Nvidia stock has reacted positively to an adjusted EPS Q4FY23 beat of $0.88 vs $0.80 and a Q1FY24 revenue guide of $6.5B vs $6.32 consensus. The most important statement on the call was: “We expect sequential growth to be driven by each of our 4 major market platforms led by strong growth in data center and gaming”We expect sequential growth to be driven by each of our 4 major market platforms led by strong growth in data center and gaming” as it supports the H2 rebound.
Nvidia’s current quarter weakness is already priced in, yet the anticipation is high that Nvidia nails the turnaround come the October quarter. This quarter — especially with the comment on sequential growth comment across all four quarters — makes this outcome a bit more likely.
We had recently written about Big Tech’s prioritization of AI related infrastructure and how Nvidia was well positioned to benefit from this secular trend here and here. We listened for further evidence of this from the conference call. Big Tech capex can’t be overestimated in terms of how Nvidia will perform, and the comments about re-allocating for AI investments was further reflected in Nvidia’s report.
Financials:
$6.05B revenue came in line with prior guidance and consensus estimates, up 2% sequentially and down 21% year-over-year. For the full year, total revenues came in at $26.9B, flat year over year.
Next quarter’s revenue guide was $6.5B, better than consensus of $6.32B.
Adjusted eps came in $0.88 which beat consensus of $0.80.
Within the main business segments, Data centers came in at $3.6B, down 7% sequentially, and up 11% year-over-year. Gaming revenue was $1.8B, up 16% sequentially and down 46% YoY. Importantly, gaming’s sequential improvement showed further evidence that it had bottomed. We wrote about this in November here.
Gross and adjusted gross margins came in at 63.3% and 66.1%, in-line with guidance. Operating and adjusted operating margins came in at 20.7% and 36.8%, in-line with guidance.
Both gross and operating margins showed sequential improvement as China related inventory write-downs and higher compensation related expenses were limited to Q3.
Net income improved to $1.4B vs $0.7B in the previous quarter for a net income margin of 23.3% vs 11.5%. Adjusted net income improved to $2.2B vs. $1.5B in the previous quarter for an adjusted net margin of 35.9% vs 24.5%
For the full year, total revenues came in at $26.9B, flat year over year. Within full year sales Data center sales were up 41% and gaming sales was down 27% YoY. Gross margins were 56.9% vs 64.9% the prior year while adjusted gross margins were 59.2% vs 66.8% prior. Operating margins were 15.7% vs 37.3% prior while adjusted operating margins were 33.5% vs 47.2% prior.
Regarding Gaming, Nvidia added the following. “The year-on-year decline reflects the impact of channel inventory correction, which is largely behind us.” This is important because it is exposed to the consumer and was facing cyclical headwinds last year that impacted group earnings. Rather than a detractor, it should be a contributor to group earnings going forward. Management provided a Q1 outlook compared to Q4 for all business segments.
“Let me look to the outlook for the first quarter of fiscal '24. We expect sequential growth to be driven by each of our 4 major market platforms led by strong growth in data center and gaming.”“Let me look to the outlook for the first quarter of fiscal '24. We expect sequential growth to be driven by each of our 4 major market platforms led by strong growth in data center and gaming.”
Looking at the balance sheet. Cash, cash equivalents and marketable securities were $13.30B. Inventory increased, primarily to support the ramp of new products in Data Center and Gaming. Meanwhile, free cash flow was $1.74B compared to $2.74B a year ago and negative $156 million a quarter ago. Fiscal-year free cash flow was $3.76B, down from $8B a year ago.
Earnings Call:
The main write-up on Nvidia’s product side will come following GTC at the end of March. However, on the call, Nvidia’s AI-as-a-service was mentioned, so I want to provide that quote for you, as it was one of the most important parts of the earnings call.
I’ve discussed in the past that the H100 is an important leap forward for enterprise AI when stating: “the A100 GPU is what led the company’s gains since Q2 2020 (detailed here) and the Hopper H100 GPU is what will lead the company’s gains for the next two years (detailed here).”
The company has stated the following in regards to H100 sales:
“Adoption of our new flagship H100 center GPU is strong. In just the second quarter of its ramp, H100 revenue was already much higher than that of A100, which declined sequentially.”
I feel like I’ve talked quite a bit about the H100 and its importance, so we won’t rehash that right now.
However, per our July write-up here, there is an important point to what was discussed on the call and what Nvidia investors can expect to hear about in the coming quarters in regards to software monetization. I’m repeating here what we wrote in July before I elaborate on what I think was the most important part of the earnings call:
“According to Nvidia, the H100 delivers 9X more throughput in AI training, and 16X to 30X more inference performance. The company also states in HPC application-specific workloads, the H100 is 7X faster. The goal of the H100 was not only to add more transistors and make the H100 faster, but to also offer function-specific optimizations. This is achieved through the transformer engine.
The architecture aims to answer one of the bigger challenges facing superfast compute, which is that moving data into traditional servers overloads the CPU and system memory and becomes bottlenecked by PCI-Express.
By improving the bandwidth issue, Nvidia’s goal is to create more demand for their DGX Pod and SuperPod Systems, which in turn, will create more demand for their software.”
