Advanced Micro Devices, Inc. vs Intel Corporation: Strategic Comparison

This in-depth comparison examines Advanced Micro Devices, Inc. and Intel Corporation across revenue, market value, business model, competitive positioning, and long-term growth strategy. Whether you are researching Advanced Micro Devices, Inc. on its own, evaluating Intel Corporation, or weighing the two companies side by side, the breakdown below highlights where each company leads and where the gap between Advanced Micro Devices, Inc. and Intel Corporation is widest.

On the headline numbers, Advanced Micro Devices, Inc. reports annual revenue of $34.6B against $52.9B for Intel Corporation, while their respective market capitalizations stand at $195.0B and $628.0B. Advanced Micro Devices, Inc. is headquartered in United States and Intel Corporation operates from United States, and those different home markets shape how each company competes.

Advanced Micro Devices, Inc.: $1.86. That was AMD's stock price in mid-2015. What happened between those two data points is one of the most dramatic turnarounds in technology history — and it wasn't luck. She bet everything on a single CPU architecture called Zen, outsourced manufacturing to TSMC, and told Wall Street to be patient. AMD doesn't make chips. It designs them — obsessively, expensively, brilliantly — and then hands the blueprints to TSMC in Taiwan, which does the actual manufacturing on the most advanced production lines on Earth. It's also why AMD's fate is partially in someone else's hands, but we'll get to that. The money comes from four places, and the mix has shifted dramatically in just three years. This is the crown jewel now. Pensando data processing units handle networking offload. Three years ago, this segment was half its current size. Semi-custom APUs power every PlayStation 5 and Xbox Series console sold worldwide. The console contracts provide predictable multi-year revenue but carry thinner margins than enterprise products. This is the Xilinx inheritance — FPGAs, Versal adaptive SoCs, Alveo accelerators. These go into telecom base stations, fighter jet avionics, automotive ADAS systems, medical imaging equipment, and industrial automation. The margins are excellent. The downside is cyclicality: telecom spending collapsed in 2023-2024, dragging this segment down before it recovers. The unusual aspect of AMD's economics is the margin trajectory. Gross margins have climbed toward 52-54% as the revenue mix tilts from low-margin console chips toward high-value data center products. The FY2025 results benefited from an AI infrastructure spending boom. Whether that spending level is sustainable is a question AMD can't answer alone. It does not manufacture any of them. The capital that doesn't go into factories goes into design engineering. It's Amazon. Amazon is doing something different. Every chip Amazon designs internally is a chip it doesn't buy from AMD. And Amazon is AMD's single largest customer category. Meta designs custom inference silicon. AMD can't sue them into buying EPYC. It can't lock them in with proprietary software the way NVIDIA does with CUDA. Now, Intel. The oldest rivalry in semiconductors — 55 years of it. Intel still ships more total server CPUs than AMD in absolute volume. It still has deeper enterprise relationships built over decades. EPYC went from near-zero server share in 2017 to an estimated 30-35% of x86 server shipments by 2025. If they do, AMD's share gains plateau. If they don't, AMD pushes toward 40-45% and the x86 server market effectively becomes a duopoly where AMD is the premium choice. My judgment: Intel recovers partially but not fully. AMD keeps gaining, just more slowly. Then there's NVIDIA in AI accelerators. AMD's pitch here is honest but limited: "You need a second supplier, and we're the only credible one." That's not a claim of superiority. It's a claim of necessity. NVIDIA's hardware is better today. NVIDIA's software network is vastly deeper. AMD exists in AI because the market structure demands an alternative, not because AMD has earned dominance through technical superiority. Where AMD wins decisively: platform breadth. That matters for customers managing complex infrastructure who want fewer supplier relationships. The fabless model shapes the financial profile in fundamental ways. Every major AI framework was improved for CUDA first. Every university teaches CUDA. Every enterprise AI team has pipelines built on CUDA libraries. AMD cannot manufacture a