Deep Dive: Is Nvidia Undervalued?

Today we are talking about the most important stock in the world right now, in video.

In video just drop their latest earnings report this week and once again the numbers blue expectations out of the water yet the stock still dropped. So in today's deep dive we'll take a closer look at and videos earnings and why some are concerned about the company moving forward. Well also take a look at the bull case and why some investors think that Nvidia is actually

undervalued right now. We got a great one for you today. Let's dive in.

“Alright let's take a closer look at Nvidia's earnings because honestly the numbers are absurd.”

For the fourth quarter in video reported 68.1 billion dollars in revenue that's up 73%

from the same quarter last year. Net income came in at 43 billion dollars which is a 94% jump

year over year. The majority of the growth is coming from the data center business which includes their AI chips. Data center revenue was 62.3 billion dollars going 75% year over year and now accounts for over 91% of the company's total revenue. You know it wasn't that long ago that Nvidia was a gaming company but they're gaming division only bought in 3.7 billion dollars in Q4. These days Nvidia is a full on AI chips company and I was listening to the earnings

call and on that call Nvidia said that their data center business has increased by 13 times since the launch of chat GPT. I mean that was like 3.5 years ago so the growth in Nvidia's business has been absolutely crazy in a very short amount of time. Now taking a little deeper gross margins held strong at 75% which was right in line with expectations. Now there's been concerns that

“Nvidia's margins might start to slip but that's not the case so far. Honestly I find it very”

impressive that Nvidia is selling hardware and able to generate software like margins. And one

number that really jumped out to me was their networking revenue. Nvidia made nearly 11 billion dollars

and networking sales which was up 263% year over year. Now this networking business includes their envy link technology and their spectrum X Ethernet switches. This is the stuff that connects the hundreds of Nvidia GPUs together in data centers to create these massive GPU clusters. So this shows that Nvidia's customers aren't just buying their chips but they're also buying entire AI systems. And speaking of Nvidia's customers from this earnings report we learned that the hyperscalers

accounted for over 50% of Nvidia's data center revenue. The hyperscalers include Microsoft, Meta, Amazon and Google. So Nvidia has making half the revenue from just four companies. We're gonna talk more about that in a bit. Overall though if you zoom out Nvidia ended their fiscal year with over $215 billion in revenue and $96.7 billion in free cash flow which is just nuts. I mean across the board this was a dominant quarter and management doesn't expect things to slow

down anytime soon. The company expects Q1 revenues to come in at $78 billion which is hired in the $73 billion that analysts were expecting. Nvidia stock did initially pop around two to three percent after their earnings came out on Wednesday afternoon but then by Thursday the stock had dropped more than 5% and then on Friday the stock dropped another 4%. So despite beating on every metric across the board Nvidia stock is down almost 10% following their earnings report. So let's get into the

bear case and why investors are suddenly so nervous about Nvidia going forward. All right so if Nvidia

“is printing money and crushing expectations why do the stock lose nearly 10% of its value in two days?”

Well the thing is the market is forward looking and right now investors are getting seriously spooked by a few looming risks when it comes to AI. I think the market is going through an identity crisis. On one hand AI is an incredible technology and it's getting better every month and companies are embracing it spending hundreds of billions of dollars on it. But on the other hand some investors are starting to ask what if AI being so good is actually bad for the economy? Our few days

ago there was a sub-stack post by satrini research that went mega viral. The post was framed as a research memo from the year 2028 and it laid out a completely dystopian view of AI's economic impact. The whole piece was very long like 7,000 words and it essentially makes the point that AI will keep getting better and companies will keep replacing white color workers with AI and those displaced workers will stop spending money and that's going to trigger a broader economic collapse.

Now personally I think the satrini piece is a bit too sci-fi for me to take seriously but the market's definitely took notice. Textdocs fell on Monday following the report and that just tells you how fragile sentiment is around AI right now. We saw something similar happen with deep seek back in January of last year when that Chinese AI started shocked the market and Nvidia stock dropped 17% in a single day so the AI narrative can turn on a dime and because

Nvidia is so tied to the AI narrative any shift in the sentiment hits Nvidia stock pretty hard.

He published a negative piece about Nvidia following their earnings report.

