Nvidia is undoubtedly dominant in the semiconductor space of AI. Estimates fluctuate, but the company has more than 80% market share by certain estimates with regard to fleas that reside in data centers and make products like Chatgpt and Claude Possible.
This enviable domination dates back almost two decades, when the researchers began to realize that the same type of intensive computer that also made video games and complex and visually breathtaking graphics, could also allow other types of computer science.
The company began to build its famous software stack, named Compute Unified Device Architecture or Cuda, 16 years before the launch of Chatgpt. During a large part of this time, he lost money. But CEO Jensen Huang and a team of real believers saw the potential of graphics treatment units to allow artificial intelligence. And today, Nvidia and its products are responsible for most of artificial intelligence at work in the world.
Thanks to the foreknowledge of NVIDIA leadership, the company was one step ahead of IA computers, but the challengers operate quickly to make up for their delay. Some were competitors in game games or traditional semiconductors, and others started zero.
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AMD, led by the CEO Lisa SU, is lagging behind of Nvidia but remains its most serious competitor. I-HWA Cheng / AFP via Getty Images
AMD is the best competitor in Nvidia on the IA computer market in the data center. Generated by its formidable CEO Lisa SU, AMD launched its own GPU, called the MI300, for the data center in 2024, more than a full year after the second generation of GPU of the Nvidia data center began to ship.
Although experts and analysts have praised the specifications and potential of the chip according to its design and architecture, the company’s software is still somewhat behind that of Nvidia, which makes these chips a little more difficult to program and use to their full potential.
Analysts provide that the company has less than 15% market share. But AMD managers insist that they are determined to put their software by SA and that future expectations for the evolution of the accelerated IT market will benefit the company – in particular the spread of AI in so -called on -board devices such as phones and laptops.
Qualcomm, Broadcom and Personalized Chips
Nvidia are also difficult, integrated circuits specific to application or ASIC. These custom -designed chips are less versatile than GPUs, but they can be designed for specific IT workloads at a much lower cost, which has made it a popular option for hyperscalers.
Although versatile fleas such as NVIDIA and AMD graphics processing units are likely to maintain the largest long -term flea market, personalized chips increase rapidly. Morgan Stanley analysts expected the ASIC double market in 2025.
Companies that specialize in the ASICs include Broadcom and Marvell, as well as players based in Asia Alchip Technologies and Mediatek.
Marvell is partly responsible for Amazon trainium fleas while Broadcom builds, among other things, the processing units of Google tensors. OPENAI, Apple, Microsoft, Meta and Tiktok Parent Company Bytedance also participated in the race for a competitive ASIC.
Amazon and Google
While also being NVIDIA leading customers, the main cloud suppliers like Amazon Web Services and Google Cloud Platform, often called hyperscalers, have also made efforts to design their own chips, often using semiconductor companies.
The Amazon trainium fleas and the Google TPUs are the most put to the scale of these efforts and offer a cheaper alternative to Nvidia fleas, mainly for the internal workloads of IA of companies. However, companies have shown progress in obtaining customers and partners to use their fleas. Anthropic has undertaken to execute certain workloads on Amazon’s chips, and Apple did the same with Google.
Intel
Intel and its GAUDI range of Puces AI had a hard time competing with Nvidia and AMD. Mandel Ngan / AFP via Getty Images
Formerly the big American name in the manufacture of shavings, Intel fell far behind its competitors in the AI era. However, the company has a line of fleas called Gaudi which, according to some reports, can resist Nvidia in some respects.
Intel installed a new CEO, the veteran of LIP-BU TAN semiconductors in the first quarter of 2025 and one of its first actions was to flatten the organization so that the operations of the AI chips report directly.
Huawei
Although Nvidia’s American Hope Challengers are numerous, Huawei of China is perhaps the most worrying competitor of all for Nvidia and all those affected by American supremacy continues in AI.
Huang himself called Huawei the “most formidable” technological society in China. The reports according to which the innovation of the Huawei chips AI catches increases in frequency. The new restrictions on Biden and Trump administrations on the expedition of GPUs even lower to China have still prompted the company to catch up and serve the Chinese markets for AI. Analysts claim that new restrictions envisaged by the Trump administration are now unlikely to hinder the progress of China AI.
Startups
The Nvidia also disputes a multitude of startups offering new conceptions of fleas and commercial models to the IA computer market.
These companies start in disadvantage, because they do not have decades of sales and full -scale distribution of flea sales in other types of technology. But many hold them by finding use cases, customers and distribution methods that are attractive for customers depending on faster treatment speeds or lower costs. These new AI players include cervres, engravings, groq, a positron ai, sambanova systems and tied, among others.