single advanced chip without TSMC. Not one. The CoWoS advanced packaging bottleneck in 2023-2024 already demonstrated this — AMD couldn't get enough AI accelerators built fast enough because packaging capacity was constrained. The third issue is regulatory. China represents enormous AI chip demand, and AMD is legally prohibited from serving much of it. That's a permanent addressable-market reduction that no amount of product innovation can fix. Intel can't do GPUs or FPGAs at AMD's level. NVIDIA can't do CPUs. Qualcomm can't do servers. Xilinx couldn't do any of it without AMD's distribution and platform integration. But breadth alone isn't a defense. That's not a marketing trick. Then there's the TSMC relationship. Every dollar of R&D goes into design, architecture, and software rather than keeping a factory running. Intel bears that factory burden. AMD doesn't. AMD now has this validation at every major cloud provider. Nobody currently has all six. The dominant wager is AI infrastructure. The AI play has three layers. AMD's accelerators compete on memory capacity and capacity — the MI300X offers 192GB of HBM3, which matters for large language models that need to fit in GPU memory. Second, software: ROCm needs to reach the point where enterprises can deploy AMD hardware without rewriting their CUDA-based pipelines. The supporting bets are simpler. EPYC keeps gaining server CPU share — AMD went from near-zero in 2017 to an estimated mid-30s percentage of x86 server shipments. Ryzen AI targets the emerging AI PC category where on-device inference creates upgrade demand. The Xilinx portfolio serves long-cycle embedded markets that provide margin stability when consumer segments get choppy. That's the metric that tells you whether the AI bet is working or whether AMD remains primarily a CPU success story with AI aspirations. The CPU side is nearly settled. The irony is, None of that is uncertain enough to lose sleep over. That's the irony Lisa Su has to solve. Santa Clara, 1969. The founding thesis was simple: the semiconductor industry needed a second-source supplier for Intel's chips, and someone technically capable should provide it. For its first two decades, AMD operated largely in Intel's shadow, manufacturing compatible versions of x86 processors under licensing agreements that gave Intel legal cover for market dominance claims while giving AMD revenue. The ATI Technologies acquisition in 2006 brought graphics processing capabilities that would prove essential two decades later when GPUs became the computational substrate for machine learning. At the time, it looked like an expensive bet on gaming. In retrospect, it positioned AMD to compete in AI compute before AI compute was a market category. AMD sold its Austin campus. It laid off thousands of engineers. What remained was a pure design firm with a single viable architectural bet — Zen — that Lisa Su and her engineering team had to execute flawlessly. If AMD's software stack crosses that line — call it the point where a Fortune 500 AI team can deploy Instinct accelerators without hiring dedicated porting engineers — then data center GPU revenue doubles by 2028 and AMD becomes a $50-60 billion revenue company. EPYC owns 30-35% of x86 server shipments and Intel would need three consecutive flawless generations to reverse that — something Intel hasn't managed since Haswell. This is two very different businesses wearing the same label. When those companies increase capital spending, AMD's numbers look spectacular. The company designs CPUs, GPUs, and adaptive computing products for data centers, personal computers, gaming consoles, and embedded systems. The company that should worry Lisa Su most isn't NVIDIA. But Intel has been executing poorly since roughly 2015, and AMD exploited every stumble. The question is whether Intel's new leadership can ship competitive products on a modern process node. That's a viable position — it generates billions in revenue — but it's fragile in a way that the CPU business isn't. No other company ships x86 CPUs, discrete GPUs, AI accelerators, FPGAs, and data processing units from a single vendor. The competitive position is the strongest it's been since the Athlon 64 era. Let me be direct about what keeps AMD's leadership up at night: CUDA. The embedded business recovers as telecom spending normalizes. The near-death years of 2012 through 2016 forced choices that determined the modern company. It spun off its manufacturing operations as GlobalFoundries.

