductor products with infrastructure software. TSMC is a foundry: it manufactures chips for customers rather than selling a merchant AI accelerator under its own brand. Total company revenue therefore cannot be treated as “AI revenue.” Use an AI or Data Center figure only when management discloses one, and state exactly what it includes.
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The comparison should answer five questions:
- How quickly are comparable revenue and AI-related businesses growing?
- How much of that growth becomes gross profit, operating income, and free cash flow?
- What multiple does the market assign to those profits and cash flows?
- How concentrated are customers, products, suppliers, and geographies?
- What could cause the earnings forecast to miss?
Keep reported facts separate from your interpretation. A high margin may indicate pricing power, but it can also reflect an unusually favorable product mix or a temporary supply shortage. A low multiple may signal an opportunity, or it may price in cyclicality, export restrictions, customer losses, or a costly product transition.
Build a comparable dataset before calculating ratios
1. Fix the measurement date
Record the date on which you collect the share price, latest diluted share count, balance sheet, and earnings forecast. Valuation changes every trading day, while financial statements update only at reporting dates. Put the “as of” date beside every multiple so a reader can reproduce it.
2. Align fiscal periods
Use the latest completed fiscal year for an annual comparison and the latest reported quarter for a quarterly update. If fiscal calendars differ, note the actual ending dates. Do not compare a quarter that contains a major product launch with another company’s quarter before its launch unless you explain the timing.
3. Use one currency
Convert revenue, profit, debt, cash, and free cash flow into one currency using a consistent policy. For income-statement items, a period-average exchange rate is usually more representative; for balance-sheet items, use the period-end rate. If a company already reports a growth rate in U.S. dollars, preserve that basis rather than silently substituting a constant-currency rate.
4. Label accounting basis
Keep GAAP or IFRS and adjusted figures in separate columns. Adjusted results may exclude stock compensation, acquisition costs, amortization, restructuring, or other items. They can be useful for operating comparisons, but they are not interchangeable with statutory earnings. Never use a GAAP share count with adjusted earnings without explaining the mismatch.
5. Define AI exposure
Write the segment definition beside the number. “Data Center” can include traditional enterprise servers, networking, storage, and AI accelerators. A foundry’s advanced-node revenue is an enabling exposure to AI demand, not direct AI-chip sales. If no company-specific AI figure is disclosed, write “not separately disclosed” rather than estimating it from total revenue.
6. Capture cash and capital structure
Collect operating cash flow, capital expenditure, free cash flow, cash, debt, diluted shares, and any material convertible securities. Enterprise-value measures require net debt, while equity-value measures such as P/E do not. Check whether restricted cash, leases, or minority interests materially affect the calculation.
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Compare growth without confusing scale and momentum
AMD: fast total-company growth with a disclosed Data Center engine
AMD reported $11.5 billion of revenue for the quarter ended June 27, 2026, up 50% from the prior-year period. The filing attributed Data Center demand to EPYC processors and Instinct MI350 GPUs. For 2025, AMD reported $34.6 billion of revenue, up 34%, while Data Center revenue reached $16.6 billion, up 32%.
Use both views. The quarterly 50% rate shows current momentum, but the annual Data Center rate shows how much of the business is tied to the infrastructure cycle. Do not label the entire $11.5 billion quarter as AI revenue: Client, Gaming, and Embedded products are included in total company sales. Check whether the latest quarter’s mix increased Data Center’s share and whether gross-margin changes came from that mix or from pricing and costs.
NVIDIA: exceptional scale and concentration in Data Center
NVIDIA reported fiscal-2026 revenue of $215.938 billion, up 65% year over year. Full-year Data Center revenue was $193.7 billion, up 68%. Its release said fourth-quarter revenue was a record $62.3 billion, up 22% from the previous quarter and 75% from a year earlier, driven by accelerated computing and AI platform shifts.
The Data Center figure is close to total company revenue, so NVIDIA’s AI exposure is more directly visible than a diversified semiconductor company’s. That same concentration increases sensitivity to hyperscaler capital expenditure, accelerator availability, export rules, and the timing of new systems. Compare growth from the same fiscal period and ask how much is unit volume, average selling price, networking, systems, or acquisitions.