“Michael Burrie pointed to Nvidia's purchase obligations going from $16 billion a year ago”

to over $95 billion today. These purchase obligations are non-cancelable commitments

and Nvidia has to make to their suppliers like TSMC to secure chip production capacity. It looks like Nvidia has already committed pretty much all their free cash flow on this capacity. The point that Burrie is trying to make is Nvidia is being forced to place these massive orders well before they actually know what demand will look like. TSMC is requiring these longer term contracts because Nvidia chips have gotten so complex that TSMC has to build custom fabrication

capacity just for Nvidia. So essentially Nvidia is placing huge bets on future demand without knowing if that demand will be there. Burrie compares this to what happened with Cisco back in the dot com bubble. Cisco was the picks and shovels play at the late 90s internet boom just like Nvidia is for AI today and at the time Cisco extended massive purchase commitments expecting 50% annual growth to continue. While when enterprise IT spending collapse,

Cisco had to write down about 40% of its supply chain obligations and Cisco stock 10.

“So I think Burrie thinks that could also happen to Nvidia. There's a pullback on AI spending”

that something will happen. Maybe Nvidia could suffer the same fate that Cisco did back during the dot com crash. And that's the key question here, right? Will there actually be a pullback in AI spending? Especially from the hyperscalers. As I mentioned earlier, 50% of Nvidia's revenues come from meta Microsoft Google and Amazon. And these companies are expecting to spend close to $700 billion combined on AI infrastructure this year. But all this

capex spending is actually wrecking havoc on the balance sheets of these companies. Google, Microsoft, Amazon, and Meta are all expected to see a noticeable decline in free cash flow this year. In fact, Amazon is expected to go into negative free cash flow from all their capex spending. So it's possible to share holders of these companies might start pushing back and asking whether this capex spending is actually worth it. In fact, the stock price for all the hyperscalers

is in the red this year. If the stock price continues to fall, there's going to be more pressure on management to potentially scale back capex. And if that happens, Nvidia could take a big hit. And finally, the last concern when it comes to Nvidia is competition. Now, look, Nvidia still dominates the AI chip market. But for the first time, it feels like competition is getting serious. And the reason competition is heating up is because the industry is shifting. AI is moving

from the training phase where you need massive GPU clusters to train frontier AI models, something that Nvidia chips are really good at, to the inference phase, which is actually running AI to answer queries from users. The thing is inference doesn't

always require the same level of GPU power that training does. And that's opening the door

for alternative chips like AMD. That AMD just announced a $100 billion partnership with Meta. And Meta said that these AMD chips will primarily handle inference workloads. And then you have some of these hyperscalers working on their own AI chips. Google already has their TPU chips, Amazon has their training chips, and Microsoft and Meta are working on their own custom silicon as well.

These hyperscalers just don't want to be reliant on Nvidia. So that could hurt Nvidia's market share in pricing power down the road. Now, Nvidia kind of brushed off the competition concerns on the conference call. The CFOs to that Nvidia is the king of inference, which I guess is true for now. But you know, there are a few reasons to be bullish on Nvidia. So let's talk about the bull case moving forward. And why some people think that Nvidia

is undervalued right now, despite being the most valuable company in the world. Okay, so I've laid out some real concerns when I come to Nvidia. But there are several reasons to believe that Nvidia's generational run still has legs, and that the AI trade is alive and well. For one, we gotta go back to the hyperscalers. They're planning to spend $700 billion on capex, a lot of that going towards building AI infrastructure. And the thing is, these companies

are starting to see a return on their AI investment. Nvidia says that the use of generative AI is already delivering measurable results for clients and areas like search optimization, ad generation, recommendation systems, and developer productivity. Meta is probably the best example of this in their recent earnings call. They said that AI is helping them improve ad targeting, which is leading to more revenue. In fact, Meta saw an acceleration of revenue in

their recent quarter. Google also said something similar in their earnings call. So I know these capex numbers are huge, but as long as these companies are seeing an ROI on their capex spend, which it looks like they are now, they're not going to slow down spending anytime soon.

“And I think investors are going to be okay with it. Again, as long as revenue is accelerating.”

