🤖 NVIDIA: In a League of its Own
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🤖 NVIDIA: In a League of its Own
It's Jensen Huang's world and competitors don't want to live there
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“A new computing era has begun.“
NVIDIA (NVDA) delivered another banger with its Q2 FY24 earnings (ending in July 2023). CEO Jensen Huang ended the earnings call with a strong message for the market:
“The industry is simultaneously going through two platform transitions, accelerated computing and generative AI. Data centers are making a platform shift from general purpose to accelerated computing. The $1 trillion of global data centers will transition to accelerated computing to achieve an order of magnitude better performance, energy efficiency and cost.”
So, let’s unpack how these transitions impact NVIDIA’s performance and guidance. We’ll also take a look at where that leaves us as investors.
Today at a glance:
NVIDIA’s Q2 FY24.
Recent partnerships.
Key quotes from the call.
What to watch looking forward.
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1. NVIDIA Q2 FY24
Income statement:
Here is the bird’s-eye view of the income statement.
I’m focusing on sequential growth (quarter-over-quarter), a better representation of the current growth dynamic.
Revenue jumped +88% Q/Q to $13.5 billion (vs. $11 billion guidance).
⚙️ Data Center grew +141% Q/Q to $10.3 billion (+171% Y/Y).
🎮 Gaming grew +11% Q/Q to $2.5 billion (+22% Y/Y).
👁️ Professional Visualization grew +28% Q/Q to $0.4 billion (-24% Y/Y).
🚘 Automotive declined by 15% Q/Q to $0.3 billion (+15% Y/Y).
🏭 OEM & Other declined by 14% Q/Q to $0.1 billion (-53% Y/Y).
The graph below shows the past eleven quarters, which paint a challenging time in FY23 caused by the decline in the Gaming segment, followed by the stunning rise in Data Center revenue in the past two quarters.
Gross margin was 70% (+5pp Q/Q), a 1 percentage point beat.
Operating margin was 50% (+21pp Q/Q).
Non-GAAP operating margin was 58% (+15pp Q/Q).
Non-GAAP EPS $2.70 ($0.61 beat).
Cash flow:
Operating cash flow was $6.3 billion (47% margin, +29pp Y/Y).
Free cash flow was $6.0 billion (45% margin, +8pp Y/Y).
Balance sheet:
Cash and cash equivalent: $16.0 billion.
Debt: $9.7 billion.
Q3 FY24 Guidance:
Revenue to grow +18% Q/Q (+170% Y/Y) to $16.0 billion ($3.6 billion beat).
Gross margin 71.5% (+1.4pp Q/Q).
So what to make of all this?
NVIDIA delivered an exceptional revenue beat of 23%. If you recall, the revenue beat was 10% in Q1. But the $11 billion revenue guidance for Q2 shocked the world, $3.8 billion ahead of expectation. Well, NVIDIA beat that raised guidance by another $2.5 billion. The reasons behind this beat are similar to last quarter. But it’s the scale of the beat that is fascinating.
⚙️ Data Center comprised 76% of overall revenue (+16pp Q/Q). It demonstrated exceptional growth sequentially, once again led by strong demand from cloud service providers and large consumer internet companies for GPU platforms related to a surge in demand for generative AI and large language models (LLMs) — more on this in a minute.
🎮 Gaming continued to bounce back after a post-COVID slump. The channel inventory levels continued to normalize. The rebound was driven by GeForce RTX 40 Series GPUs (based on the Ada Lovelace architecture).
👁️ Professional Visualization also faced channel inventory challenges in recent quarters but continued to rebound sharply, driven by higher demand for workstation GPUs, combined with the ramp of NVIDIA RTX products.
🚘 Automotive was down 15% sequentially, reflecting lower overall auto demand, particularly in China.
Margins improved across the board, boosted by the rise in Data Center revenue. Following inventory improvements, the gross margin was one percentage point ahead of guidance. Inventory provisions from prior periods lowered the cost of revenue, boosting gross margin in the process. That’s a non-recurring boost.