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TSMC’s revenue increased 35.9% in U.S.-dollar terms in 2025. Its 3-nanometer process represented 24% of wafer revenue, and 2-nanometer entered high-volume manufacturing in the fourth quarter of 2025. The company says advanced technologies and advanced packaging are intended to address demand for energy-efficient computing; its 2-nanometer ramp is planned for 2026.
For TSMC, track advanced-node wafer revenue, technology mix, utilization, pricing, and packaging capacity rather than searching for a single “AI revenue” line. A customer’s AI accelerator order can benefit the foundry, but the foundry does not control the accelerator’s selling price or end-customer demand. Node transitions can also create temporary costs before volume production improves economics.
Broadcom: semiconductor growth plus infrastructure software
Broadcom’s second-quarter fiscal-2026 release described record revenue and accelerating AI-semiconductor growth, and its third-quarter guide called for $29.4 billion of revenue. The disclosed figure combines semiconductors with infrastructure software, so total-company growth is not a clean measure of AI-chip momentum.
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Separate semiconductor revenue from infrastructure software when the filing allows it. Then examine whether AI growth comes from custom accelerators, networking, connectivity, or other products. Software can add recurring revenue and diversification, but it also changes the margin, acquisition, and valuation profile compared with a pure semiconductor business.
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Measure margins and cash conversion on the same basis
Gross margin indicates how much revenue remains after direct product costs and is a useful first test of pricing power and mix. Operating margin shows what remains after research and development, sales, and administration. Free-cash-flow margin tests whether accounting profit becomes cash after capital expenditure and working-capital needs.
AMD reported a 54% gross margin and $2.0 billion of operating income in the June 27, 2026 quarter. Dividing operating income by $11.5 billion of revenue gives an approximately 17.4% operating margin; label that as a calculation and preserve the filing’s accounting basis. NVIDIA reported a fiscal-2026 non-GAAP gross margin of 71.3% and non-GAAP operating income of $137.3 billion. Dividing by $215.938 billion gives an approximately 63.6% non-GAAP operating margin.
Those percentages are not directly interchangeable. They cover different periods, business mixes, and adjustment policies. Put GAAP and non-GAAP side by side, reconcile the largest adjustments, and check whether stock-based compensation is a recurring economic cost. For each company, calculate:
- Gross margin: gross profit ÷ revenue.
- Operating margin: operating income ÷ revenue.
- Free-cash-flow margin: (operating cash flow − capital expenditure) ÷ revenue.
- Cash conversion: free cash flow ÷ net income, with a note when working capital or a one-time tax payment distorts the period.
Use a trailing four-quarter total when quarterly cash flow is volatile. Investigate a widening gap between net income and free cash flow: inventory builds, receivables from large customers, supplier prepayments, or heavy data-center investment can all explain it. A high margin with weak cash conversion deserves a lower quality score than a slightly lower margin that consistently produces cash.
Calculate valuation with live, clearly labeled inputs
The available company figures do not establish live valuation multiples. Populate them immediately before publication using the same-day share price and the latest diluted share count. State whether the denominator is trailing or forward, GAAP or adjusted, and which fiscal year the forecast uses.
Equity-value measures
- Trailing P/E: current share price ÷ trailing-12-month diluted EPS.
- Forward P/E: current share price ÷ forecast diluted EPS for a specified fiscal year.
- Price-to-sales: market capitalization ÷ trailing or forecast revenue.
- Free-cash-flow yield: trailing or forecast free cash flow ÷ market capitalization.
Enterprise-value measures
Calculate enterprise value as market capitalization plus debt, preferred equity, and minority interests minus cash and qualifying investments. Then divide by EBITDA for the same period. Explain whether lease liabilities are included and avoid mixing a non-GAAP EBITDA definition with a GAAP numerator.
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Use growth-adjusted context, not a single “cheap” multiple
Pair each multiple with expected revenue growth, operating-margin durability, and free-cash-flow conversion. A stock at 20 times earnings may be expensive if earnings are near a cyclical peak; a stock at 40 times earnings may be reasonable only if the growth rate and margins persist. Compare the multiple with the company’s own history and with peers only after normalizing accounting, fiscal year, and net-cash position.
| Metric | Required input | Interpretation | Common error |
|---|---|---|---|
| P/E | Share price and diluted EPS | Price paid for accounting earnings | Mixing GAAP EPS with adjusted EPS |
| EV/EBITDA | Market value, debt, cash, EBITDA | Value of operations before interest, tax, depreciation, and amortization | Ignoring net cash or lease treatment |
| Price-to-sales | Market capitalization and revenue | Useful when earnings are temporarily depressed | Ignoring large differences in margins |
| FCF yield | Free cash flow and market capitalization | Cash return implied by the current price | Using a one-quarter cash spike as a run rate |
AI-chip stock scorecard
Use this table as a starting framework. “Not stated” means the cited company disclosures do not provide a comparable figure; it is not a zero. Add live valuation data only after the calculations described above.
