Top 10 AI Hardware Compute Stocks to Watch in 2026
Artificial intelligence workloads depend on specialized hardware to train and run models. GPUs process large datasets quickly. Custom accelerators help speed specific tasks. Advanced semiconductor manufacturing enables these next-generation chips. This overview highlights top 10 AI stocks with essential roles in the AI ecosystem as we head into 2026. This overview highlights 10 key hardware compute stocks that play fundamental roles in the AI stack going into 2026. If you are new to AI, visit our AI basics section to learn more.
1. NVIDIA – GPU Compute Powerhouse
NVIDIA is a leading provider of AI optimized GPUs for modern artificial intelligence workloads. Its GPUs are widely used to train and run large generative AI models. In the third quarter of fiscal 2026, NVIDIA reported record revenue of $57.0 billion. This represented a 62 percent increase compared with the same quarter last year. The Data Center segment generated $51.2 billion in revenue during the quarter. This growth reflected strong global demand for AI compute infrastructure. Sales of Blackwell series AI chips contributed significantly to this performance. Data center revenue accounted for most of NVIDIA’s total quarterly sales.
NVIDIA’s leadership in GPU compute comes from broad adoption by major cloud providers and AI developers. This adoption makes NVIDIA a central player in the global AI infrastructure ecosystem. Analyst commentary and company guidance point to sustained demand for advanced AI chips. Revenue expectations remain strong as AI workloads continue to scale worldwide.
2. AMD (AMD) — Growing Competitor in AI Compute
Advanced Micro Devices has expanded beyond traditional CPUs into accelerated computing. Its Instinct GPUs and EPYC server processors support modern data center and AI workloads. These products are seeing increased adoption across enterprise and cloud environments. Recent investor communications highlight strong demand for AMD’s compute offerings. AMD’s growth strategy focuses on partnerships with cloud providers and AI platform developers. The company aims to increase its share within the AI hardware market.
Recent earnings releases show that AMD continues to increase its data center and AI-related revenue within a multi-billion dollar business. At its investor day and recent earnings calls, AMD outlined plans for continued expansion. The company aims to capture a larger share of the compute market over the coming years. Analysts view AMD as a credible competitor to established GPU providers. This is especially true for workloads combining AI acceleration with general server computing.
3. Taiwan Semiconductor Manufacturing Company (TSMC) — Foundry Powerhouse for AI Chips
Taiwan Semiconductor Manufacturing Company is the world’s largest dedicated semiconductor foundry and a critical backbone for AI hardware. TSMC manufactures advanced process nodes used by leading AI chip designers, including NVIDIA, AMD and others. In the third quarter of 2025, TSMC reported record revenue of approximately $33.1 billion, with profits rising significantly as demand for AI and high-performance computing chips continued to strengthen. This reflects sustained industry demand for chips used to train and deploy AI models as well as other advanced compute applications.
Management noted that AI-related chip demand was stronger than expected, and the company guided revenue for the subsequent quarter in the range of $32.2 billion to $33.4 billion, driven by continued growth in AI and high-performance workloads. TSMC’s role in scaling production of cutting-edge wafer technologies — including sub-7nm processes — positions it as a foundational supplier across the AI compute ecosystem, making it a key hardware infrastructure stock to watch as AI deployments expand.
4. Micron Technology (MU) — Memory Supplier Supporting AI Infrastructure
Micron Technology is a major supplier of DRAM, high bandwidth memory, and other memory products. These components are essential for modern AI compute systems. In the first quarter of fiscal 2026, Micron reported record revenue of $13.64 billion. Revenue increased sharply compared with the prior year. The company also reported strong earnings and improved operating cash flow. Micron attributed this performance to rising demand from AI data center deployments. High bandwidth memory is increasingly used to support fast data throughput for processors.
