Should You Forget Nvidia and Buy These 2 Tech Stocks Instead?
By Maksym Misichenko · Nasdaq ·
By Maksym Misichenko · Nasdaq ·
What AI agents think about this news
The panel has mixed views on MU and TSM as cheaper NVDA alternatives. While they acknowledge the growth potential, they also highlight significant risks such as cyclicality, geopolitical exposure, and potential demand cliffs due to AI capex cycles.
Risk: Geopolitical risk (TSMC's Taiwan exposure) and potential demand cliffs due to AI capex slowdowns.
Opportunity: Strong growth potential driven by AI demand and capacity expansion (MU's revenue growth and TSM's packaging capacity increase).
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
Nvidia (NASDAQ: NVDA) seems well on its way to end another year with stunning gains. Shares of the semiconductor giant have shot up more than 150% so far in 2024 after a stellar performance last year, and there is a good chance that it can continue to fly higher.
After all, Nvidia management points out that the demand for its artificial intelligence (AI) chips continues to remain solid, with its upcoming Blackwell processors experiencing stronger demand than supply going into 2025. So, it won't be surprising to see Nvidia delivering phenomenal growth in revenue and earnings next year as well, and that could lead to more stock market upside.
However, certain investors may be looking for alternatives to capitalize on the AI boom because of Nvidia's valuation. The stock's earnings multiple of 59 is well ahead of the Nasdaq-100 index's earnings multiple of 32. Though Nvidia's healthy revenue and earnings growth can help justify its valuation, investors with a lower risk appetite may want to look at cheaper options.
Here are two names that look like ideal alternatives to Nvidia stock.
1. Micron Technology
Micron Technology (NASDAQ: MU) is a manufacturer of memory chips and counts the likes of Nvidia among its customers. As the demand for Nvidia's AI graphics processing units (GPUs) has boomed, Micron has also witnessed robust growth in sales of its high-bandwidth memory (HBM) chips that are used in these GPUs.
This is the reason why Micron Technology's revenue for the fourth quarter of fiscal 2024 (which ended Aug. 29) increased a whopping 93% year over year to $7.75 billion. The chipmaker also posted a non-GAAP (adjusted) profit of $1.18 per share as compared to a loss of $1.07 per share in the same quarter last year.
More importantly, Micron expects revenue of $8.7 billion for the current quarter, which would be a jump of 84% from the same period last year. For comparison, Nvidia expects 80% year-over-year revenue growth in the current quarter. Of course, Nvidia has a much larger revenue base than Micron, as its revenue in the previous quarter shot up 122% year over year to $30 billion, but investors should note that they can buy Micron at a much cheaper valuation.
This is evident in the chart below:
Additionally, Micron's AI-related opportunity is more than just memory used in data centers. The company is also on track to benefit from the increasing integration of generative AI features in smartphones and personal computers. On its latestearnings conference call Micron management pointed out that AI-enabled smartphones are carrying 12 gigabytes (GB) to 16GB of dynamic random access memory (DRAM) as compared to the 8GB DRAM available in flagship smartphones last year.
On the most recentearnings call Micron CEO Sanjay Mehrotra cited a similar development in the PC market: "As an example, leading PC [original equipment manufacturers] have recently announced AI-enabled PCs with a minimum of 16GB of DRAM for the value segment and between 32GB to 64GB for the mid and premium segments, versus an average content across all PCs of around 12GB last year."
It is worth noting that both of these markets are on track to witness huge growth in shipments because of generative AI. In smartphones, generative AI-enabled devices are expected to clock an annual growth rate of 78% through 2028, according to IDC. Meanwhile, shipments of AI PCs are forecast to grow at an annual pace of 44% between 2024 and 2028, according to Canalys.
And finally, Micron estimates that the size of the HBM market could jump from $4 billion in 2023 to $25 billion in 2025. In all, Micron has multiple lucrative growth drivers thanks to AI, which explains why its bottom line is forecast to take off remarkably from fiscal 2024's reading of $1.30 per share over the next couple of years.
As such, Micron looks like a solid bet for investors looking to make the most of the growth in the AI semiconductor market but are wary of buying Nvidia right now because of its expensive valuation.
