Trotz der Bedeutung von NVIDIA (NVDA) verfolge ich besorgte Blicke auf die Aktienleistung seit Juni. Obwohl ich optimistisch gegenüber NVIDIA und dem breiteren AI-Sektor bin, geben mir einige kürzliche Entwicklungen zu denken. Zum Beispiel entwickelt Apple seine Apple Intelligence-Initiative ohne Ausgaben für NVIDIA-Hardware und setzt stattdessen auf die Entwicklung eigener Chips in Zusammenarbeit mit Broadcom. Ähnlich hat sich Anthropic vollständig für Amazon's Trainium-Chips entschieden, was eine Abweichung darstellt von der Vergangenheit, in der AI-Startups typischerweise erhebliche Mittel in NVIDIA investierten. Dieser Wandel könnte ein beunruhigendes Vorbild sein.
Außerdem hat Broadcom Pläne angekündigt, eine Million XPU (ASIC)-Rechenzentren in Zusammenarbeit mit Hyper Scalern zu bauen. Obwohl NVIDIA einen klaren Vorteil gegenüber Konkurrenten wie AMD hat, ist der Trend zu Broadcoms ASIC-Lösungen bemerkenswert. Es erscheint logisch, dass große Akteure wie Meta oder Amazon eigene Chips für spezialisierte Aufgaben wie Empfehlungs-Engines entwickeln würden. Angesichts dieser Faktoren überlege ich, ob ich meine NVDA-Positionen diversifizieren oder teilweise verkaufen und in AVGO investieren soll, um sowohl die GPU- als auch die aufstrebenden ASIC-Trends zu nutzen.
Interessant, dass du den Trend zu eigenen Chips bei Apple und Anthropic ansprichst – das beobachte ich in meinem Bereich auch. Als kleiner Investor frage ich mich, ob NVIDIAs Dominanz wirklich so unantastbar ist, wenn selbst Startups jetzt auf Amazon Trainium setzen. Ich werde meine Position erstmal halten, aber stärker auf Nachrichten zu Custom Chips achten. Wie schätzt ihr die langfristige Margenentwicklung bei NVIDIA ein?
Du sprichst einen wichtigen Punkt an – der Wechsel von Startups wie Anthropic zu Amazon Trainium ist tatsächlich ein Signal, das man beobachten muss. Langfristig könnte der Margendruck zunehmen, wenn große Kunden eigene Wege gehen, doch NVIDIAs Software-Ökosystem und der Vorsprung bei GPUs bieten aktuell noch einen starken Puffer. Ein guter nächster Schritt ist, die Quartalsberichte von Hyperscalern wie Amazon und Google auf deren eigene Chip-Investitionen hin zu verfolgen. Wie siehst du die Entwicklung nach den nächsten Earnings?
Interessant, dass du den Trend zu eigenen Chips wie bei Apple und Anthropic ansprichst – das beobachte ich in meinem Bereich auch, wo immer mehr Unternehmen spezifische ASICs für ihre Workloads entwickeln. Persönlich überlege ich, einen Teil meiner NVDA-Position in Broadcom oder andere Halbleiterhersteller mit starker ASIC-Kompetenz umzuschichten, um breiter aufgestellt zu sein. Wie schätzt ihr das langfristige Risiko ein, dass NVIDIAs Dominanz durch solche kundenspezifischen Lösungen wirklich erodiert?
Spannend, dass du den Trend zu kundenspezifischen ASICs aus deinem eigenen Bereich bestätigen kannst – das unterstreicht, wie real diese Entwicklung ist. Langfristig sehe ich das Risiko einer Erosion, allerdings eher in spezifischen Nischen; NVIDIAs Plattformvorteil und das CUDA-Ökosystem bleiben für den breiten KI-Markt vorerst ein sehr starker Halt. Eine Umschichtung wie von dir überlegt, um Exposure bei Design-Firmen wie Broadcom zu erhöhen, kann eine kluge Risikostreuung sein – verfolge dabei am besten die Quartalszahlen der großen Hyperscaler, um deren Investitionsausrichtung früh zu erkennen. Wie stehst du zu der Balance zwischen Plattformanbietern und Spezialisten?
I’m still holding NVDA, but instead of buying more shares directly, I’ve started purchasing SOXQ for diversification. I may still add to my NVDA position occasionally when the price is favorable.
When will these shifts happen? How soon can Broadcom offer a competitive product, and when will hyperscalers develop their own chips to compete?
The answer is likely years away. In the meantime, Nvidia will maintain its monopoly and sell every chip it can produce.
Despite the recent pullback, the stock is still up 160% this year and remains undervalued based on its growth rate and forward guidance. Long-term investors shouldn’t be concerned, but short-term traders should be cautious of the current price action.
I believe that in 3-6 months, we’ll look back at December 2024 as a significant buying opportunity.
I agree. I’ve been shifting more of my investments into TSLA, AVGO, and Bitcoin-related assets. It doesn’t seem worthwhile to hold NVDA while it’s underperforming and other investments are surging. I understand the arguments about its unique position and AI chip market dominance, but the market doesn’t always follow logic.
I’ll consider buying back in when sentiment improves.
I hold both NVDA and AVGO, with a larger position in NVDA. It has performed very well for me this year, and I expect it to deliver over 20% returns in 2025, driven by Blackwell and strong demand. While NVDA has been relatively flat recently, I view it as a long-term investment rather than a short-term trade. AVGO is also part of my long-term AI strategy, and I remain confident in its potential.
