In 2010, Intel generated $43.6 billion in revenue and its nearest competitor in logic chips, AMD, generated $6.5 billion. NVIDIA was a $3.3 billion company still best known for gaming graphics cards. Qualcomm was growing rapidly on the smartphone wave. Broadcom and Texas Instruments were mid-sized analog and connectivity specialists.
By 2025, the same six companies tell a radically different story. NVIDIA has grown to $130.5 billion in revenue driven almost entirely by AI infrastructure demand. Intel sits at $52.9 billion, barely changed from its 2020 peak, now reporting losses. AMD has reached $34.6 billion and crossed Intel's gross margin for the first time in the company's history.
The Finance Toolkit makes it straightforward to track this transformation through financial data, both via Python code and the MCP server for those who prefer conversational analysis. The source code for every calculation is on GitHub. The MCP server documentation lives here.
Try this with the Finance Toolkit MCP: "Let's do a deep dive in the Semiconductor industry. What trends do you see in the last 10 years? And what about the fundamentals?"
Setting Things Up
Start by installing the Finance Toolkit:
pip install financetoolkit
Then import the library and define a universe of tickers. The example below uses six semiconductor companies: Intel, AMD, NVIDIA, Qualcomm, Broadcom, and Texas Instruments.
import pandas as pd
from financetoolkit import Toolkit
sector = Toolkit(
tickers=["INTC", "AMD", "NVDA", "QCOM", "AVGO", "TXN"],
api_key="YOUR_FMP_API_KEY",
start_date="2010-01-01"
)
Get your FMP API key at jeroenbouma.com/fmp. A paid plan is required to access the full 15-year history used here.
Revenue: How the Landscape Shifted
The most immediate observation from pulling 15 years of income statements is the NVIDIA revenue trajectory. Everything else looks like normal cyclical variation by comparison.
income = sector.get_income_statement()
revenue = income.loc["Revenue"][
["2010", "2014", "2018", "2022", "2025"]
] / 1e9
Which returns:
| Ticker | 2010 | 2014 | 2018 | 2022 | 2025 |
|---|---|---|---|---|---|
| INTC | 43.6 | 55.9 | 70.8 | 63.1 | 52.9 |
| AMD | 6.5 | 5.5 | 6.5 | 23.6 | 34.6 |
| NVDA | 3.3 | 4.1 | 9.7 | 26.9 | 130.5 |
| QCOM | 11.0 | 26.5 | 22.7 | 44.2 | 44.3 |
| AVGO | 2.1 | 4.3 | 20.8 | 33.2 | 63.9 |
| TXN | 14.0 | 13.0 | 15.8 | 20.0 | 17.7 |
Several things stand out. Intel peaked somewhere between 2020 and 2022, then contracted, a pattern without precedent in the company's history. NVIDIA's inflection is visible between 2022 and 2025: revenue grew from $26.9 billion to $130.5 billion in three years. Broadcom's growth looks smooth in this table but masks something important: the jump from $4.3 billion in 2014 to $20.8 billion in 2018 was almost entirely acquisition-driven, as the company absorbed Avago Technologies, Brocade, and CA Technologies in rapid succession. TXN and QCOM, the two companies least exposed to the AI compute buildout, show the flattest trajectories.
Gross Margins: The Fabless Advantage
Revenue tells you who is growing. Gross margins tell you who controls their cost structure. In semiconductors, the key structural divide is between integrated device manufacturers (companies that design and fabricate their own chips) and fabless companies that outsource manufacturing to foundries like TSMC.
gross_margin = sector.ratios.get_gross_margin()
margins = gross_margin[["2010", "2014", "2018", "2022", "2025"]] * 100
Which returns:
| Ticker | 2010 | 2014 | 2018 | 2022 | 2025 |
|---|---|---|---|---|---|
| INTC | 66.1% | 63.7% | 61.7% | 42.6% | 34.8% |
| AMD | 45.6% | 33.4% | 37.8% | 44.9% | 49.5% |
| NVDA | 35.4% | 54.9% | 59.9% | 64.9% | 75.0% |
| QCOM | 68.0% | 59.7% | 54.9% | 57.8% | 55.4% |
| AVGO | 46.2% | 43.9% | 51.5% | 66.6% | 67.8% |
| TXN | 53.6% | 56.9% | 65.1% | 68.8% | 57.0% |
The Intel margin collapse is the defining story of the table. A company that earned 66% gross margins in 2010 earns 34.8% in 2025. The proximate cause is that Intel's manufacturing processes fell behind TSMC's, first by one node generation, then two, meaning Intel's chips cost more to produce while competitors using TSMC got access to better processes at lower cost. The structural consequence is that Intel's cost-per-chip disadvantage compounds every product cycle.
