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AI infrastructure investment is helping Samsung’s semiconductor business grow most clearly through memory: Samsung reported record quarterly Memory revenue and operating profit in Q2 2026, a record-high server share of its Memory sales mix, and scaled sales of HBM4. The growth also reflects limited supply and broad memory-price increases, so the company’s results cannot be attributed to AI alone. Foundry is a developing opportunity, but Samsung’s stated H2 growth is a target, not an achieved result.
What Samsung’s latest results say about AI-driven growth
Samsung Electronics’ latest reported quarter is Q2 2026, which ended June 30 and was announced on July 30. Companywide revenue reached KRW 171.5 trillion and operating profit was KRW 89.5 trillion. Its Device Solutions (DS) division, which includes Memory, Foundry and System LSI, reported KRW 127.5 trillion in revenue and KRW 89.2 trillion in operating profit. DS revenue rose 56% quarter over quarter, and Samsung said Memory set all-time quarterly highs for both revenue and operating profit.
Those totals show the scale of the semiconductor division’s contribution, but they are not an accounting of revenue generated by AI. Samsung did not disclose how much of its Q2 revenue or profit came specifically from AI-related products. Its own explanation is that Memory addressed AI demand while capacity was limited, and that industry-wide memory price increases also contributed. Conventional DRAM demand and conditions in mobile and PC markets are part of the wider picture too.
The clearest evidence of the AI connection is therefore a combination of product mix and company commentary, not a standalone AI revenue figure: Samsung reported a record-high server share of Memory sales and described demand from AI infrastructure as a driver of its record quarter.
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How the growth built across recent quarters
The pattern is easier to interpret when the latest quarter is set against the preceding results. The figures below are company-reported totals; “DS” is a division total, not a separate measure of AI-related sales.
| Period | Company revenue | Company operating profit | DS revenue | DS operating profit | What Samsung said about Memory |
|---|---|---|---|---|---|
| Q2 2026 | KRW 171.5 trillion | KRW 89.5 trillion | KRW 127.5 trillion | KRW 89.2 trillion | Record quarterly revenue and operating profit; AI demand, limited capacity and industry price increases contributed. |
| Q1 2026 | KRW 133.9 trillion | KRW 57.2 trillion | KRW 81.7 trillion | KRW 53.7 trillion | Memory exceeded its quarterly sales record by serving high-value AI demand despite limited supply; industry-wide price increases also contributed. |
| Q4 2025 | KRW 93.8 trillion | KRW 20.1 trillion | KRW 44.0 trillion | KRW 16.4 trillion | Memory set quarterly records as HBM and other high-value products expanded and the broader market price surge lifted results. |
| FY 2025 | KRW 333.6 trillion | KRW 43.6 trillion | Not stated as a full-year DS figure in the cited FY 2025 results release. | Not stated as a full-year DS figure in the cited FY 2025 results release. | Full-year results included higher-value products such as HBM, server DDR5 and enterprise SSDs; Samsung also cited market-price effects. |
The sequence shows a strong acceleration in reported results through the first half of 2026, particularly in DS. It does not isolate the effect of AI from pricing, product mix, supply availability or demand outside AI. The FY 2025 companywide figures also cover a full year, whereas the other rows are individual quarters; comparing them directly as if they were equal periods would be misleading.
Which memory products are benefiting from AI demand?
AI systems need more than one kind of memory. High-bandwidth memory (HBM) provides high data throughput for compute-intensive workloads; server DRAM supports server systems more broadly; and enterprise solid-state drives (SSDs) provide storage. Samsung’s disclosures point to demand across these categories rather than a single product explaining the entire upswing.
HBM: a high-value product with visible sales momentum
Samsung said it scaled HBM4 sales in Q2 2026 and shipped first HBM4E samples to major customers. Samples are not the same as volume sales: the announcement establishes that Samsung had advanced to customer sampling for HBM4E, not that the product had already become a large source of recognized revenue. In Q1, Samsung said mass product sales of HBM4 and SOCAMM2 for NVIDIA’s Vera Rubin platform had begun. The company’s FY 2025 release had already identified HBM among the higher-value products supporting Memory profitability.
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HBM matters to the growth story because it is a specialized, high-value memory product used in AI computing systems. Yet Samsung’s public results do not state HBM’s separate revenue, profit or contribution to the quarter’s increase. It is more accurate to say that HBM is one of the products benefiting from AI-related demand and part of the richer product mix than to treat it as the sole cause of Memory’s results.
Server DRAM and newer memory formats
Samsung reported that server products reached a record-high share of the Memory Business sales mix in Q2. It expected demand growth for server DRAM to accelerate in H2 2026 as AI infrastructure investment continued and adoption of agentic AI broadened. That expected acceleration is management’s outlook, not an independently verified forecast or a completed result.
The product set Samsung identifies also includes DDR5, SOCAMM2 and GDDR7. In its FY 2025 plans, it named HBM4, DDR5, SOCAMM2 and GDDR7 among products for 2026. Its Q1 release described mass product sales of SOCAMM2 alongside HBM4 for the Vera Rubin platform. These disclosures show that the company sees AI-related opportunity in a broader memory portfolio, although they do not quantify sales for each product.
