NVIDIA's market capitalization breaks 5 trillion! From gaming graphics cards to AI arms dealer, three transformations.

On October 30, NVIDIA's market value surpassed $5 trillion, exceeding the annual GDP totals of developed countries such as Japan and Germany. From its IPO price of $12 in 1999, taking into account stock splits, NVIDIA has generated an 8000-fold return over 26 years. With its GPU and CUDA-based general computing power, NVIDIA has successfully navigated multiple technology cycles, including gaming, cryptocurrency mining, and AI.

GPU Builders Started from Gaming Graphics Cards

The birth of the graphics card (GPU) dates back to the 1990s. At that time, some people in Silicon Valley proposed an idea: by using specialized chips such as sound cards for processing audio and network cards for handling networking, the workload of the central processing unit (CPU) could be alleviated. Similarly, it was only logical to manufacture a chip dedicated to computer graphics output, which is the graphics card (Graphic Card).

However, at that time, there were many options for the technology path of graphics cards. The breakthrough that NVIDIA found was to achieve 3D graphics acceleration through parallel computing, especially applied in the gaming field. Parallel computing refers to breaking down a complex task into multiple smaller tasks and processing them simultaneously to improve computational efficiency. In 1999, NVIDIA launched a graphics card named GeForce. This graphics card was designed for gaming, focusing on “parallel computing,” which significantly enhances 3D graphics processing capabilities, thereby providing a smoother and more realistic gaming experience.

The success of GeForce propelled NVIDIA to rise rapidly and become a leader in the graphics card field. At that time, it was not only NVIDIA that was researching graphics processing units, but NVIDIA successfully tied itself deeply to the label of “GPU inventor.” NVIDIA's then marketing head, Dan Vivoli, used the concept of “graphics processing unit” (GPU) to promote their chips. He believed that as long as NVIDIA repeatedly emphasized that it was the inventor of the GPU, it could become the industry leader. Indeed, this turned out to be true, and NVIDIA became synonymous with GPU.

The Silent Big Winner of the Crypto Bull Market

NVIDIA's market value increased from 14 billion USD in 2016 to a peak of 175 billion USD in 2018, with more than a tenfold increase in two years closely linked to the cryptocurrency mining craze. In 2017, cryptocurrency entered a bull market, attracting a large number of miners competing for GPUs, turning GPUs into money printers. Global graphics card sales surged, and prices soared. Taking the NVIDIA GTX 1060 model used by miners as an example, the purchase price before May 2017 was about 1650 CNY per unit, and by June 2017, it had risen to around 2900 CNY.

NVIDIA has become the big winner behind the cryptocurrency bull market, reaping a fortune. Benefiting from the crypto mining boom, NVIDIA's total revenue for the 2018 fiscal year reached a new high of $9.7 billion. Jen-Hsun Huang stated, “Our GPUs support the world's largest scale of distributed supercomputing, which is why they are so popular in the cryptocurrency field.” In addition, NVIDIA has also launched mining-specific cards like the GTX 1060 3GB and the P106 and P104 professional mining cards.

In 2020, after a 2-year bear market, the crypto market set sail again, with Bitcoin rising more than 2 times and Ethereum rising 4 times. Nvidia once again became a beneficiary of the “crypto boom.” Nvidia acted quickly and actively participated in the mining market, launching the CMP series of professional mining cards that removed graphics processing capabilities, featuring lower core peak voltage and frequency to improve mining performance and efficiency.

NVIDIA's Performance in Two Rounds of the Crypto Bull Market

2017-2018 Bull Market: Market capitalization soared from 14 billion to 175 billion USD, and the price of GTX 1060 rose from 1650 to 2900.

2020-2021 Bull Market: Launched CMP professional mining cards, RTX3060 surged from 2499 to 5499, RTX3090 soared from 11999 to 20000.

Crypto Chip Revenue: Reached $155 million in Q1 2021, accounting for one-quarter of total sales.

After the release of the financial report for the first quarter of 2021, Nvidia's Chief Financial Officer Colette Kress revealed that Nvidia's sales of cryptocurrency chips reached as high as $155 million, with graphics cards used for “mining” accounting for a quarter of total sales in the first quarter. In 2021, Nvidia's annual revenue set a record of $26.91 billion, an increase of 61% compared to the previous fiscal year, and its market value once exceeded $800 billion.

However, the good times did not last long. In September 2022, Ethereum transitioned from PoW (Proof of Work) to PoS (Proof of Stake), marking the gradual end of the GPU mining era. In the third quarter of 2022, Nvidia experienced declines in both revenue and net profit, with quarterly revenue only reaching $5.931 billion, a year-on-year decrease of 17%, and net profit only at $680 million, a staggering year-on-year decline of 72%. At that time, both overseas media such as the Financial Times and domestic tech media were pessimistic about Nvidia. Just when it seemed dire, an unexpected turn of events occurred as AI and large language models gained momentum.