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|---|---|---|---|---|---|---|---|---|---|---|---|
| AMD | Processors and accelerators; Data Center, Client and Gaming, Embedded segments | $11.5B, +50% year over year, quarter ended June 27, 2026 | 2025 Data Center $16.6B, +32% | 54% for June 2026 quarter; basis stated in filing | Approximately 17.4% from $2.0B operating income ÷ $11.5B revenue; calculated | Not stated | Not stated; populate with live P/E, EV/EBITDA, P/S and FCF yield | Quantify hyperscaler and major-program exposure from filings | Assess China and other export restrictions | Relies on external foundry and packaging capacity | EPYC, Instinct software and platform adoption; verify design wins and recurring support |
| NVIDIA | Accelerated computing, AI platforms, networking and systems; Data Center is dominant | Fiscal 2026 $215.938B, +65% | Fiscal 2026 Data Center $193.7B, +68% | 71.3% fiscal 2026 non-GAAP | Approximately 63.6% fiscal 2026 non-GAAP from $137.3B ÷ $215.938B; calculated | Not stated | Not stated; use current price and specified fiscal-year EPS or FCF | Measure hyperscaler and platform concentration | Fiscal-2027 Q1 outlook assumes no Data Center compute revenue from China | Depends on leading-edge manufacturing and advanced packaging partners | CUDA ecosystem, systems, networking and rapid platform cadence; test switching costs |
| TSMC | Foundry manufacturing and advanced packaging for customers’ chips | 2025 revenue +35.9% in U.S.-dollar terms | Not separately disclosed; track advanced-node and packaging demand | Not stated | Not stated | Not stated | Not stated; use foundry earnings and cash-flow estimates | Quantify largest customers and wafer demand concentration | Assess cross-strait, export-control and customer-location risk | Manufacturing is the core business; 2nm high-volume manufacturing began in 4Q25 and ramps in 2026 | Process technology, yield, scale and advanced packaging |
| Broadcom | Semiconductors plus infrastructure software; AI semiconductor growth is disclosed separately only in part | Q2 fiscal 2026 record revenue; exact comparable rate not stated | Accelerating AI-semiconductor growth; exact rate not stated | Not stated on a comparable basis | Not stated on a comparable basis | Not stated | Not stated; separate semiconductor and software assumptions where possible | Review custom-accelerator and networking customer concentration | Review export controls and end-market geography | Uses external manufacturing for semiconductor products | Custom silicon, networking and infrastructure software; assess recurring revenue and design-win durability |
Data-date and accounting-basis note: AMD figures are from the quarter ended June 27, 2026 and its 2025 filing; NVIDIA figures are fiscal 2026 unless noted; TSMC figures are for 2025; Broadcom references its fiscal-2026 second-quarter release and third-quarter guide. Margin bases are not uniform, and several cash-flow and concentration fields require the latest filings.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Test the risks that can derail AI-chip earnings
Customer and platform concentration
Identify the percentage of revenue from the largest customers, distributors, cloud providers, and individual programs. A company can appear diversified by product category while relying on a few hyperscalers for most AI demand. Check purchase commitments, cancellation terms, receivables concentration, and whether a customer is designing an internal alternative.
Export and geopolitical exposure
Map revenue and supply chains by country, not just headquarters. NVIDIA’s fiscal-2027 first-quarter outlook assumes no Data Center compute revenue from China, illustrating how a policy change can alter a forecast even when underlying demand remains strong. Review licensing requirements, product-specific restrictions, and the possibility that customers redesign around controlled components.