NVIDIA went in the opposite direction: from 35.4% in 2010 to 75.0% in 2025. A fabless company with a near-monopoly on AI training hardware can charge what the market bears, and the market has been willing to pay very high prices for H100 and Blackwell GPUs. NVIDIA's gross margin today is higher than Intel's ever was.
AMD transitioned from a company with 33% gross margins in 2014 (a period when it was fighting for survival) to 49.5% in 2025. In 2022, AMD's gross margin crossed above Intel's for the first time. That crossover is not primarily a product story, it is a manufacturing story. AMD, as a fabless company using TSMC, gained access to better nodes while Intel's own fabs struggled.
Intel vs AMD: The x86 CPU Battle
Not every company in this sector competes with every other. Texas Instruments makes analog chips for industrial and automotive customers; it does not compete with NVIDIA for AI data center revenue. Qualcomm sells ARM-based mobile processors and has never produced an x86 chip. Broadcom targets networking and storage controllers.
The genuine competitive battle in x86 CPUs is between exactly two companies: Intel and AMD. Every server, desktop, and laptop CPU socket holds a chip made by one of them. Market share gained by one is market share lost by the other.
cpu_rivals = ["INTC", "AMD"]
years = ["2010", "2014", "2018", "2020", "2022", "2024", "2025"]
cpu_revenue = income.loc["Revenue"].loc[cpu_rivals, years] / 1e9
cpu_margins = sector.ratios.get_gross_margin().loc[cpu_rivals, years] * 100
cpu_roic = sector.ratios.get_return_on_invested_capital().loc[cpu_rivals, years] * 100
Which returns:
| Year | INTC Rev ($B) | AMD Rev ($B) | INTC GM | AMD GM | INTC ROIC | AMD ROIC |
|---|---|---|---|---|---|---|
| 2010 | 43.6 | 6.5 | 66.1% | 45.6% | n/a | n/a |
| 2014 | 55.9 | 5.5 | 63.7% | 33.4% | 22.8% | -16.1% |
| 2018 | 70.8 | 6.5 | 61.7% | 37.8% | 27.0% | 14.9% |
| 2020 | 77.9 | 9.8 | 56.0% | 44.5% | 23.6% | 50.2% |
| 2022 | 63.1 | 23.6 | 42.6% | 44.9% | 10.1% | 4.0% |
| 2024 | 53.1 | 25.8 | 32.7% | 49.4% | -10.9% | 2.8% |
| 2025 | 52.9 | 34.6 | 34.8% | 49.5% | -0.2% | 6.8% |
From 2010 to 2017, Intel was dominant by every metric. AMD spent this period losing money, cutting headcount, and struggling to produce a competitive architecture. Its gross margins compressed from 45.6% to below 30% in 2015 and 2016 as it competed on price with inferior products.
The inflection came in 2017 when AMD launched the Zen architecture under Lisa Su. The first Ryzen CPUs and EPYC server chips were genuinely competitive with Intel's best products. The financial data lags the product cycle: revenue did not break meaningfully higher until 2021-2022, and gross margin recovery tracked along with product mix shifting toward EPYC.
By 2022, AMD's gross margin had exceeded Intel's, a reversal that would have seemed implausible in 2015. By 2024 and 2025, Intel's ROIC had turned negative, meaning the company was destroying capital. Intel's $5 billion investment in foundry capacity between 2020 and 2024 has not yet returned the expected margins, and the company returned a net loss in 2025.
AMD's ROIC of 6.8% in 2025 is modest, reflecting the Xilinx acquisition ($35 billion, 2022) which dramatically expanded the invested capital base. The business is generating reasonable returns on operating assets; the acquisition debt is working against the ratio.
NVIDIA vs AMD: The GPU and AI Accelerator Race
AMD and NVIDIA have been GPU competitors since AMD's 2006 acquisition of ATI Technologies. Both companies design discrete graphics chips for gaming, professional workstations, and data center compute. In 2010, the two companies were comparable in size. By 2025, the gap was $130.5 billion versus $34.6 billion.