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Storage is another part of the infrastructure demand story. In Q2, Samsung said it expected demand growth for enterprise SSDs to accelerate in H2. Its earlier releases described plans for PCIe Gen6 enterprise SSD offerings associated with KV-cache storage demand and high-performance TLC products for Key Value SSD inference demand. These references connect NAND products to storage needs in AI and inference systems, but they do not establish a separate AI-derived revenue total.
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Samsung’s management expected server-centered demand to remain robust as infrastructure investment continued, while also expecting some moderation in mobile and PC demand. That distinction matters: a semiconductor supplier can benefit from stronger server demand while facing softer demand in other end markets at the same time.
Why memory revenue can rise faster than unit demand alone
Samsung’s explanation points to three linked factors: demand for AI-related and other server memory, constrained capacity, and industry-wide price increases. When customers seek more memory than suppliers can readily provide, limited supply can support higher market prices. At the same time, a greater share of higher-value products can improve the revenue mix. Samsung cited all of these forces around its recent Memory results, but did not publish a breakdown that assigns a precise amount to each one.
Profit is not simply a synonym for revenue. It also reflects product mix, manufacturing costs and other expenses. Samsung reported record Memory operating profit in Q2, but the provided company-level and DS totals do not disclose a Memory-only profit figure or the proportion of the change attributable to AI products. Readers should distinguish the reported outcome from the explanation: the record is a result; the contribution of AI, prices and individual products is not separately quantified.
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Foundry is a second opportunity, but a less established one
Foundry is the business of manufacturing chips designed by customers. Its AI link differs from Memory’s: Samsung’s Q2 release tied improved foundry earnings before incentive-related provisions to HBM base-die demand and strong U.S. customer orders. It also identified 2nm high-performance computing engagements as notable design wins. A design win or customer engagement can indicate future opportunity, but it is not the same as a disclosed production volume or realized revenue figure.
For H2 2026, Samsung planned to ramp second-generation 2nm mobile production and expand 4nm LPU and base-die sales. It targeted double-digit foundry revenue growth over the half, citing demand across process nodes, advanced-node opportunities and AI/HPC design wins. This is a company target, not an outcome already reported. The release’s qualifier about earnings before incentive-related provisions is also important: it does not describe a clean, unqualified increase in reported foundry profit after all provisions.
The previous quarter shows why the foundry contribution should be described as developing rather than steady. In Q1 2026, Samsung said foundry earnings declined amid off-peak seasonality, although it maintained HPC-focused design wins and planned to increase HBM4 base-die supply. Against that uneven performance, the Q2 improvement and H2 target are evidence of an opportunity, not proof that foundry has already become as direct or consistent an AI growth engine as Memory.
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System LSI results should not be folded into the AI growth narrative without qualification. Samsung said Q2 performance was affected by flagship seasonality and weak mobile demand in China, while expanded mobile SoC and image sensor sales sustained quarterly revenue. It also noted orders for a next-generation flagship SoC, but did not quantify an AI-specific contribution to System LSI revenue or profit. On the disclosed evidence, Memory is the clearest AI-linked segment; System LSI’s AI contribution remains unestablished.
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What the Broadcom announcement does—and does not—mean
On July 25, 2026, Samsung and Broadcom announced an expanded strategic collaboration across memory, foundry and advanced packaging. Samsung said the companies expected collaboration to be estimated at more than $200 billion across memory and foundry over five years through 2030. That is the companies’ forward-looking estimate associated with an MOU, not booked revenue, a completed order or an amount Samsung has already earned.
The announcement does illustrate how Samsung frames AI infrastructure demand: as a need for tightly integrated memory, logic and advanced packaging technologies. Young Hyun Jun, vice chairman and CEO of Samsung Electronics’ Device Solutions Division, said: “AI is driving unprecedented demand for tightly integrated semiconductor technologies spanning memory, logic and advanced packaging.” The statement is useful as management’s view of the opportunity, not as independent evidence of a specific financial contribution.
How to read the growth story without overstating it
- Separate reported results from outlook. Q2 financial totals and record Memory performance are reported results; H2 server-demand expectations and the double-digit foundry growth target are forward-looking statements.
- Do not label all DS revenue as AI revenue. The DS division includes businesses with different products and market conditions, and Samsung did not publish an AI-only revenue attribution.
- Keep multiple drivers in view. Samsung cited AI demand, limited capacity and broader price increases; conventional DRAM demand and softer mobile or PC markets also affect the business environment.
- Distinguish products and stages. HBM4 sales and HBM4E customer samples are different milestones. Foundry design wins and engagements indicate potential, not automatically realized sales.
- Treat the collaboration estimate as a forecast. The Broadcom figure is the companies’ estimate over a stated five-year period, not a guarantee or recognized revenue.
The strongest supported conclusion is that AI infrastructure is contributing to a broader, high-value memory upswing at Samsung, with the most direct evidence in HBM and server-oriented products. Foundry offers a plausible additional route through base dies and AI/HPC customer work, but its contribution remains more dependent on future execution and targets than Memory’s already-reported records.
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