CEO commentary and forward guidance highlight strength in memory pricing and AI market fundamentals. Micron expects additional growth throughout fiscal 2026. This outlook is supported by tight supply conditions and sustained demand from AI infrastructure customers. The company is prioritizing high value memory solutions and capacity expansion plans. These efforts position Micron as a critical partner within the AI hardware ecosystem. Memory remains essential for high performance AI model training and inference.
5. Broadcom (AVGO) — Custom AI Accelerators and Networking Chips
Broadcom is a major semiconductor company serving high performance AI data centers. Its technology includes custom accelerators and networking products for large scale AI workloads. In the fourth quarter of fiscal 2025, Broadcom reported revenue of $18.0 billion. This represented a 28 percent increase compared with the prior year. AI semiconductor revenue grew by about 74 percent during the quarter. Growth was driven by strong demand for custom AI accelerators and Ethernet AI switches. Broadcom expects AI related sales to continue rising in fiscal 2026. Enterprises are expanding AI infrastructure across cloud and data center environments.
Broadcom’s products are widely used by hyperscale cloud providers and enterprise customers seeking alternatives to general-purpose GPUs. This makes the company a significant participant in the AI compute ecosystem. Its backlog of AI-focused product orders remains large, suggesting sustained demand for its custom hardware. Analysts continue to view Broadcom as one of the key non-GPU players benefiting from the growth of AI hardware spending.
6. Qualcomm (QCOM) — Expanding Into AI Data Center Chips
Qualcomm, traditionally known for mobile processors and communications chips, is strategically expanding into AI compute and data center hardware. In fiscal year 2025, Qualcomm reported total revenue of about $44.3 billion. This reflected stable performance while the company invested in new growth areas. Qualcomm announced development of two new AI chips, the AI200 and AI250. These chips are designed for AI inference workloads in data center environments. Commercial availability is expected in 2026 and 2027. This shift reflects Qualcomm’s strategy to diversify beyond traditional markets.
The company aims to build a presence in the growing AI infrastructure space. The acquisition of Alphawave IP supports improvements in connectivity and compute capabilities. These moves position Qualcomm near segments served by traditional GPU vendors.
7. Marvell Technology (MRVL) — Networking and Custom AI Silicon Provider
Marvell Technology supplies networking chips, custom AI silicon, and data-center interconnect products that support high-performance computing and AI workloads. According to its investor reports, Marvell delivered record revenue of about $2.006 billion in the second quarter of fiscal 2026, up roughly 58% year-over-year, driven by strong demand for AI-related products such as custom silicon and electro-optics solutions. Its data-center business now makes up a significant portion of total sales, reflecting its expanding role in AI infrastructure.
The company recently announced plans to acquire semiconductor startup Celestial AI for about $3.25 billion. This acquisition aims to strengthen its photonic fabric technology for advanced AI data center networks. The deal supports Marvell’s long term strategy in next generation AI infrastructure. It also complements a strong pipeline of data center and custom computing products. Together, these efforts position Marvell beyond traditional networking hardware in the AI compute ecosystem.
8. ASML Holding (ASML) — Lithography Backbone for AI Chip Production
ASML is a Dutch semiconductor equipment company that supplies advanced lithography machines. These machines are essential for manufacturing modern AI processors used by leading chipmakers. In the third quarter of 2025, ASML reported net sales of approximately €7.5 billion. Net income for the quarter reached about €2.1 billion. Results were supported by strong demand for extreme ultraviolet lithography systems. The company expects full year 2025 sales to grow around 15 percent compared with 2024. This growth reflects continued global investment in advanced logic and memory chips.
ASML does not design or sell chips directly. Its technology enables the production of smaller and more power efficient processors. These processors are critical for modern AI workloads. Demand for EUV and advanced lithography capacity remains strong. Semiconductor manufacturers continue scaling production of next generation AI chips. This positions ASML as a key infrastructure stock linked to AI hardware growth..