Intel Corporation: It had lost inevitability. For thirty years, Intel was the metronome of computing — Moore's Law made flesh, stamped onto silicon, shipped inside every PC and server that mattered. Then the 10nm delay broke the cadence. AMD ate into CPUs. NVIDIA swallowed AI. The 18A process node is in volume production — ahead of TSMC's competing N2. Apple is reportedly evaluating Intel Foundry for chip manufacturing. This is either the greatest comeback in semiconductor history or the most expensive dead-cat bounce. Intel's revenue story is really two stories stitched together by a shared fab network. It's smaller, steadier, less exciting. The bet is enormous: fabs in Oregon, Arizona, New Mexico, Ireland, Israel, with a massive Ohio complex under construction. What makes Intel structurally unusual is the IDM model — Integrated Device Manufacturer. AMD doesn't do this. NVIDIA doesn't do this. Apple doesn't do this. They all send their designs to TSMC. Under Lip-Bu Tan, the workforce has been cut from 108,900 to roughly 75,000. The financial structure is still stressed, but the trajectory has shifted from decline to cautious recovery. It's TSMC. AMD and NVIDIA compete for Intel's customers. TSMC manufactured over 90% of the world's most advanced chips in 2025. Its N3 and N2 nodes serve Apple, AMD, NVIDIA, Qualcomm, MediaTek, and Amazon. That's the structural tension nobody has solved yet. EPYC captured over 30% of server CPU revenue by 2024. Ryzen owns meaningful desktop and laptop share. Every quarter Intel's foundry burns $2-3 billion in operating losses, AMD spends nothing on fabs and ships competitive products anyway. NVIDIA occupies a different competitive dimension entirely. It wants Intel's data center budget. Surprisingly, Millions of developers, thousands of improved libraries, enterprise workflows built over a decade. When Apple shipped M1 in 2020, it didn't just leave Intel — it proved that vertical integration could beat merchant silicon on performance-per-watt in premium computing. Government contracts requiring domestic manufacturing. Intel doesn't need to win every fight. It needs to win the foundry fight and hold enough product share to fund the transition. That's not a cyclical dip. That's structural share loss made visible in a P&L statement. But here's where it gets interesting. Q1 2026 broke the pattern. Gross margins recovered to 41% non-GAAP. Can Gaudi accelerators capture meaningful AI training budgets? And can Intel Foundry convert interest into committed wafer starts? External foundry customers don't commit billion-dollar chip designs based on one successful node. Most enterprises won't rearchitect their AI infrastructure to save 20% on hardware. Some of those people know things that aren't written down anywhere. Institutional knowledge walks out the door with every layoff round. If Intel Foundry can't serve its own internal product groups for all designs, why should external customers believe it can serve them? Not the products — the infrastructure. You'd need to spend $150+ billion on fabrication facilities across four countries. You'd need 130,000+ active patents covering transistor physics, interconnect chemistry, and packaging architecture. You'd need forty years of enterprise relationships with Dell, HP, Lenovo, AWS, Azure, and the U.S. Department of Defense. You'd need an installed base of billions of devices running software compiled for your instruction set. Nobody is doing that from scratch. Nobody. Enterprise software, Windows applications, database engines, virtualization layers, government systems — they all assume x86. The 18A node changes the manufacturing narrative specifically because it combines two innovations — RibbonFET (gate-all-around transistors) and PowerVia (backside power delivery) — in a single production node. TSMC's N2 uses gate-all-around but not backside power. Advanced packaging is the underappreciated asset. The U.S. Government's ~10% equity stake isn't just money — it's a political commitment. No. AMD executes well, NVIDIA owns AI software, Apple proved you can leave x86 and thrive. But displacing Intel requires replacing hardware, software compatibility, manufacturing capacity, government trust, and enterprise procurement relationships simultaneously. That's still extraordinarily hard. Everything else is supporting evidence. The 18A process node — RibbonFET gate-all-around transistors plus PowerVia backside power delivery — entered volume production in 2025 with Panther Lake laptop processors. The enhanced 18A-P variant promises 9% more performance and 50% better thermal conductivity. The 14A node is already in development for external foundry customers. Reports that Apple is evaluating Intel Foundry would be far-reaching validation — the customer that left Intel for its own silicon potentially returning as a manufacturing client. The U.S. Government's ~10% equity stake and CHIPS Act funding provide both capital and political cover for this ambition. The third lever is AI product revenue. Tan isn't trying to do twelve things. He's trying to do three things without the bureaucratic drag that made Intel slow for a decade. The obstacle is trust latency. That means Intel needs to be winning design starts right now for revenue that won't materialize until 2028. One data point suggests this is happening: Apple reportedly evaluating Intel Foundry. The irony would be extraordinary. Intel is winning the AI workloads that don't require CUDA. That's a real market, just not the headline market. That's how fast the money moved when Robert Noyce and Gordon Moore told him they were leaving Fairchild Semiconductor in the summer of 1968. No product prototype. It was supposed to make memory chips. Cheaper, denser, more reliable memory chips that could replace the bulky magnetic-core systems still humming inside mainframes across corporate America. Noyce was the public face: warm, persuasive, the kind of physicist who could charm a customer and inspire an engineer in the same conversation. Moore was the quieter force, the man whose 1965 observation about transistor doubling would eventually become the most cited prediction in technology history. The best engineers were leaving. Noyce and Moore decided to leave first. Intel's first commercial product, the 3101 SRAM chip, shipped in 1969. The 1103 DRAM followed in 1970 and became the world's best-selling semiconductor device within two years, proving that silicon could genuinely displace magnetic-core memory in production systems. Revenue grew. Credibility grew faster. In 1969, Busicom asked Intel to design a set of custom chips for a new calculator line. Federico Faggin led the physical implementation. The result was the Intel 4004, released in November 1971 — 2,300 transistors on a single chip, running at 740 kHz. Tiny by any modern measure. Revolutionary in concept. It was the first commercially available microprocessor, and it opened a door Intel hadn't planned to walk through. The 8008 followed in 1972. The 8080 in 1974. Then the 8086 in 1978, which created the x86 instruction set — the architectural lineage that would eventually run inside billions of PCs, servers, and data centers worldwide. None of this was inevitable. Software developers wrote for x86 because that's where the users were. Users bought x86 because that's where the software was. The flywheel spun. By 1985, Japanese DRAM manufacturers had turned memory into a commodity bloodbath. Intel was losing money on every memory chip it shipped. Intel has reinvented itself before. The question is whether it can do it again at 57 years old.

