[News] Nvidia vs. AMD, the Expensive Duel as Two Major Buyers Opt for AMD’s Latest AI GPU

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AMD has long aspired to gain more favor for its AI chips, aiming to break into Nvidia’s stronghold in the AI chip market. Key players like Meta, OpenAI, and Microsoft, who are major buyers of AI chips, also desire a diversified market with multiple AI chip suppliers to avoid vendor lock-in issues and reduce costs.

With AMD’s latest AI chip, Instinct MI300X slated for significant shipments in early 2024, these three major AI chip buyers have publicly announced their plans to place orders as they consider AMD’s solution a more cost-effective alternative.

At the AMD “Advancing AI” event on December 6th, Meta, OpenAI, Microsoft, and Oracle declared their preference for AMD’s latest AI chip, Instinct MI300X. This marks a groundbreaking move by AI tech giants actively seeking alternatives to Nvidia’s expensive GPUs.

For applications like OpenAI’s ChatGPT, Nvidia GPUs have played a crucial role. However, if the AMD MI300X can provide a significant cost advantage, it has the potential to impact Nvidia’s sales performance and challenge its market dominance in AI chips.

AMD’s Three Major Challenges

AMD grapples with three major challenges: convincing enterprises to consider substitutions, addressing industry standards compared to Nvidia’s CUDA software, and determining competitive GPU pricing. Lisa Su, AMD’s CEO, highlighted at the event that the new MI300X architecture features 192GB of high-performance HBM3, delivering not only faster data transfer but also meeting the demands of larger AI models. Su emphasized that such a notable performance boost translates directly into an enhanced user experience, enabling quicker responses to complex user queries.

However, AMD is currently facing critical challenges. Companies that heavily rely on Nvidia may hesitate to invest their time and resources in an alternative GPU supplier like AMD. Su believes that there is an opportunity to make efforts in persuading these AI tech giants to adopt AMD GPUs.

Another pivotal concern is that Nvidia has established its CUDA software as the industry standard, resulting in a highly loyal customer base. In response, AMD has made improvements to its ROCm software suite to effectively compete in this space. Lastly, pricing is a crucial issue, as AMD did not disclose the price of the MI300X during the event. Convincing customers to choose AMD over Nvidia, whose chips are priced around USD 40,000 each, will require substantial cost advantages in both the purchase and operation of AMD’s offerings.

The Overall Size of the AI GPU Market is Expected to Reach USD 400 Billion by 2027

AMD has already secured agreements with companies eager for high-performance GPUs to use MI300X. Meta plans to leverage MI300X GPUs for AI inference tasks like AI graphics, image editing, and AI assistants. On the other hands, Microsoft’s CTO, Kevin Scott, announced that the company will provide access to MI300X through Azure web service.

Additionally, OpenAI has decided to have its GPU programming language Triton, a dedication to machine learning algorithm development, support AMD MI300X. Oracle Cloud Infrastructure (OCI) intends to introduce bare-metal instances based on AMD MI300X GPUs in its high-performance accelerated computing instances for AI.

AMD anticipates that the annual revenue from its GPUs for data centers will reach USD 2 billion by 2024. This projected figure is substantially lower than Nvidia’s most recent quarterly sales related to the data center business (i.e., over USD 14 billion, including sales unrelated to GPUs). AMD emphasizes that with the rising demand for high-end AI chips, the AI GPU market’s overall size is expected to reach USD 400 billion by 2027. This strategic focus on AI GPU products underscores AMD’s optimism about capturing a significant market share. Lisa Su is confident that AMD is poised for success in this endeavor.

(Image: AMD)