The Q3 FY24 revenue guidance of $16.0 billion was another astounding beat, exceeding Wall Street's expectations of $12.4 billion. It wasn’t as massive as the $3.9 billion beat from the prior quarter, but it was close. And if history is any indication, they will beat this guidance handsomely.
Management expects profitability to increase from here. The Q2 FY24 outlook includes a 71.5% GAAP gross margin (+1pp) and a 53% operating margin (+3pp Q/Q).
Now, let’s look at some recent business highlights.
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2. Recent partnerships
☁️ Google Cloud
Google Cloud and NVIDIA just announced a deeper collaboration to advance AI computing at Google:
Accelerating AI Development: Google's LLM-building framework, PaxML, is now optimized for NVIDIA's H100 and A100 Tensor Core GPUs. This adjustment allows for advanced, scalable experimentation.
NVIDIA Innovations on Google Cloud: A series of strategic implementations were announced:
Google Cloud's A3 VMs, powered by NVIDIA H100 GPUs, will be available next month, boasting 3x faster training and enhanced networking.
NVIDIA H100 GPUs will soon fuel Google Cloud’s Vertex AI platform.
Google Cloud will gain early access to NVIDIA's DGX GH200 AI supercomputer (the next generation), exploring its capabilities for generative AI tasks.
NVIDIA DGX Cloud will soon be accessible from web browsers, providing scalability for advanced AI training.
NVIDIA AI Enterprise, a suite for diverse AI tasks, will be available on the Google Cloud Marketplace.
This reinforced partnership shows that Google needs NVIDIA chips not just for GCP customers but for its own internal models.
❄️ Snowflake
During Snowflake Summit 2023, Snowflake and NVIDIA unveiled their collaboration to enhance generative AI capabilities within the Snowflake Data Cloud.
NVIDIA NeMo integration: Allows businesses to create custom LLMs for AI services like chatbots and search, all within Snowflake Data Cloud.
Data security: Proprietary data remains safeguarded and governed within Snowflake while developing LLMs.
Enterprise potential: Enterprises can leverage their vast data to develop business-specific LLMs.
Industry application: The partnership aims to transform various sectors, introducing AI-driven solutions for healthcare, finance, and more.
🤗 Hugging Face
NVIDIA announced a collaboration with Hugging Face, an open-source machine learning platform, to bring generative AI supercomputing capabilities to millions of developers. Their goal is to streamline the building of LLMs and other advanced AI apps.
Here are the key points:
The integration will leverage NVIDIA's DGX Cloud within the Hugging Face platform. This promises faster training and fine-tuning of AI models.
A significant outcome of this partnership will be the introduction of Training Cluster as a Service. This service simplifies the creation of custom generative AI models for businesses.
The collaboration focuses on industry-specific applications, including intelligent chatbots, search, and summarization.
The aim is to make AI computing accessible to the vast Hugging Face community (over 15,000 organizations) with just a click.
Hugging Face just raised $235 million from NVIDIA, Salesforce, Amazon, Google, AMD, and others at a $4.5 billion valuation.
💻 VMWare
VMware and NVIDIA just announced a partnership for Advanced Generative AI.
The VMware Private AI Foundation with NVIDIA will allow businesses to craft models and execute generative AI operations like chatbots, assistants, and search. This platform will be seamlessly integrated, featuring NVIDIA's AI software and accelerated computing, all built atop the VMware Cloud Foundation tailored for AI applications.
New NVIDIA hardware offerings, such as the L40S GPU and BlueField-3 DPUs, will supercharge generative AI tasks, from customization to inference. Colette Kress highlighted that L40S’s focus is to fine-tune pre-trained models.
Businesses will have a variety of platforms to build and run models, from NVIDIA NeMo to Llama 2. Major tech giants like Dell Technologies, Hewlett Packard Enterprise, and Lenovo are backing the partnership.
Overall, these new partnerships illustrate that NVIDIA is moving fast and making sure it serves its large install base with new features and solutions. Let’s turn to key quotes from the call.