Advanced Micro Devices, Inc. and Intel Corporation pursue distinct approaches to generating revenue, and understanding how each company operates is the foundation of any fair comparison between Advanced Micro Devices, Inc. and Intel Corporation.

Advanced Micro Devices, Inc. business model: When they pull back, or when they design their own custom chips to reduce dependence on merchant silicon, AMD feels it immediately. TSMC in Taiwan runs the actual production lines on the most advanced nodes in the world — 4nm, 3nm — and AMD pays them to do it. But hyperscalers hate single-vendor dependence because it gives NVIDIA pricing power and supply use that no procurement team can tolerate indefinitely.

Intel Corporation business model: The first story is straightforward: Intel designs and sells processors. This is still the bread-and-butter business, the one that pays most of the bills. The Network and Edge Group (NEX) sells chips for telecom infrastructure, industrial automation, and IoT devices. Here's why: Then there's the second story — the one investors are actually pricing. Intel designs chips, manufactures them in its own fabs, packages them using proprietary technologies like Foveros 3D stacking and EMIB interconnects, and sells them to end customers. Honestly, revenue model: Intel earns revenue from client computing processors (laptops, desktops, workstations), data center and AI processors (Xeon, Gaudi accelerators), network and edge computing chips, and Intel Foundry services for external customers. Intel reported a GAAP net loss for FY2025 because restructuring charges, asset impairments, and the cost of cutting 33,900 jobs hit the income statement all at once. But the market is now pricing in success, which means the penalty for any stumble will be severe. It's also the reason the current turnaround feels so loaded with historical weight.

The durability of a company's moat often decides long-term winners. Here is how the competitive advantages of Advanced Micro Devices, Inc. stack up against those of Intel Corporation.