The reality is the more money these companies spend, a lot of that's going to trickle to

Nvidia because they still have the best AI chips. In fact, Nvidia has outlined a $500 billion or a cumulative revenue opportunity across its black well and upcoming Rubin chip platforms.

assumptions, it provided just a year ago. So demand has been stronger than they projected

“themselves. Now, remember what I said earlier that Nvidia is starting to face competition,”

especially when it comes to inference chips. Well, the Wall Street general just reported that Nvidia is working on a chip specifically designed for inference computing. For this new inference chip, they've incorporated technology from a startup called Grok that Nvidia essentially acquired

last year for $20 billion. Now, this chip hasn't even come out yet, and OpenAI is already

agreed to be one of the largest customers of this chip. So Nvidia saw the inference threat from AMD and others and they're moving to address it head on. Next, let's talk about agentic AI. On the earnings call CEO Jensen Wang declared that agentic AI inflection point has arrived and he called it the next chat GPT moment for the industry. Now, what agentic AI refers to is AI systems designed to execute complex multi-step tasks with limited human supervision. These are AI systems

that don't just answer questions, they actually take action. These AI systems could be used to

“monitor patient data and hospitals and flag issues or detect cybersecurity threats and respond”

in real time. Or maybe manage entire supply chains autonomously. And the reason why the rise of AI agents matter for Nvidia is up until now Nvidia's revenue growth had been heavily concentrated amongst the handful of hyperscalers. But agentic AI is expanding AI adoption into the enterprise world. You know, I'm talking banks, hospitals, manufacturers, logistics companies, they're all going to be needing computing power to run these AI agents. So that means that Nvidia's customer base

could get a lot broader. Next up, let's talk about China because this might be the most underappreciated part of the bullcase. Right now Nvidia generates $0 in revenue from China. Keep in mind, China is the largest semiconductor market in the world, yet Nvidia makes no money from them. And this is all because of export restrictions, but that might be changing soon. So the backstory here is that Nvidia has been locked out of China because of US export restrictions,

but the US government recently granted Nvidia a license to export a small number of their

powerful H200 ships to China. But that's just one side of the equation because now the Chinese

government has been hesitant to allow Nvidia's chips into their country due to its own national security concerns. China also wants to funnel support to their homegrown rivals like Huawei. But Bloomberg recently reported that the Chinese government began telling tech firms like Alibaba that they can prepare to start ordering Nvidia's chips. In the market, it's already adjusted to Nvidia not being in China. So whatever revenue that Nvidia ends up making is just upside.

Jenton seems to think this could be a $50 billion opportunity. Now to wrap up the bullcase, I have to talk about valuation. I know it sounds kind of crazy to say, but the most valuable company in the world might be under value. So hear me out here, okay? Nvidia currently trades at less than 22 times forward earnings. This is well below its five year average of around 37 times.

In fact, Bloomberg reported that Nvidia is now cheaper than roughly one third of all the stocks

“in the S&P 500. The best way that I can put this into perspective is that Nvidia's revenues”

grew 65% last year, which makes it the third fastest growing company in all of the S&P 500. And right now the stock is trading basically at the same forward PE as an average S&P 500 company. Meanwhile, you have a company like Palantir, which has a similar growth rate to Nvidia, but that stock is trading nearly 100 times forward earnings. So that just kind of puts in the perspective why Nvidia might be undervalued trading at 22 times forward earnings.

So what's my take here? Well look, I'm not going to sit here and tell you that Nvidia is a risk-free investment. In fact, I think that there are valid concerns. I'm also concerned about the AI doomerism stuff where AI is going to destroy the economy. I'm more concerned about the potential pullback in AI spending from the hyperscalers in competition from custom made chips. But that being said, the valuation is pretty mind-blowing. Nvidia grew revenues at 65% in 2025, and their guidance

continues to blow past expectations moving forward. Now to mention the shift from AI training to a genetic AI is a massive tailwind and then China could also come back into play. So at 22 times forward earnings, it's hard not to think that Nvidia might be undervalued. The fundamentals of the company are strong. But given that the market is spooked about AI right now, there could be some short-term pain and volatility as everyone tries to figure out what an AI economy will look like going forward.

Well all right guys, that's it for today's weekend deep dive. Hope you guys enjoyed today's episode. Let us know in the comments on Spotify or YouTube what you thought about today's deep dive, and if you're bullish or bearish on Nvidia moving forward. And why you added don't forget to hit us with a five star rating and vote in today's Spotify poll. All of that engagement really does help us out and it helps other people find the show. Thank you guys so much for listening,

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