Thursday, May 23, 2024

NVIDIA Earnings Call And Transcript Q1 2025 - May 22, 2024 (NVDA)

The stock is up $88.04 (+9.27%) at $1,037.54 on an otherwise blah day at the market.

We'll be going to AlphaStreet's recording and transcript but first some highlights from The Transcript:

And from AlphaStreet:

Corporate Participants:
— Vice President, Investor Relations
— Executive Vice President and Chief Financial Officer
— Founder, President and Chief Executive Officer
 
Analysts:
— Bernstein
— UBS
— Bank of America Securities
— Morgan Stanley
— Goldman Sachs
— TD Cowen
— Evercore ISI
— Jefferies
— Raymond James
— Truist Securities
— Cantor Fitzgerald
 
Operator
Good afternoon. My name is Regina and I will be your conference operator today. At this time, I would like to welcome everyone to NVIDIA's First Quarter Earnings Call. All lines have been placed on mute to prevent any background noise. After the speaker's remarks, there will be a question-and-answer session. [Operator Instructions] Thank you.
Simona Jankowski, you may begin your conference.
 
Simona Jankowski
Thank you. Good afternoon, everyone, and welcome to NVIDIA's conference call for the first quarter of fiscal 2025. With me today from NVIDIA are Jen-Hsun Huang, President and Chief Executive Officer, and Colette Kress, Executive Vice President and Chief Financial Officer.
 
I'd like to remind you that our call is being webcast live on NVIDIA's Investor Relations website. The webcast will be available for replay until the conference call to discuss our financial results for the second quarter of fiscal 2025. The content of today's call is NVIDIA's property. It can't be reproduced or transcribed without our prior written consent.
During this call, we may make forward-looking statements based on current expectations. These are subject to a number of significant risks and uncertainties and our actual results may differ materially. For a discussion of factors that could affect our future financial results and business, please refer to the disclosure in today's earnings release, our most recent Forms 10-K and 10-Q and the reports that we may file on Form 8-K with the Securities and Exchange Commission.
 
All our statements are made as of today, May 22, 2024, based on information currently available to us. Except as required by law, we assume no obligation to update any such statements. During this call, we will discuss non-GAAP financial measures. You can find a reconciliation of these non-GAAP financial measures to GAAP financial measures in our CFO commentary, which is posted on our website.
 
Let me highlight some upcoming events. On Sunday, June 2nd, ahead of the Computex Technology Trade Show in Taiwan, Jensen will deliver a keynote which will be held in-person in Taipei as well as streamed live. And on June 5th, we will present at the Bank of America Technology Conference in San Francisco.
With that let me turn the call over to Colette.
 
Colette Kress
Thanks, Simona. Q1 was another record quarter. Revenue of $26 billion was up 18% sequentially and up 262% year-on-year and well above our outlook of $24 billion. Starting with Data Center. Data Center revenue of $22.6 billion was a record, up 23% sequentially and up 427% year-on-year, driven by continued strong demand for the NVIDIA Hopper GPU computing platform. Compute revenue grew more than five times and networking revenue more than three times from last year. Strong sequential data center growth was driven by all customer types, led by enterprise and consumer internet companies. Large cloud providers continue to drive strong growth as they deploy and ramp NVIDIA AI infrastructure at scale and represented the mid-40s as a percentage of our Data Center revenue.
 
Training and inferencing AI on NVIDIA CUDA is driving meaningful acceleration in cloud rental revenue growth, delivering an immediate and strong return on cloud provider's investment. For every $1 spent on NVIDIA AI infrastructure, cloud providers have an opportunity to earn $5 in GPU instant hosting revenue over four years. NVIDIA's rich software stack and ecosystem and tight integration with cloud providers makes it easy for end customers up and running on NVIDIA GPU instances in the public cloud. For cloud rental customers, NVIDIA GPUs offer the best time to train models, the lowest cost to train models and the lowest cost to inference large language models. For public cloud providers, NVIDIA brings customers to their cloud, driving revenue growth and returns on their infrastructure investments.
 
Leading LLM companies such as OpenAI, Adept, Anthropic, Character.AI, Cohere, Databricks, DeepMind, Meta, Mistral, xAI, and many others are building on NVIDIA AI in the cloud. Enterprises drove strong sequential growth in Data Center this quarter. We supported Tesla's expansion of their training AI cluster to 35,000 H100 GPUs. Their use of NVIDIA AI infrastructure paved the way for the breakthrough performance of FSD Version 12, their latest autonomous driving software based on Vision. Video Transformers, while consuming significantly more computing, are enabling dramatically better autonomous driving capabilities and propelling significant growth for NVIDIA AI infrastructure across the automotive industry. We expect automotive to be our largest enterprise vertical within Data Center this year, driving a multibillion revenue opportunity across on-prem and cloud consumption.
 
Consumer Internet companies are also a strong growth vertical. A big highlight this quarter was Meta's announcement of Llama 3, their latest large language model, which was trained on a cluster of 24,000 H100 GPUs. Llama 3 powers Meta AI, a new AI assistant available on Facebook, Instagram, WhatsApp and Messenger. Llama 3 is openly available and has kickstarted a wave of AI development across industries. As generative AI makes its way into more consumer Internet applications, we expect to see continued growth opportunities as inference scales both with model complexity as well as with the number of users and number of queries per user, driving much more demand for AI compute. In our trailing four quarters, we estimate that inference drove about 40% of our Data Center revenue. Both training and inference are growing significantly. Large clusters like the ones built by Meta and Tesla are examples of the essential infrastructure for AI production, what we refer to as AI factories.
 