The comments in the earnings call that pertain to the H100 and DGX Pods and SuperPods is this – it’s important because it can mark the beginning of Nvidia’s software revenue. So, I’m including this as a bigger quote from the earnings report:
“Generative AI's versatility and capability has triggered a sense of urgency at enterprises around the world to develop and deploy AI strategies. Yet, the AI supercomputer infrastructure, model algorithms, data processing and training techniques remain an insurmountable obstacle for most […]
We are partnering with major service — cloud service providers to offer NVIDIA AI cloud services, offered directly by NVIDIA and through our network of go-to-market partners, and hosted within the world's largest clouds. NVIDIA AI as a service offers enterprises easy access to the world's most advanced AI platform, while remaining close to the storage, networking, security and cloud services offered by the world's most advanced clouds […]
AI supercomputers are hard and time-consuming to build. Today, we are announcing the NVIDIA DGX Cloud, the fastest and easiest way to have your own DGX AI supercomputer, just open your browser […]
With our new business model, customers can engage NVIDIA's full scale of AI computing across their private to any public cloud. We will share more details about NVIDIA AI cloud services at our upcoming GTC so be sure to tune in.”
The takeaway is that not only will Nvidia begin to monetize through software on the DGX systems but accessibility will improve through CSPs, or cloud service providers. This is an attempt to democratize AI development while driving software sales.
In the call, management stated the following about CSPs, or cloud service providers:
“With cloud adoption continuing to grow, we are serving an expanding list of fast-growing cloud service providers, including Oracle and GPU specialized CSPs. Revenue growth from CSP customers last year significantly outpaced that of Data Center as a whole as more enterprise customers moved to a cloud-first approach. On a trailing 4-quarter basis, CSP customers drove about 40% of our Data Center revenue.”
This is important as it links back to the comment about Nvidia’s AI as-a-service and cloud service providers helping to move DGX Cloud. It also helps to illustrate how DGX Cloud can be successful, given the strong CSP partnerships and revenue growth in the data center segment.
Here is another quote in regard to DGX Cloud and why it’ll be important for a lower barrier to entry for AI development:
“The accumulation of technology breakthroughs has brought AI to an inflection point. Generative AI's versatility and capability has triggered a sense of urgency at enterprises around the world to develop and deploy AI strategies. Yet, the AI supercomputer infrastructure, model algorithms, data processing and training techniques remain an insurmountable obstacle for most. Today, I want to share with you the next level of our business model to help put AI within reach of every enterprise customer.
Moving along, this was the Q&A piece that is most important to Nvidia investors long-term:
“Timothy Arcuri
Jensen, I had a question about what this all does to your TAM. Most of the focus right now is on text, but obviously, there are companies doing a lot of training on video and music. They're working on models there. And it seems like somebody who's training these big models has maybe, on the high end, at least 10,000 GPUs in the cloud that they've contracted and maybe tens of thousands of more to inference a widely deployed model. So it seems like the incremental TAM is easily in the several hundred thousands of GPUs and easily in the tens of billions of dollars. But I'm kind of wondering what this does to the TAM numbers you gave last year. I think you said $300 billion hardware TAM and $300 billion software TAM. So how do you kind of think about what the new TAM would be?
Jensen Huang
I think those numbers are really good anchor still. The difference is because of the, if you will, incredible capabilities and versatility of generative AI and all of the converging breakthroughs that happened towards the middle and the end of last year, we're probably going to arrive at that TAM sooner than later.”
Today, Nvidia trades at less than 1X that TAM at $515 million compared to what this analyst believes will be an easily-achieved TAM of $600 billion. This would suggest the stock price does not yet fully reflect the future market opportunity.
Conclusion:
There are some upset investors today on social media who shorted Nvidia going into the print. This was based on Nvidia’s current weak financial profile coupled with its valuation. As pointed out in our Q1 webinar, we are entirely focused on the H2 rebound, which can arguably be easier to predict with semiconductors due to the longer-term supply chain visibility this industry has. At least for today, Nvidia proved it’s on track for the H2 rebound.
As you know, we track Nvidia very closely due to its leading allocation in our portfolio. We saw evidence of a gaming bottom in November, which we published about here. We also felt Nvidia had masterfully timed it’s RTX40 Series with the Ada Lovelace architecture plus the H100 release to drop exactly when the crypto mining selloff would be most felt. We discussed this here in September. These points were entirely overlooked by Nvidia critics.
Yes, that revenue miss in the Fall was crazy – but what was lying beneath the surface for chances of a quick recovery?
Most importantly, we discussed Nvidia’s entry into AI software here, which we stated was the important analysis we have ever written on Nvidia. I think “most important analysis” will be rivaled when I write about Nvidia’s automotive segment.
Basically, the devil is in the details and not a lot of investors or analysts care to look into Nvidia’s complex hardware products. Jim Cramer got 1M views on his tweet here that admitted it was tough to listen to this particular company’s earnings calls. It works in our favor that talking heads prefer to discuss consumer tech, and that the masses are collected around those who have not taken the time to get to know his company.
We know Nvidia is not pushing a buzzword to move the stock, as we’ve been covering Nvidia’s AI angle for going on five years. It’s the headlines that changed; not Nvidia.
To remain balanced here, we agree that Nvidia is likely due for a pullback. The shorts were probably right in that regard. That is Knox’s territory. He had written here that $230 has a lot of resistance and also on the forum. He plans to update everyone on Nvidia in his webinar this afternoon.
Your bigger product update will come post-GTC as we begin to lay a strong foundation for 2024 and onward for this exciting company.