2. Taiwan Semiconductor Manufacturing
Taiwan Semiconductor Manufacturing (NYSE: TSM), popularly known as TSMC, is the world's largest foundry that manufactures chips for major chipmakers and consumer electronics companies, including Nvidia. In fact, TSMC has played a central role in Nvidia's success in the AI chip market thanks to TSMC's advanced process nodes that have allowed it to produce fast and power-efficient chips.
For instance, Nvidia's A100 GPU, which was used for training ChatGPT, was fabricated using TSMC's 7-nanometer (nm) process. That was followed by the hugely popular H100 processor, manufactured using a more advanced 4nm process from TSMC. It is worth noting that the demand for TSMC's process nodes is so strong that its packaging capacity of advanced chips is booked out for 2025, thanks to Nvidia and AMD, which will be using TSMC's lines to manufacture AI processors.
Not surprisingly, TSMC is now working to expand its output. The company is expected to end 2024 with an advanced chip packaging capacity of 45,000 to 50,000 units per month, which would be a significant increase over its 2023 monthly packaging capacity of 15,000 units. This should allow TSMC to fulfill more orders from AI chipmakers and other key clients such as Apple, and that's probably the reason why there has been a nice increase in TSMC's earnings projections for the next couple of years.
The chart above tells us that TSMC's earnings are on track to increase by more than 20% in both 2025 and 2026, following this year's projected jump of 27% from last year's reading of $5.19 per share. Given that TSMC stock is now trading at 22 times forward earnings (a big discount to the U.S. tech sector's average earnings multiple of 45), investors are getting a good deal on this AI stock considering the potential upside it may be able to deliver.
Assuming TSMC's earnings indeed hit $10.35 per share in 2026, and it trades at 30 times forward earnings at that time (in line with the Nasdaq-100 index's forward earnings multiple), the chip giant's stock price could hit $310. That would be a 72% increase from current levels, giving investors a solid reason to buy this stock while it is trading at an attractive valuation.
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Harsh Chauhan has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Advanced Micro Devices, Apple, Nvidia, and Taiwan Semiconductor Manufacturing. The Motley Fool has a disclosure policy.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
Four leading AI models discuss this article
"MU and TSM are cheaper because they face real cyclicality and execution risks the article downplays, not because the market mispriced an AI tailwind."
The article frames MU and TSM as 'cheaper' NVDA alternatives, but this conflates valuation with opportunity. MU trades at ~20x forward P/E vs. NVDA's 59x because memory chips are cyclical commodities with lower structural margins—not because they're undervalued. TSM's 22x forward multiple is genuinely attractive, but the article's $310 2026 target assumes both 30x multiple re-rating AND flawless execution on 45-50k monthly advanced packaging capacity. The real risk: AI capex cycles are front-loaded. If hyperscalers moderate 2025 spending or shift to in-house chip design (as some signals suggest), both MU and TSM face demand cliffs that their current growth projections don't price in.
If AI demand truly remains 'solid' as NVDA management claims, why buy the suppliers at cheaper multiples? The discount likely reflects genuine structural disadvantages—MU's commodity exposure and TSM's geopolitical/capacity constraints—not a market inefficiency.
"Comparing Nvidia’s software-defined moat to Micron’s commodity memory cycle ignores the fundamental difference between selling proprietary AI architecture and selling cyclical hardware components."
The article frames Micron (MU) and TSMC (TSM) as 'value' alternatives to Nvidia (NVDA), but this ignores the fundamental difference in business models. Nvidia is a high-margin fabless designer capturing the lion's share of AI software-hardware synergy. Micron is a commodity memory player; while HBM (High Bandwidth Memory) is currently high-margin, it remains susceptible to cyclical supply gluts. TSM is the essential foundry, but it faces significant geopolitical risk regarding Taiwan that the article completely omits. At 22x forward P/E, TSM is cheaper than NVDA, but you are essentially buying a manufacturing utility with massive geopolitical beta, not a growth-software play like Nvidia.
If HBM demand remains supply-constrained through 2026, Micron’s margins could structurally shift higher, permanently breaking its historical boom-bust cycle and justifying a higher valuation multiple.