9. Intel (INTC) — Established Chipmaker with AI Strategy
Intel remains one of the largest semiconductor companies globally, with a broad portfolio that includes CPUs, accelerators, and AI-supporting technologies. In the third quarter of 2025, Intel reported revenue of $13.7 billion, exceeding analyst expectations. Improved performance was driven by investments in AI related compute and broader strategic shifts. The company highlighted rising demand for compute and data center technologies. AI workloads are creating new opportunities across several Intel product lines.
Despite this progress, Intel faces competitive pressure from dedicated AI hardware companies and continues to restructure parts of its business to focus more on high-growth areas. This includes increased investments in purpose-built accelerators, ASICs, and foundry services to support customers pursuing AI and advanced computing tasks.
10. KLA Corporation (KLAC) — Semiconductor Equipment for AI Chip Production
KLA Corporation plays a critical role upstream in the AI hardware ecosystem by providing inspection and process-control equipment that semiconductor manufacturers rely on to produce advanced chips. In its first quarter of fiscal 2026, KLA reported total revenue of $3.21 billion with strong profitability, reflecting growth in demand for tools used in logic, memory, and advanced packaging production.
AI-driven growth in semiconductor fabrication is expected to support continued investment in the equipment needed to make next-generation chips. Because advanced nodes and packaging techniques are essential for high-performance AI processors, companies like KLA that enable these production steps are positioned to benefit from broader industry spending tied to AI compute. Analyst commentary reinforces KLA’s exposure to this trend, given its leading market share in chip inspection and metrology tools.
Key Revenue Summary (2025 / Latest Reported Data)
| Company | Most Recent Revenue (Annual or Quarterly) | Context/Notes |
|---|---|---|
| NVIDIA (NVDA) | ~$187 B TTM (2025) / $130.5 B FY2025 | Record growth driven by AI data center GPUs and accelerated computing. TTM = trailing 12 months. |
| AMD (AMD) | ~$25.8 B (2024) | Significant AI momentum with data center growth; expecting growth into next years. |
| TSMC (TSM) | ~$33.1 B Q3 2025 | Record quarterly revenue with strong demand from AI chip makers. |
| Broadcom (AVGO) | ~$63.9 B TTM (2025) / ~$18.0 B Q4 | AI semiconductor revenue up significantly YoY. |
| Micron (MU) | ~$13.64 B Q1 FY2026 | First quarter 2026 record revenue driven by AI demand. |
| Qualcomm (QCOM) | ~$44.3 B FY2025 | Traditional mobile strong, with AI acceleration expansion plans. |
| Marvell (MRVL) | ~$2.006 B Q2 FY2026 | Strong YoY growth in networking and data center silicon. |
| ASML (ASML) | ~€7.5 B Q3 2025 | Key lithography machine provider for advanced AI chips. |
| Intel (INTC) | ~$53.1 B (2024) | Broad compute revenue with AI accelerator strategy. |
| KLA (KLAC) | ~$3.21 B Q1 FY2026 | Equipment supplier to chipmakers building AI silicon. |
Conclusion
The revenue snapshot above highlights the scale and diversity of companies powering AI hardware compute in 2026.
NVIDIA stands out with exceptionally large quarterly revenue heavily driven by AI data center sales, and its latest results show the magnitude of demand for GPU-based AI compute.
Companies like AMD, Broadcom, Qualcomm, Intel, and Micron maintain significant revenue bases while positioning products and technologies that support different pieces of the AI stack, from accelerators and memory to connectivity and general compute.
Foundries and equipment providers like TSMC and ASML do not build chips themselves but generate substantial revenue by enabling the manufacture of cutting-edge AI silicon. Their results reflect the capital investment in semiconductor infrastructure necessary to sustain AI growth.
The combined picture shows that the AI hardware compute ecosystem involves multiple revenue streams. Some companies derive large portions of their sales from AI-specific technology, while others benefit indirectly through memory demand, production tools, or the broader compute environment. This diversity highlights how AI demand is reshaping not just individual firms but the entire semiconductor and compute supply chain.
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