Advanced Micro Devices, Inc. competitive advantage: Instinct AI accelerators — the MI300X, MI325X, and the newer MI350 — sell to hyperscalers who need alternatives to NVIDIA's $40,000 GPUs. That's a treadmill, not a moat. The x86 server CPU business generates high margins with multi-year design win cycles — once an AMD EPYC chip is designed into a hyperscaler's server rack, that customer doesn't switch architectures for three to five years. The FY2025 acceleration reflects MI300X AI accelerator shipments at scale. The switching cost isn't technical — it's organizational. Set aside the word moat for a second. The real advantage is architectural. The chiplet approach — assembling large processors from smaller, higher-yielding dies connected by Infinity Fabric — gives AMD a manufacturing economics advantage that Intel has struggled to replicate. It's a genuine engineering innovation that translates directly into cost-per-transistor advantages. What rarely gets discussed is server ecosystem validation. Once EPYC is validated in AWS's infrastructure, the switching cost to move away from it is enormous — not because the hardware is irreplaceable, but because the qualification investment is sunk.

Intel Corporation competitive advantage: Intel's model was once its greatest advantage because tight coordination between design and manufacturing produced better chips faster. Competitive position: Intel's advantage is its x86 installed base across billions of devices, integrated manufacturing capability (the only Western company with leading-edge fabs), advanced packaging technologies (EMIB, Foveros), enterprise relationships, and strategic importance to US national security as the domestic advanced chip manufacturer. The switching cost isn't just technical — it's relational. The CUDA ecosystem locks in customers through software dependency, not hardware superiority. Intel's Gaudi 3 accelerators offer competitive specs on paper, but 'competitive specs' don't overcome ecosystem gravity. Where Intel retains genuine advantage: the x86 installed base spanning billions of devices and decades of enterprise software. And the sheer scale of its fab network, which becomes more valuable as geopolitical tension makes manufacturing geography a boardroom concern. CUDA isn't just software — it's an ecosystem with millions of trained developers, optimized libraries, and enterprise workflows built around NVIDIA's GPUs. Intel's Gaudi accelerators offer competitive price-performance on paper, but switching costs are real and high. Intel's x86 compatibility requirement is the quietest but most powerful lock-in in computing. Is the advantage as strong as it was in 2005?

Future prospects matter as much as current results. The growth strategies below explain how Advanced Micro Devices, Inc. and Intel Corporation each plan to expand from here.

Advanced Micro Devices, Inc. growth strategy: The growth rate here is what makes Wall Street pay attention. Ryzen processors for laptops and desktops, sold to Lenovo, HP, Dell, ASUS, and directly to enthusiasts who build their own PCs. The design-in cycles are long, meaning once a customer builds around your chip, they're locked in for 7-10 years. This fabless model means AMD carries no depreciation on semiconductor fabs, which typically cost $15-20 billion each to build. CEO Lisa Su, who took the role in 2014 when AMD's survival was not guaranteed, has built a product roadmap that covers every major segment of the computing market from gaming consoles to AI training clusters. Honestly, that's a fight AMD understands — build better chips, price them aggressively, win on total cost of ownership. It's building Graviton CPUs that replace EPYC in its own cloud. It's building Trainium accelerators that replace Instinct for its own AI workloads. The pattern is unmistakable: the four companies spending the most on compute infrastructure are all investing billions to reduce their dependence on merchant chip suppliers. It can only make its products so good, so cost-effective, and so easy to deploy that the build-vs-buy math keeps favoring buying. Goodwill impairment risk is now a real financial consideration — if Xilinx-derived products don't meet growth expectations, the accounting adjustment could materially impact reported earnings. Not NVIDIA's hardware — AMD can build competitive silicon. NVIDIA spent over a decade building CUDA into the default programming model for AI, scientific computing, and high-performance workloads. TSMC dependence is the second vulnerability, and it's existential in a way most investors don't fully appreciate. If Taiwan faces a geopolitical crisis, a major earthquake, or simply allocates more capacity to Apple and NVIDIA during a shortage, AMD's product launches slip and revenue evaporates. There is no Plan B. Building an alternative would cost $50+ billion and take a decade. Zen is now in its fifth generation, and each iteration builds on validated customer deployments rather than starting from scratch. AMD can build a 128-core server chip from eight identical compute dies plus I/O dies, achieving yields that would be impossible with a single monolithic slab of silicon. The result is higher returns on invested capital when products are competitive. AMD's growth strategy centers on a single dominant wager surrounded by complementary plays. First, hardware: MI300X shipped in volume through 2024-2025, MI350 is ramping now, and the roadmap extends through MI400. That growth should continue as long as the architecture stays competitive. The single data point that determines everything for AMD is data center GPU revenue growth rate quarter over quarter. Ryzen AI in PCs is a steady grower, not a moonshot.