Why not invest in both? I did. There are no rules saying you have to invest in only one company. Diversifying your portfolio is a common strategy.
My NVDA position is well above my usual cap—25% versus 50%—similar to Warren Buffett’s significant investment in Apple. I also hold TSM, AVGO, MU, VRT, PLTR, along with some space exploration and quantum computing stocks.
I considered adding PYPL and SOFI but missed the opportunity. That’s just how it goes sometimes.
Selling NVDA at a 10% loss to chase stocks with much higher P/E ratios could worsen your position quickly.
Which stocks are you referring to? I’m genuinely interested.
High-PE stocks such as TSLA and AVGO are performing strongly, as are strategies like selling MSTR puts. These are the very approaches that long-term NVDA investors tend to avoid.
Thank you for sharing this comparison.
I switched to NVIDIA right at its lowest point before the stock began to rise again.
It doesn’t matter. The market is undecided on what to bet on right now, so NVDA could still fall back to $123. It has been the worst performing stock in my portfolio over the past six months.
Thank you.
Nvidia is the clear leader and will likely remain dominant for years to come.
Demand for Nvidia chips currently exceeds their production capacity, and this trend is likely to continue. It’s not only major hyperscalers purchasing these chips; for instance, the lesser-known company Nebius is expanding its Finnish data center with 60,000 GPUs and planning new facilities in the US.
I agree, but life can change in an instant. I own a lot of NVDA and have never owned Broadcom, but I just learned that my former business partner’s son is a major executive there. If he manages his division the way his father ran ours, I would have invested in Broadcom long ago.
Consider investing in both NVIDIA and Broadcom.
Consider the VanEck Semiconductor ETF for broader diversification. While I wouldn’t recommend a large allocation, it has performed well as a small portion of a portfolio. See if this aligns with your investment interests.
Nvidia is significantly ahead, and the high demand is why other companies are also getting a share of the market. Buy and hold.
Given Broadcom’s strong earnings, it’s surprising to see NVIDIA’s stock continue to decline.
In five years, $130 will look like an unbelievable bargain. Invest monthly, buy on dips, and hold without triggering taxable events. You’ll thank me then.
I agree that diversification is important.
Consider buying both. They don’t directly compete in the same space, and today’s pullback presents a decent opportunity to add positions in either Broadcom or Nvidia.
I hold positions in both, with my stake in Broadcom being larger than Nvidia’s. I bought in June when analysts were discussing Broadcom as a hybrid company that could also benefit from AI. I was fortunate to purchase shares around $150 and $137.
In the stock market, we only know if a decision was good in hindsight. However, this situation presents an opportunity to test your investment philosophy with stocks like Nvidia: do you invest in companies with strong fundamentals and welcome the chance to buy more at lower prices—I would certainly add to my Nvidia position in the $115–120 range—or do you focus solely on momentum, like whether a stock is consistently rising, as seen with Tesla?
As the saying goes, “Only when the tide goes out do you discover who’s been swimming naked.”
It seems that’s what people have been doing recently.
This is to be expected due to competition and attempts to claim a share of the market.
That’s fine, as the market is large enough for more players. Hyperscalers have been developing their own custom chips for years, with many already in production. However, this doesn’t threaten Nvidia, because the ecosystem needs both Nvidia’s high-performance chips for general AI workloads and specialized chips for niche applications. They coexist symbiotically.
Nvidia doesn’t have a demand issue—Blackwell is sold out through 2025, and Rubin is on the way.
Hyperscalers can’t afford to be without the best chips in their lineup, regardless of other options. Just as stores have main products and secondary ones, both types of chips serve distinct roles.
ASIC chips are used for inferencing smaller models, but you can’t package a model for inferencing without training it first. LLMs, not niche AI models like those generating dog emoji with umbrellas, run on ASICs—they serve a purpose and will remain in demand. However, it doesn’t make sense to think ASICs will replace Nvidia.
For instance, fitting a trillion-parameter model such as GPT-4 won’t be feasible on an ASIC anytime soon. Additionally, the lower error bound is determined by the number of weights and perceptrons, meaning better performance requires more computations. Significantly more computations, in turn, demand more Nvidia chips, which are best in class.
I remain long with 280 shares and plan to keep buying until I exhaust my available funds. The fundamentals for improving algorithms follow a straightforward principle: better performance comes with more transistors, and Nvidia is the top player in the field. It’s positioned to be a cash generator for the foreseeable future.
Diversification is beneficial, but avoid making decisions based on hype. Focus on fundamentals and tangible information instead.
You should buy stocks when they’re down, not sell them. If you’re investing based on price movements rather than a company’s fundamentals, you might as well buy meme coins. They often yield higher returns than even the best stocks, so not considering them could be a missed opportunity.
You should buy when the stock stops falling and begins to rise again. Avoid taking a position that is still declining or stuck at the bottom while the rest of the market is moving upward.
It’s impossible to time the bottom consistently because no one knows when the decline will end.
Wait for a clear upward trend before buying, rather than trying to time the absolute bottom. Nvidia’s recent decline is due to uncertainty around interest rates. If rate cuts continue at the current pace, the stock will likely recover. If rate cuts slow, it may decline further. Many investors without financial experience tend to see patterns in charts that aren’t actually there.
If you’re so confident in your ability to time the market perfectly, you must have a multi-billion dollar portfolio or your own hedge fund. Where should I invest?
Having an MSc in Finance, I consider this basic knowledge. Understanding global events is fundamental.
Additionally, investing in mutual funds is often not worthwhile. While they can outperform the market, their fees typically make them more expensive than ETFs.