Advanced Micro Devices is positioning itself as an emerging competitor to the industry leader in the AI market.
The Nvidia situation
Nvidia designs semiconductors for use in AI, gaming, autonomous vehicles, robotics, 5G networks and data centers. While chip sales drive its revenue, the company also offers a full platform of related products that developers use to build, deploy, run and scale enterprise applications on the hardware.
The company established itself in the late 1990s by creating the graphics processing unit (GPU) , used primarily in video games. In 2013, Nvidia CEO Jensen Huang saw a bigger picture for his company. He envisioned artificial intelligence as the future of computing and believed he could lead that future. The company began working on programmable GPUs to support complex computational operations.
Today, Nvidia is the recognized leader in AI infrastructure , selling far more AI chips than any other competitor. The company also boasts a customer roster that includes the world’s leading technology companies.
Where AMD is now
Historically, AMD has competed with Intel for market share in central processing units (CPUs). Its competitor remains dominant, but AMD has been a formidable competitor, at least since its CEO, Lisa Su, led the launch of the high-performance Zen architecture in 2017. Five years later, Advanced Micro Devices’ market capitalization surpassed that of its rival for the first time.
AMD is now targeting the AI market, and Su has taken key steps to compete with Nvidia. He quadrupled the company’s R&D budget and acquired Xilinx, which makes programmable processors, Nod.ai, which develops open-source AI software, and ZT Systems, which designs and manufactures servers and related infrastructure for data centers.
While AMD is not yet significantly competing with Nvidia, it is positioned to capture double-digit market share in AI chips , which could represent a huge opportunity in the future.
Comparing AI Strategies
Nvidia and AMD won’t necessarily compete directly for AI-related revenue. Let’s look at their market strategies to understand why.
Nvidia’s AI strategy
Nvidia’s initial strategy in AI was to be first and best , and the company capitalized on this strategy. Huang’s strategic vision, combined with a proven product development process, provides some protection against other competitors.
Nvidia doesn’t just make AI chips — it maintains an entire platform around those chips , including software and optimized libraries to support application development from start to finish. This platform approach is another competitive advantage that could make it harder for customers to switch to another vendor.
AMD’s AI strategy
AMD has been following Intel for years, and is likely using similar tactics to gain AI market share from Nvidia. Offering better value is at the core of its strategy, which could mean providing similar performance at a lower price or slightly lower performance at a much lower cost.
While offering a comprehensive AI computing platform was a secondary focus for AMD, it has taken steps to expand its offering. The recent acquisition of ZT Systems, for example, allows AMD to offer a full suite of compute and storage resources needed to power AI data centers.
Financial performance
Nvidia ’s trailing-12-month revenue totals about $96 billion, nearly four times AMD’s $23 billion . The earnings comparison isn’t that stark, with Huang’s company posting diluted EPS of $2.13 versus Advanced Micro Devices’ $0.84.
Both companies report AI-related revenue within their data center divisions . In the most recent fiscal quarter, Nvidia’s data center revenue was $26.3 billion, up 154% from a year ago. AMD generated data center revenue of $2.8 billion, up 115% year over year.
Valuation and investment potential
Nvidia is a much larger company, with a market capitalization of $2.89 trillion , making it the third-largest public company in the world, ahead of Alphabet and Amazon . The tech company’s valuation metrics, particularly its price-to-book ratio, are also much higher than AMD’s. However, the latter’s growth potential based on analysts’ targets is comparable.
Market share and competitive position
Nvidia has a dominant market position and a reputation as the leader in AI chips. AMD is working to establish itself as a strong second choice.
Fortunately for AMD, the AI chip market is predicted to be large enough to be lucrative for two companies . It predicts that global spending on AI accelerators will reach $400 billion by 2027. If AMD manages to capture 20% to 30% of that market, its data center division’s revenue could increase sevenfold.
Tech companies investing in AI infrastructure are also likely to want more than one vendor and more than one software platform. AMD’s development software, ROCm, is an open-source solution, while Nvidia’s CUDA is proprietary and has a strong reputation, but some projects might require the flexibility of the Su Lisa-led company’s open-source solution.
Product offerings and technological leadership
Nvidia’s AI offering includes:
- Specialized architectures Blackwell, Hopper and Ada Lovelace.
- High-performance HGX H200 GPUs and the upcoming Blackwell B200 GPU for data centers.
- GeForce RTX GPUs for AI-powered PCs.
- Thor SoCs for autonomous cars.
