A guide to Nvidia's competitors: AMD, Qualcomm, Broadcom, startups, and more are vying to compete in the AI chip market
Nvidia is undoubtably dominant in the AI semiconductor space. Estimates fluctuate, but the company has more than 80% market share by some estimates when it comes to the chips that reside inside data centers and make products like ChatGPT and Claude possible.
That enviable dominance goes back almost two decades, when researchers began to realize that the same kind of intensive computing that made complex, visually stunning video games and graphics possible, could enable other types of computing too.
The company started building its famous software stack, named Compute Unified Device Architecture or CUDA, 16 years before the launch of ChatGPT. For much of that time, it lost money. But CEO Jensen Huang and a team of true believers saw the potential for graphics processing units to enable artificial intelligence. And today, Nvidia and its products are responsible for most of the artificial intelligence at work in the world.
Thanks to the prescience of Nvidia's leadership, the company had a big head start when it came to AI computing, but challengers are running fast to catch up. Some were competitors in the gaming or traditional semiconductor spaces, and others have started up from scratch.
AMD
AMD is Nvidia's top competitor in the market for AI computing in the data center. Helmed 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 Nvidia's second generation of data center GPUs started shipping.
Though experts and analysts have touted the chip's specifications and potential based on its design and architecture, the company's software is still somewhat behind that of Nvidia, making these chips somewhat harder to program and use to their full potential.
Analysts predict that the company has under 15% market share. But AMD executives insist that they are committed to bringing its software up to par and that future expectations for the evolution of the accelerated computing market will benefit the company — specifically, the spread of AI into so-called edge devices like phones and laptops.
Qualcomm, Broadcom, and custom chips
Also challenging Nvidia are application-specific integrated circuits or ASICs. These custom-designed chips are less versatile than GPUs, but they can be designed for specific AI computing workloads at a much lower cost, which have made them a popular option for hyperscalers.
Though multipurpose chips like Nvidia's and AMD's graphics processing units are likely to maintain the largest share of the AI-chip market in the long term, custom chips are growing fast. Morgan Stanley analysts expected the market for ASICs to double in size in 2025.
Companies that specialize in ASICs include Broadcom and Marvell, along with the Asia-based players Alchip Technologies and MediaTek.
Marvell is in part responsible for Amazon's Trainium chips while Broadcom builds Google's tensor processing units, among others. OpenAI, Apple, Microsoft, Meta, and TikTok parent company ByteDance have all entered the race for a competitive ASIC as well.
Amazon and Google
While also being prominent customers of Nvidia, the major cloud providers like Amazon Web Services and Google Cloud Platform, often called hyperscalers, have also made efforts to design their own chips, often with the help of semiconductor companies.
Amazon's Trainium chips and Google's TPUs are the most scaled of these efforts and offer a cheaper alternative to Nvidia chips, mostly for the companies' internal AI workloads. However, the companies have shown some progress in getting customers and partners to use their chips as well. Anthropic has committed to running some workloads on Amazon's chips, and Apple has done the same with Google's.
Intel
Once the great American name in chip-making, Intel has fallen far behind its competitors in the age of AI. But, the firm does have a line of AI chips called Gaudi that some reports have said can stand up to Nvidia's in some respects.
Intel installed a new CEO, semiconductor veteran Lip-Bu Tan, in the first quarter of 2025 and one of his first actions was to flatten the organization so that the AI chip operations reports directly to him.
Huawei
Though Nvidia's American hopeful challengers are many, China's Huawei is perhaps the most concerning competitor of all for Nvidia and all those concerned with continued US supremacy in AI.
Huang himself has called Huawei the "single most formidable" tech company in China. Reports that Huawei's AI chip innovation is catching up are increasing in frequency. New restrictions from the Biden and Trump administrations on shipping even lower-power GPUs to China have further incentivized the company to catch up and serve the Chinese markets for AI. Analysts say further restrictions being considered by the Trump administration are now unlikely to hamper China's AI progress.
Startups
Also challenging Nvidia are a host of startups offering new chip designs and business models to the AI computing market.
These firms are starting out at a disadvantage, as they don't have the full-sized sales and distribution machines decades of chip sales in other types of tech bring. But several are holding their own by finding use cases, customers, and distribution methods that are attractive to customers based on faster processing speeds or lower cost. These new AI players include Cerebras, Etched, Groq, Positron AI, Sambanova Systems, and Tenstorrent, among others.
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