These next-generation data centers host advanced full-stack accelerated computing platforms where the data comes in and intelligence comes out. In Q1, we worked with over 100 customers building AI factories ranging in size from hundreds to tens of thousands of GPUs, with some reaching 100,000 GPUs. From a geographic perspective, Data Center revenue continues to diversify as countries around the world invest in Sovereign AI. Sovereign AI refers to a nation's capabilities to produce artificial intelligence using its own infrastructure, data, workforce and business networks. Nations are building up domestic computing capacity through various models. Some are procuring and operating Sovereign AI clouds in collaboration with state-owned telecommunication providers or utilities. Others are sponsoring local cloud partners to provide a shared AI computing platform for public and private sector use.
 
For example, Japan plans to invest more than $740 million in key digital infrastructure providers, including KDDI, Sakura Internet, and SoftBank to build out the nation's Sovereign AI infrastructure. France-based, Scaleway, a subsidiary of the Iliad Group, is building Europe's most powerful cloud native AI supercomputer. In Italy, Swisscom Group will build the nation's first and most powerful NVIDIA DGX-powered supercomputer to develop the first LLM natively trained in the Italian language. And in Singapore, the National Supercomputer Center is getting upgraded with NVIDIA Hopper GPUs, while Singtel is building NVIDIA's accelerated AI factories across Southeast Asia.
 
NVIDIA's ability to offer end-to-end compute to networking technologies, full-stack software, AI expertise, and rich ecosystem of partners and customers allows Sovereign AI and regional cloud providers to jumpstart their country's AI ambitions. From nothing the previous year, we believe Sovereign AI revenue can approach the high single-digit billions this year. The importance of AI has caught the attention of every nation. We ramped new products designed specifically for China that don't require an export control license. Our Data Center revenue in China is down significantly from the level prior to the imposition of the new export control restrictions in October. We expect the market in China to remain very competitive going forward.
 
From a product perspective, the vast majority of compute revenue was driven by our Hopper GPU architecture. Demand for Hopper during the quarter continues to increase. Thanks to CUDA algorithm innovations, we've been able to accelerate LLM inference on H100 by up to three times, which can translate to a three times cost reduction for serving popular models like Llama 3. We started sampling the H200 in Q1 and are currently in production with shipments on track for Q2. The first H200 system was delivered by Jensen to Sam Altman and the team at OpenAI and powered their amazing GPT-4o demos last week. H200 nearly doubles the inference performance of H100, delivering significant value for production deployments.
 
For example, using Llama 3 with 700 billion parameters, a single NVIDIA HGX H200 server can deliver 24,000 tokens per second, supporting more than 2,400 users at the same time. That means for every $1 spent on NVIDIA HGX H200 servers at current prices per token, an API provider serving Llama 3 tokens can generate $7 in revenue over four years. With ongoing software optimizations, we continue to improve the performance of NVIDIA AI infrastructure for serving AI models. While supply for H100 prove, we are still constrained on H200. At the same time, Blackwell is in full production. We are working to bring up our system and cloud partners for global availability later this year.

Demand for H200 and Blackwell is well ahead of supply and we expect demand may exceed supply well into next year. Grace Hopper Superchip is shipping in volume. Last week at the International Supercomputing Conference, we announced that nine new supercomputers worldwide are using Grace Hopper for a combined 200 exaflops of energy-efficient AI processing power delivered this year. These include the Alps Supercomputer at the Swiss National Supercomputing Center, the fastest AI supercomputer in Europe. Isambard-AI at the University of Bristol in the UK and JUPITER in the Julich Supercomputing Center in Germany.....

....MUCH MORE, including conference call playback

One out-the-door note, Nvidia has basically created a brand-new multi-billion dollar business:

We were struck by the possibilities of the SovereignAI plan and have a few posts on same.

First up December 19, 2023

Nvidia CEO Jensen Huang Says AI to See ‘Major Second Wave (NVDA)

AI to See ‘Major Second Wave,’ NVIDIA CEO Says in Fireside Chat With iliad Group Exec
NVIDIA’s Jensen Huang says sovereign AI a growing need for countries to reflect unique cultural, linguistic, industrial characteristics
European startups will get a massive boost from a new generation of AI infrastructure, NVIDIA founder and CEO Jensen Huang said Friday in a fireside chat with iliad Group Deputy CEO Aude Durand — and it’s coming just in time.

February 2, 2024
"Nvidia chief sees rise of ‘sovereign AI’ infrastructure across nations, driving demand for company’s advanced chips"

March 5, 2024
Here's Nvidia's "Sovereign AI" Pitch (NVDA)

.... This is terrible. I now have Jensen Huang speaking in Dr. Martin Luther King's cadences as he repurposes the penultimate paragraph of "I have a Dream":

Let AI ring from Stone Mountain of Georgia.
Let AI ring from Lookout Mountain of Tennessee.
Let AI ring from every hill and molehill of Mississippi.
From every mountainside, let AI ring. 

I may have to go lie down.
 
...Every, town, every village, every hamlet, every wide spot in the road, should have their own (NVDA-powered) supercomputer.
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