Nvidia’s Share of Future AI Chip Deals Falls to 39% as AMD and Rivals Gain Ground
Nvidia's position in the market for computing infrastructure used by leading artificial intelligence developers is facing increasing competition, with JPMorgan estimating that the chipmaker holds 39% of future compute deals among frontier AI laboratories. That compares with a market share of more than 80% between 2023 and 2025, according to figures shared by Coin Bureau.
The remaining share of future deals is distributed among several competing chip platforms. Broadcom custom chips account for 24%, Google Tensor Processing Units (TPUs) for 16%, AMD for 15% and Amazon Trainium for 6%, highlighting the range of alternatives being pursued by major AI developers.
AMD Chip Transition Reportedly Takes Just Three Days
One of the developments cited in the report concerns how quickly an AI laboratory can move its models to hardware from another supplier. According to the information shared by Coin Bureau, one frontier AI lab said switching its models to AMD chips now takes three days, compared with an earlier estimate of six to 12 months.
The lab attributed the shorter transition period to its own AI performing the engineering work required for the switch. The reported change illustrates how the use of AI in engineering processes can reduce the time involved in adapting models to different chip architectures.
The development is relevant to Nvidia's competitive position because the ability to move workloads between hardware providers can give AI laboratories more flexibility when selecting computing infrastructure. The source, however, does not identify the laboratory or specify which AMD chips are involved.
Major AI Chip Buyers Are Developing Their Own Hardware
The report also points to efforts by leading AI companies to develop their own chip technologies. Of the seven largest AI chip buyers, "only SpaceX is not trying to build their own," according to the statement cited by Coin Bureau.
That trend adds another dimension to competition in the AI infrastructure market. Alongside purchases from Nvidia, AMD and other suppliers, some of the largest buyers are pursuing in-house hardware development rather than relying entirely on external chip providers.
Nvidia's Investment and Acquisition Spending
JPMorgan's note also highlighted Nvidia's capital allocation. The company spent 58% of its operating cash flow on equity investments and acquisitions over the last three quarters, according to the figures reported by Coin Bureau.
The timing of the note was also notable: it was published two days after Jensen Huang resigned as CEO on November 12, as stated in the original post. The report did not provide further details about the circumstances of the resignation.
Together, the figures point to a changing competitive landscape for AI computing. JPMorgan's estimate places Nvidia at 39% of future frontier AI lab compute deals, while Broadcom custom chips, Google TPUs, AMD and Amazon Trainium account for the other reported portions of the market.
Writer: Victoria HaleTechnology & Blockchain WriterVictoria Hale writes about blockchain technology, digital infrastructure, and the intersection of emerging technologies with finance. Her articles explore how new protocols and systems are shaping the evolving digital economy.She prioritises clarity and accuracy when explaining technical developments to a general audience.
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