Intel Corporation growth strategy: Apple proved you could build a better laptop chip without Intel's help. AI-driven businesses hit 60% of Q1 2026 revenue, growing 40% year-over-year. Each leading-edge fab costs $20-30 billion to build and equip. Strategic direction: Under Lip-Bu Tan, Intel is executing a disciplined turnaround focused on manufacturing excellence (18A in production, 14A in development), AI product competitiveness, workforce efficiency, and proving Intel Foundry can win external customers. AMD doesn't need manufacturing breakthroughs — it rents TSMC's fabs and focuses purely on design. Amazon's Graviton now powers a growing share of AWS instances. One bad quarter of 18A yields could unwind months of trust-building. You'd need a government that considers your survival a matter of national security and has invested accordingly. Foveros (3D die stacking) and EMIB (2D high-capacity interconnects) let Intel build chiplet-based systems where different components can be manufactured on different process nodes and assembled into a single package. Lip-Bu Tan's turnaround has one thesis fundamentally: manufacturing leadership is the strategy. Surprisingly, if Intel can sustain this cadence, it restores something the company hasn't had since 2015: a credible manufacturing roadmap that customers can plan around. That's not NVIDIA-level dominance, but it's meaningful participation in the industry's fastest-growing spending category. AI revenue at 60% of Q1 2026's mix and growing 40% annually provides breathing room, but most of that is Xeon inference and AI PC processors, not Gaudi training accelerators going toe-to-toe with NVIDIA. No administration lets that investment go to zero. But political insurance doesn't build chips. Yields build chips. Just two names that carried enough weight in the semiconductor world to make investors write checks on reputation alone. The company they incorporated — first as NM Electronics, then renamed Intel, a contraction of 'integrated electronics' — wasn't supposed to build microprocessors. Together they'd already helped build Fairchild into the most important semiconductor company of the 1960s, but Fairchild's East Coast parent company had turned the place into a bureaucratic cage. Ted Hoff, an Intel engineer, proposed something radical: instead of building dedicated logic for one product, why not design a general-purpose processor that could be programmed for different tasks? When IBM chose the 8088 (a cost-reduced 8086 variant) for its Personal Computer in 1981, Intel got lucky in a way that few companies ever do: IBM's open architecture meant clone makers could build compatible machines, and every clone needed an Intel-compatible processor. But the hardest decision in Intel's early history wasn't a product launch — it was a product funeral.

A closer look at the financial trajectory of Advanced Micro Devices, Inc. and Intel Corporation rounds out the comparison.