3. Key quotes from the earnings call
CFO Colette Kress:
On Data Center:
“Our cloud service providers drove exceptional strong demand for HGX systems in the quarter, as they undertake a generational transition to upgrade their data center infrastructure for the new era of accelerated computing and AI.”
She provided updates on the three major customer categories:
☁️ Cloud service providers (CSPs): They contributed over 50% of Data Center revenue. All hyperscalers (Amazon, Microsoft, Google) are NVIDIA customers with strong demand for the flagship H100 data center GPUs.
💬 Consumer Internet companies: They were the second largest category. For example, Meta powers its Grand Teton AI supercomputer with H100 chips. AI helps increase time spent on Instagram and ad performance.
🗄️ Enterprise: Demand for AI and accelerated computing touches all sectors, from automotive to financials to healthcare. Everyone is getting an LLM. They get access to NVIDIA’s acceleration libraries, pre-trained models, and APIs.
All three customer categories are driving the surge in demand for generative AI.
On export restrictions to China:
“We do not anticipate that additional export restrictions on our Data Center GPUs, if adopted, would have an immediate material impact to our financial results.
However, over the long term, restrictions prohibiting the sale of our Data Center GPUs to China, if implemented, will result in a permanent loss and opportunity for the U.S. industry to compete and lead in one of the world's largest markets.”
On the opportunity with AI assistants:
“AI Copilot and assistants are set to create new multi-hundred billion dollar market opportunities for our customers.”
From coding to personal to voice and writing assistants, this market clearly showed promising signs in 2023, and all CSPs are involved
On the next generation GH200 Grace Hopper Superchip (combining ARM-based Grace CPU with Hopper GPU):
“(It) entered full production and will be available this quarter in OEM servers. […] The second generation version of our Grace Hopper Superchip with the latest HBM3e memory will be available in Q2 of calendar 2024.”
Notably, NVIDIA announced the DGX 200, a new class of large memory AI supercomputer for giant LLMs. It enables 256 Grace Hopper Superchips to work together as one (as opposed to just eight GPUs previously).
On guidance:
“Our demand visibility extends into next year. Our supply over the next several quarters will continue to ramp as we lower cycle times and work with our supply partners to add capacity. Additionally, the new L40S GPU will help address the growing demand for many types of workloads from cloud to enterprise.”
This visibility must have been a factor in the new share repurchase program (more on that in a minute).
On Gaming:
“We believe global end demand has returned to growth after last year's slowdown. We have a large upgrade opportunity ahead of us. Just 47% of our installed base have upgraded to RTX and about 20% of the GPU with an RTX 3060 or higher performance.”
Gaming suffered after a pandemic-induced glut and a crypto slump following Ethereum’s upgrade to proof-of-stake. Now, the company is benefiting from a strong performance from NVIDIA's GPU-powered laptops.
CEO Jensen Huang:
On NVIDIA’s main differentiation (4 main characteristics):
“I would say number one is architecture. The flexibility, the versatility and the performance of our architecture […] From data processing to training to inference, for preprocessing of the data before you do the inference to the post processing of the data, tokenizing of languages so that you could then train with it. […]
The second characteristic of our company is the installed base. […] Software developers seek a large installed base so that they can reach the largest number of end users, so that they could build a business or get a return on the investments that they make.
And then the third characteristic is reach. […] We're in the cloud, we're in enterprise. […]
And then lastly, because of our scale and velocity. ”
Huang highlighted that these four characteristics make it compelling for companies to build their business on top of NVIDIA’s ecosystem. And it empowers NVIDIA to introduce new products and new architecture at a faster clip.
On networking:
“For the customers that are building very large infrastructure, InfiniBand is, I hate to say it, kind of a no-brainer. And the reason for that because the efficiency of InfiniBand is so significant, some 10%, 15%, 20% higher throughput for $1 billion infrastructure translates to enormous savings. Basically, the networking is free.”
On demand visibility:
“We have excellent visibility through the year and into next year. And we're already planning the next-generation infrastructure with the leading CSPs and data center builders.”