Supply, manufacturing and packaging
Check wafer capacity, advanced packaging availability, substrate supply, memory access, lead times, and yield. TSMC’s 2-nanometer high-volume manufacturing began in the fourth quarter of 2025 and is ramping in 2026; the opportunity depends on successful yields and customer qualification, not only on the announced node. For fabless designers, a strong order book is not useful if a manufacturing or packaging bottleneck prevents delivery.
Custom-silicon competition
Hyperscalers may move workloads from merchant GPUs to internally designed accelerators. Look for evidence of design wins, production volumes, software compatibility, networking content, and recurring support revenue. A custom chip may reduce accelerator share while increasing demand for networking or foundry capacity, so analyze the whole value chain rather than assuming every substitution is equally negative.
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Cycle and valuation risk
Compare backlog, customer capital-expenditure plans, inventory days, receivable days, and capacity commitments with the earnings growth embedded in the share price. Rapid growth can reverse when customers digest inventory or delay data-center projects. A high valuation magnifies the effect of a one-quarter miss; a low valuation can reflect genuine structural deterioration.
Execution and product transitions
Track roadmap cadence, software releases, yields, benchmark availability, customer qualification, and the time between announcement and meaningful revenue. Launch claims are not evidence of profitable volume. Watch gross-margin guidance during transitions because early versions of a new product may carry higher costs, lower yields, or expensive system components.
Turn the data into an investment decision
Use a weighted score rather than a single winner
Assign weights that match your objective. A growth-oriented investor might emphasize two-year Data Center growth and design-win momentum; a quality investor might weight gross margin, operating margin, and free-cash-flow conversion; a risk-controlled investor might give more weight to customer concentration, export exposure, and balance-sheet resilience. Keep the weights fixed across companies and document why a score changed.
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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteSeparate evidence from assumptions
Create one column for reported results and another for forward assumptions. Reported growth, margins, and cash flow are facts for a defined period. Forecast growth, terminal margins, and valuation multiples are assumptions. If your conclusion changes only when a very optimistic forecast is used, the thesis is fragile.
Stress-test the thesis
Run at least three cases: a base case using current guidance, a downside case with slower AI demand or an export loss, and an upside case with sustained growth and stable margins. Recalculate earnings, free cash flow, and valuation in each case. Include a product delay, packaging constraint, customer insourcing, and foreign-exchange movement where relevant. The goal is not to predict the exact future but to see which assumption controls the outcome.
Common comparison mistakes
- Calling all revenue AI revenue: diversified segments and foundry sales require separate treatment.
- Mixing fiscal periods: seasonality and product launches can distort growth rankings.
- Combining GAAP and adjusted margins: adjustments can materially change operating profitability.
- Ignoring cash flow: profit can rise while inventory and capital spending consume cash.
- Using stale multiples: share prices and analyst estimates move daily.
- Assuming a low multiple is safe: export limits, concentration, and cyclicality can justify a discount.
- Ignoring manufacturing: design wins do not guarantee wafer, packaging, or memory availability.
- Scoring announcements instead of execution: verify qualification, shipment, yield, and recurring software or networking revenue.
A repeatable quarterly update process
- Download each company’s latest earnings release, filing, segment note, and guidance.
- Record fiscal-period end dates, currency, diluted shares, cash, debt, revenue, gross profit, operating income, operating cash flow, and capital expenditure.
- Update the AI or Data Center line only when the company defines it; preserve the definition in your notes.
- Recalculate growth, margins, free-cash-flow margin, net cash or debt, and working-capital trends.
- Collect the same-day share price and specified forward estimates, then calculate P/E, EV/EBITDA, price-to-sales, and FCF yield.
- Review customer, export, supply, custom-silicon, cycle, and execution indicators for changes.
- Re-run base, downside, and upside cases and record which assumption moved the valuation most.
- Publish the date and accounting basis beside every table so the comparison remains auditable.
Bottom line
The best way to compare AI chip stocks is to rank the durability of profitable, cash-generating growth after adjusting for business model and risk. NVIDIA currently provides the clearest disclosed AI scale in the figures above, AMD shows substantial Data Center momentum from a broader portfolio, TSMC offers foundry and advanced-node exposure, and Broadcom combines AI semiconductors with infrastructure software. None can be judged fairly from growth alone. A defensible conclusion requires normalized periods, separate accounting bases, live valuation inputs, and a stress test for customers, exports, manufacturing, custom silicon, cycles, and execution.
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