Advanced Micro Devices, Inc.: Today it's worth north of $170 billion. FY2025 revenue landed at $34.6 billion. That's a 5x increase from 2019's $6.7 billion. Data Center alone — EPYC servers and Instinct AI accelerators — pulled in $16.6 billion, making it the company's largest business for the first time. Under CEO Lisa Su, the company executed a turnaround through Zen architecture, chiplet design, and TSMC manufacturing partnerships, growing revenue from $4B to $34.6B between 2014 and 2025. This fabless model is why AMD can spend $6 billion a year on R&D without also burning $15-20 billion on factory upgrades the way Intel does. Data Center: $16.6 billion in FY2025. Client: $7.6 billion. Gaming: roughly $7 billion. Embedded: approximately $3.5 billion. AMD grew from $6.7 billion in revenue in 2020 to $34.6 billion in fiscal year 2025. Data Center revenue reached $16.6 billion in FY2025, nearly half of total company revenue. The Xilinx acquisition in 2022 for $35 billion added field-programmable gate arrays to AMD's product range, and the 2024 ZT Systems acquisition brought server integration capabilities. FY2025 Data Center revenue of $16.6 billion, nearly half of AMD's $34.6 billion total, is the number that explains why the market values the company at approximately $195 billion. Revenue trajectory: $22.7 billion in 2022, $22.7 billion in 2023 (essentially flat during an AI infrastructure investment pause), then $25.8 billion in 2024 and $34.6 billion in FY2025. Net income reached $4.3 billion in FY2025 against a market cap of approximately $195 billion — a valuation that prices in substantial future growth from AI infrastructure. AMD has no capital expenditure for manufacturing facilities, so free cash flow conversion from operating income is high. The Xilinx acquisition for $35 billion in 2022 added the Adaptive and Embedded segment, which contributed revenue but also created $26 billion in goodwill on the balance sheet. AMD gets access to the world's best manufacturing without spending $20 billion a year maintaining fabs. The Silo AI acquisition ($665 million) and investments in PyTorch compatibility, vLLM inference improvement, and Hugging Face integrations are all aimed at this. Third, systems: the ZT Systems acquisition ($4.9 billion) gives AMD rack-level design expertise so it can sell complete AI clusters, not just individual chips. The entire valuation debate — whether AMD is worth $170 billion or $300 billion — reduces to a software question masquerading as a hardware company. The relationship was adversarial from the start — AMD filed antitrust complaints against Intel in 2005, alleging that Intel paid PC manufacturers to exclude AMD chips, a case that settled for $1.25 billion in 2009.

Intel Corporation: The stock cratered below $100 billion in late 2024. Eighteen months later, Intel's market cap sits near $628 billion. FY2025 revenue was $52.9 billion, and the stock surged 170% in early 2026. The Client Computing Group (CCG) — laptops, desktops, workstations — generated $32.2 billion in FY2025, making it the company's largest segment by far. The Data Center and AI Group (DCAI) brought in $16.9 billion, up 22% in Q1 2026 as AI inference demand pulled Xeon server processors back into growth. This segment lost over $10 billion in FY2025 because Intel is building capacity years ahead of revenue. The Altera FPGA business was sold to Silver Lake for $8.75 billion. Q1 2026 showed early signs it might work — revenue of $13.6 billion beat guidance by $1.4 billion, AI businesses reached 60% of the mix, and non-GAAP gross margins recovered to 41%. Intel Corporation reported $52.9 billion in revenue for fiscal year 2025, with Q1 2026 showing 7% year-over-year growth to $13.6 billion as AI-driven businesses reached 60% of revenue. Market capitalization surged to approximately $628 billion by May 2026 after the stock rose 170% in early 2026, driven by 18A manufacturing success, US government equity investment, and reports of Apple evaluating Intel Foundry. NVIDIA's data center revenue exceeded $47 billion in FY2024 — nearly three times Intel's entire DCAI segment at $16.9 billion. The number that tells Intel's story isn't $52.9 billion in FY2025 revenue. It's the gap between $79 billion (FY2021 peak) and where the company sits now — a 33% decline in four years while competitors grew. Revenue hit $13.6 billion, beating guidance by $1.4 billion. Non-GAAP EPS came in at $0.29 versus a consensus of $0.01 — not a small beat, a 29x beat. The stock's 170% surge to a ~$628 billion market cap reflects this inflection, but it also prices in a lot of future execution. The Altera sale to Silver Lake ($8.75 billion for 51%) helped the balance sheet but also removed a revenue stream. Intel Foundry lost over $10 billion operationally in FY2025 — the cost of building fabs years before customers fill them. Capital expenditure runs above $25 billion annually. Q2 2026 guidance of $13.8-$14.8 billion suggests management sees continued momentum. Everything else — the workforce cut to 75,000, the Altera divestiture for $8.75 billion, the organizational flattening — is about removing friction from these three bets. The timeline is tight, the execution bar is high, and the stock at $628 billion already prices in substantial success. Arthur Rock raised $2.5 million in a single afternoon. That shift — painful, identity-destroying, and absolutely correct — is the reason Intel became a $79 billion revenue company three decades later.