Huang believes that general-purpose computing at scale is now too expensive and slow. So, the current workload going through CPUs could eventually entirely transition to GPUs. If his vision proves to be correct, it may be only the beginning of a multi-year cycle that could turn NVIDIA into the largest company in the world.
“The world has something along the lines of about $1 trillion worth of data centers installed, in the cloud, in enterprise and otherwise. And that $1 trillion of data centers is in the process of transitioning into accelerated computing and generative AI. […] It's about $1 trillion worth of data centers, call it, $0.25 trillion of capital spend each year.”
It remains to be seen what portion of general-purpose computing will transition to GPUs or on what time horizon this transition could occur.
4. What to watch looking forward
Polarizing Buybacks
NVIDIA abstained from stock buybacks last quarter despite $7 billion left in its share repurchase program. This changed in Q2 with a $3 billion repurchase.
Management initiated a new $25 billion repurchase program, hinting at more buybacks in FY24.
For context, management bought back $10 billion of NVDA shares in FY23, so we are on track for a similar pace in FY24. Time will tell if it’s the best use of the current influx of cash. But with clear demand visibility, management is sending a message to Wall Street that the stock is attractive enough.
Valuation update
NVIDIA's stock valuation remains controversial. While some perceived it as overvalued, many big money managers doubled down on NVDA in Q2. Notably, renowned investor Stanley Druckenmiller made it his fund's largest position. We discussed the details here. 👇
If NVIDIA continues to outperform analysts’ expectations, it will continue to rise. If not, the stock could be cut in half (or worse). Simple, right?
To be sure, putting NVIDIA in a DCF model is not helpful and probably ill-advised. Who would have modeled a sequential revenue growth of 171% for Data Center?NVIDIA has outperformed Wall Street's EPS predictions by 19% and 31% in the last two quarters.
Nvidia's current forward PE ratio has dropped to around 33, according to data from Refinitiv, its lowest forward earnings multiple since December 2022. That compared to over 46 before the earnings report. What a difference an earnings report makes.
For context, that’s barely more than Apple or Microsoft, trading at 30 times forward earnings. Of course, we are comparing apples to oranges here, and the sustainability of NVIDIA’s demand is still unclear. A lot of future demand is already factored in NVIDIA’s updated forward EPS, but this isn’t Cisco at the peak of the dot-com bubble.
Risks and challenges
The risks and challenges are well-known:
NVIDIA’s solutions could become increasingly commoditized, with Google, Amazon, and Meta investing in their own AI chips and software for training and inference. Other chip makers like AMD and Intel are expected to make some moves.
The hype around generative AI could wane, as illustrated by the recent decline in traffic to OpenAI’s ChatGPT based on Similarweb data.
The demand for NVIDIA’s GPUs could decline once the CSPs are sufficiently equipped for training.
There is no way to know what the future holds. That’s why investing is so hard!
As always, the key here is to continually reassess our assumptions as the story unfolds. Whatever you thought about the prospects of NVIDIA two quarters ago, the fundamentals have evolved dramatically.
As the saying goes:
“When the facts change, I change my mind. What do you do, sir?”
Whether you are an NVIDIA shareholder or observing from the sidelines, there is a lot to celebrate with the shift to accelerated computing and generative AI.
I can’t wait to see the applications that come to life in this new computing era.
In observance of Labor Day, our Premium issue will be taking a short break this Tuesday, September 5th. We'll be back with fresh insights in next Friday’s edition.
That’s it for today!
Stay healthy and invest on!
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Disclosure: I am long NVDA, AMD, AMZN, CRM, and GOOG in the App Economy Portfolio. I share my ratings (BUY, SELL, or HOLD) with App Economy Portfolio members here.
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Author's Note (Bertrand here 👋🏼): The views and opinions expressed in this newsletter are solely my own and should not be considered financial advice or any other organization's views.
🤖 NVIDIA: In a League of its Own
Remember times when nvidia was only about gaming gpus?