The divergence is almost entirely explained by AI infrastructure.
gpu_rivals = ["NVDA", "AMD"]
gpu_revenue = income.loc["Revenue"].loc[gpu_rivals, years] / 1e9
gpu_margins = sector.ratios.get_gross_margin().loc[gpu_rivals, years] * 100
gpu_roic = sector.ratios.get_return_on_invested_capital().loc[gpu_rivals, years] * 100
Which returns:
| Year | NVDA Rev ($B) | AMD Rev ($B) | NVDA GM | AMD GM | NVDA ROIC | AMD ROIC |
|---|---|---|---|---|---|---|
| 2010 | 3.3 | 6.5 | 35.4% | 45.6% | n/a | n/a |
| 2014 | 4.1 | 5.5 | 54.9% | 33.4% | 11.6% | -16.1% |
| 2018 | 9.7 | 6.5 | 59.9% | 37.8% | 37.5% | 14.9% |
| 2020 | 10.9 | 9.8 | 62.0% | 44.5% | 24.3% | 50.2% |
| 2022 | 26.9 | 23.6 | 64.9% | 44.9% | 32.2% | 4.0% |
| 2024 | 60.9 | 25.8 | 72.7% | 49.4% | 68.4% | 2.8% |
| 2025 | 130.5 | 34.6 | 75.0% | 49.5% | 102.6% | 6.8% |
Through 2020, the two companies moved roughly in parallel. AMD and NVIDIA were neck-and-neck on revenue. The ROIC numbers for 2020, AMD at 50.2% and NVIDIA at 24.3%, actually show AMD leading, a reflection of AMD's lean capital base at that moment before the Xilinx acquisition.
The separation happened in 2021 and accelerated through 2022 to 2025. The driver is not gaming GPUs, where AMD's Radeon line remains a genuine competitor for NVIDIA's GeForce range. The driver is AI training infrastructure. NVIDIA's H100 and Blackwell GPUs, running on CUDA, became the default compute substrate for training large language models. The software ecosystem, built over 15 years around CUDA, proved nearly impossible for AMD to replicate quickly with its ROCm platform.
The financial consequence shows in ROIC. NVIDIA earned 102.6% return on invested capital in 2025. AMD earned 6.8%. Both companies make GPUs. One of them has a software moat that the other does not.
AMD's position in this race is structurally harder than its Intel rivalry. Against Intel, AMD competes on x86 CPU performance, a problem of engineering execution. Against NVIDIA, AMD competes on AI software ecosystem depth, a problem of developer adoption and network effects that is slower and more expensive to overcome.
What the Market Is Pricing In
The financial history explains the divergence. Current valuations reflect where the market expects each company to go.
pe = sector.ratios.get_price_to_earnings_ratio()
ev_ebitda = sector.ratios.get_ev_to_ebitda_ratio()
current_valuation = pd.DataFrame({
"P/E": pe["2025"],
"EV/EBITDA": ev_ebitda["2025"]
}).sort_values("EV/EBITDA")
Which returns:
| Ticker | P/E | EV/EBITDA |
|---|---|---|
| QCOM | 34.1 | 14.2 |
| INTC | neg | 19.1 |
| TXN | 31.9 | 21.3 |
| NVDA | 63.5 | 55.5 |
| AVGO | 72.6 | 50.5 |
| AMD | 80.8 | 52.1 |
Qualcomm is the cheapest name on EV/EBITDA at 14.2x, pricing in limited AI exposure and the ARM licensing exposure risk. Texas Instruments at 21.3x is being valued as a stable analog business with cyclical revenue sensitivity.
Intel is uninvestable on P/E (the company is reporting losses) and its EV/EBITDA of 19.1x is elevated relative to the earnings power the business is currently generating. The market is either pricing in a recovery or pricing in acquisition optionality. The gross margin and ROIC data suggest recovery will take years.
NVIDIA at 63.5x P/E and 55.5x EV/EBITDA is expensive in absolute terms. Whether those multiples are justified depends on whether AI infrastructure CapEx remains elevated and whether NVIDIA maintains its software ecosystem lead. At 102.6% ROIC in 2025, the business is extraordinary; the question is the duration of that advantage.
AMD at 80.8x P/E trades at a premium to NVIDIA despite lower ROIC and a two-front competitive battle. The premium reflects expectations for ROIC recovery as the Xilinx acquisition amortizes and as AI GPU shipments scale. The execution risk is real.
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