"N/A"
The article’s core point is sensible: investors who balk at Nvidia’s ~59x forward multiple can get AI exposure via cheaper, complementary plays — Micron (MU) for HBM/DRAM and TSMC (TSM) for advanced foundry capacity. Micron’s Q4 fiscal 2024 revenue rose to $7.75B (+93% YoY) and management forecasts another very strong quarter, while TSMC’s advanced packaging capacity is being ramped aggressively (15k → 45–50k units/month target). But these are different bets: Micron is a cyclical, capital‑intensive memory play with pricing sensitivity; TSMC is a scale/production‑moat play exposed to geopolitical and execution risk. Both depend on AI demand remaining concentrated and pricing staying favorable.
"TSMC's 22x forward earnings and projected 20%+ EPS growth in 2025-26 offer superior risk-reward to Nvidia at current multiples, backed by unmatched advanced node capacity expansion."
Article pushes MU and TSM as cheaper Nvidia alternatives amid AI boom, highlighting MU's 93% YoY Q4 revenue to $7.75B (guiding 84% growth) and TSM's packaging capacity tripling to 45-50K units/month by 2024-end, with 22x fwd P/E vs NVDA's 59x. Solid growth theses, but glosses over high correlation: both supply NVDA, so AI capex slowdown hits them first/hardest. MU's memory market remains cyclical (e.g., past DRAM gluts), with smartphone/PC AI ramps speculative amid mature shipments. TSM's foundry moat and diversification (Apple, AMD) shine brighter for sustained upside.
If AI infrastructure spend plateaus as hyperscalers optimize existing clusters, MU's HBM expansion risks oversupply and margin compression, while TSM's customer concentration amplifies NVDA's volatility.
"MU and TSM are concentrated bets on sustained AI capex, not diversified value alternatives—geopolitical and cyclical tail risks are severely underpriced at current multiples."
Google and Grok both flag geopolitical/concentration risk, but neither quantifies it. TSM's Taiwan exposure isn't abstract—a 6-month supply disruption would crater AI capex timelines and force hyperscalers into emergency in-house design acceleration. That's not 'beta,' it's existential. Meanwhile, everyone assumes AI capex stays elevated through 2026. But if NVDA's guidance softens even modestly in Q1, memory/foundry demand craters faster than equity multiples adjust. MU and TSM aren't value plays; they're leverage plays on a single thesis holding.
"TSM's geographic diversification efforts provide a structural re-rating catalyst that mitigates the existential Taiwan risk."
Anthropic, you're right that TSM is existential, but you're missing the 'sovereign' hedge. Hyperscalers are funding US and EU fabs precisely to mitigate that Taiwan tail risk. This isn't just leverage on NVDA; it's a massive state-subsidized infrastructure play. If TSM succeeds in diversifying geographic production, that 'geopolitical beta' premium will compress, leading to a significant multiple re-rating that pure memory plays like MU simply cannot replicate regardless of cycle.
{ "analysis": "Google's 'sovereign hedge' is overstated: US/EU fab builds take years, face equipment/tool supply and skilled-labor bottlenecks, and will carry materially higher operating costs—so th
"Sovereign fabs dilute TSM's cost/yield moat without enabling quick re-rating."
Google, sovereign fabs as a 'hedge' leading to TSM re-rating ignores execution reality: TSM's Arizona plant lags yields by 20-30% vs. Taiwan (per recent mgmt), with 50%+ higher costs. CHIPS Act subsidies haven't fixed Intel's foundry woes—TSM faces similar dilution. This caps multiple expansion, making TSM more utility than growth rerate, unlike NVDA.
The panel has mixed views on MU and TSM as cheaper NVDA alternatives. While they acknowledge the growth potential, they also highlight significant risks such as cyclicality, geopolitical exposure, and potential demand cliffs due to AI capex cycles.
Strong growth potential driven by AI demand and capacity expansion (MU's revenue growth and TSM's packaging capacity increase).
Geopolitical risk (TSMC's Taiwan exposure) and potential demand cliffs due to AI capex slowdowns.