CUDA has honed its skills for ten years to achieve AI dominance

NVIDIA's dominance in the AI industry began with earlier accumulations. NVIDIA's former chief scientist David Kirk had long envisioned generalizing the 3D graphics rendering power of GPUs, not limited to the gaming field. Under the leadership of David Kirk and Jen-Hsun Huang, NVIDIA launched the revolutionary GPU unified computing platform CUDA in 2007, unleashing massive computational resources.

But at that time, CUDA did not impress investors at all. Instead, due to the huge investment in creating a “super computing” system that was ahead of its time, NVIDIA's profits were significantly reduced, and Wall Street responded with boos. Ben Gilbert, the host of the popular podcast “Acquired” that was all the rage in Silicon Valley, commented on this: “They weren't targeting a large market at that time, but a niche corner of academia and scientific computing, and they spent billions of dollars on it.”

The voices from the outside did not affect Jen-Hsun Huang. His persistence in investing in CUDA for over a decade has brought NVIDIA to its current status. To solve the “which came first, the chicken or the egg” problem, NVIDIA leveraged their existing large user base of gamers with GForce gaming graphics cards. However, the additional costs of CUDA are very high, which has led to a significant decline in NVIDIA's profits over the years, and their market value has fluctuated around the 1 billion dollar level.

Jen-Hsun Huang founded a conference named GTC, tirelessly promoting CUDA worldwide. Eventually, a plethora of applications emerged, including CT reconstruction, molecular dynamics, particle physics, fluid dynamics, and image processing. It wasn't until 2012 that AI researchers recognized the potential of CUDA. The renowned AI expert Alex Krizhevsky trained AlexNet on the GForce GTX 580, triggering an explosion in artificial intelligence.

In March 2016, AlphaGo defeated Lee Sedol, shocking the world. A month later, Jen-Hsun Huang officially announced at the GTC China conference that NVIDIA was no longer just a semiconductor company, but a company focused on artificial intelligence computing. In August 2016, Jen-Hsun Huang personally delivered NVIDIA's first AI supercomputer, the DGX-1, to OpenAI's office, where then-chairman Elon Musk opened the package with a box cutter. Jen-Hsun Huang left a message: “For the future of computing and humanity, I donate the world's first DGX-1.”

Later, OpenAI trained the globally popular ChatGPT using NVIDIA's supercomputers, and the subsequent hardware product DGX H100 from NVIDIA was in high demand in the market, with supply unable to meet the demand. Jen-Hsun Huang views computing power as core. Whether it is AI, autonomous driving, the metaverse, robotics, or cryptocurrency, NVIDIA is leveraging its massive computing power to seek new opportunities. Computing power, NVIDIA's eternal weapon.

Three Near-Death Experiences Shaped Resilience

In 2023, Jen-Hsun Huang delivered a speech at the graduation ceremony of National Taiwan University, sharing three stories of failure. The first failure involved surviving on the brink of bankruptcy. In 1994, Nvidia's first customer was the Japanese gaming company SEGA, but in the following year, Microsoft released Direct3D, which caused great panic at Nvidia. Ultimately, Nvidia chose to terminate the contract with SEGA and instead developed GPUs for the Windows platform. Nvidia's funding could only support operations for 6 months, and just one month away from bankruptcy, Nvidia designed the Riva 128 chip. By the end of 1997, shipments of the Riva 128 exceeded 1 million units.

The second failure, giving up short-term profits, led to great achievements in the future. After the release of CUDA in 2007, creating a new computing model was very difficult; the CPU computing model has existed as the industry standard for nearly 60 years since the launch of the IBM System 360. NVIDIA's years of poor performance made shareholders skeptical about CUDA, but NVIDIA persevered.

The third failure, NVIDIA exits the mobile chip market. In 2013, the Xiaomi 3 flagship version was equipped with the mobile version of NVIDIA's Tegra4 processor, marking the end of this series. Despite the vastness of the entire mobile market, NVIDIA could have fought for market share, but they made a difficult decision: to abandon this market. Jen-Hsun Huang stated that NVIDIA's mission is to build computers that ordinary computers cannot.

In 2024, Jen-Hsun Huang returned to his alma mater Stanford University to give a speech. When the host asked for advice on success, he replied, “I hope you all have the opportunity to experience a lot of pain and hardship.” He mentioned that one of his greatest strengths is that “my expectations are very low.” Jen-Hsun Huang stated, “People who have very high expectations for themselves often have low resilience, and unfortunately, resilience is crucial for success. Success does not come from intelligence, but from character, and character is shaped by experiencing suffering.”

What makes NVIDIA most enviable is its “freedom from cyclical limitations”. It has always served as the underlying infrastructure, continuously “collecting taxes”; no matter what you do, you cannot escape it. This strategic resilience stems from its commitment to the core value of general computing power and its long-term investment in key technologies.