- Specialized software frameworks CUDA, the TensorRT deep learning library, Jarvis for chatbot AI, Omniverse for 3D simulation, and Merlin for recommender systems.
AMD’s AI product line includes:
- AMD XDNA 2, AMD CDNA, and AMD RDNA specialized architectures.
- Instinct MI300A accelerators and MI300X GPUs designed for high-performance workloads.
- Ryzen 7040 Series Processors for AI-Powered PCs.
- Versal Adaptive SoCs.
- ROCm and Vitis AI software tools.
Growth opportunities
Several research firms and AMD’s CEO are predicting strong double-digit annual growth in AI infrastructure spending over the next few years . However, the growth opportunity is somewhat different for our two companies. In short, Nvidia will be playing defense, while its competitor will be playing offense.
Nvidia’s growth opportunities
With a head start in the AI space, Nvidia now holds roughly 80% of the market share . The rapid rise to the top led to extreme growth in revenue and profits as tech companies rushed to build out their AI capabilities. Unfortunately for the company, spending could moderate just as competitors enter the market with viable alternatives.
However, the company can find growth by doing what it does best: pushing the boundaries of what high-performance computing can do in terms of speed and efficiency . Improving its platform to bring AI computing to a broader market could be another source of growth.
The company won’t be complacent under Huang. Nvidia recently shortened its product refresh cycle from two years to one, presumably to keep pace with AMD.
AMD Growth Opportunities
AMD has more to gain and less to lose than Nvidia, which is a more interesting position to be in.
AMD’s chips are currently cheaper and have about 80% of the power of Nvidia’s , according to AI software firm MosaicML. After testing AMD’s MI250s alongside Nvidia’s A100s last year, MosaicML CTO Hanlin Tang believes the Su Lisa-led company can close the performance gap. That will be the path for the company to achieve solid market share and revenue growth, especially if it remains competitive on price and can produce enough to meet demand.
Challenges and risks
Both companies will need to manage supply constraints, regulations limiting revenue opportunities in China, and increasing competition. But they also face specific challenges related to their position in the AI growth trajectory.
Nvidia’s challenges and risks
Nvidia’s biggest challenge will be defending its position. The sheer size of the market ensures fierce competition as GPU makers position themselves to take advantage of AI spending.
To avoid losing market share, the tech company will need to innovate and execute product launches flawlessly . Continued improvements in speed and efficiency will support increased spending, even as the initial buildout of AI infrastructure slows.
Absent impressive improvements to its products, the company could face share losses , which would be a drag on revenue — something that likely won’t please Nvidia investors.
AMD Challenges and Risks
AMD’s main challenge is to establish itself as the best second choice in AI, while integrating the four acquisitions it made in the past two years. These acquisitions should improve its competitive position , but they won’t be enough to dethrone Nvidia’s dominance.
The big risk for AMD , therefore, is that it will miss its target and end up competing for third or fourth place in the industry. Supply constraints or strategic, product or execution mistakes could open the door for another player, such as Intel, to gain market share.
Analysts’ opinions and market sentiment
Analysts are bullish on Nvidia and AMD stocks. Both companies have an average rating of Strong Buy. Of the 40 analysts covering the Huang-led company, 20 recommend a Strong Buy, 17 a Buy, and three a Hold. None suggest selling NVDA’s positions . Of the 30 ratings for its main competitor, 15 are Strong Buy, 11 a Buy, and four a Hold. As with NVDA, analysts see no reason to sell AMD at the moment.
To gauge market sentiment, we can look at the price trends of NVDA and AMD compared to the broader market. NVDA outperformed AMD and the S&P 500 by a wide margin over the past six months and rose nearly 30%, while the index rose 10% and its competitor’s stock fell 14%.
The past month’s performance, however, shows Nvidia as the loser . The company lost 10%, while AMD and the S&P 500 posted small gains. This is partly a consequence of the company’s high valuation, which makes it more reactive to economic news.
What is the best AI stock to buy right now?
AMD is the best AI stock in terms of value and growth potential . Yes, the company is an “underdog” that probably won’t replace Nvidia as the recognized leader in AI. But it operated from the second spot before and thrived under its current leader, Su Lisa. Plus, the addressable market is so large that a lower market share position still means massive growth for AMD.
Nvidia already has an impressive track record of growth under its belt, but the company is quickly catching up to the big AI-related gains it has generated to date. Comparisons will become more difficult going forward, which could create further volatility in NVDA’s stock price.
