Nvidia plans to invest $5 billion in Intel in a move analysts say will help the chip giant branch out into lucrative new markets.
Announced this week, the partnership will see the two rivals collaborate on data center and PC hardware. The immediate aim is to ensure Intel’s data center architecture – in particular its x86 ecosystem – can connect to Nvidia’s via its proprietary NVLink technology.
In time this will yield Intel-built, custom CPUs for Nvidia that will connect its market-leading GPUs within data centers.
The pair will also collaborate on new hardware in the consumer PC market, with Intel set to build x86 system-on-chips (SoCs) that will complement Nvidia’s RTX range of graphics cards, used for gaming and graphics-intensive applications such as computer assisted design (CAD) software.
“Intel’s x86 architecture has been foundational to modern computing for decades — and we are innovating across our portfolio to enable the workloads of the future,” said Lip-Bu Tan, CEO of Intel.
“Intel’s leading data center and client computing platforms, combined with our process technology, manufacturing and advanced packaging capabilities, will complement Nvidia's AI and accelerated computing leadership to enable new breakthroughs for the industry,” he added.
“We appreciate the confidence Jensen and the Nvidia team have placed in us with their investment and look forward to the work ahead as we innovate for customers and grow our business.”
Nvidia is the big winner
Intel has struggled in recent years to curb Nvidia’s meteoric rise to becoming not only the largest chip company, but also the most valuable company in the world.
The former chip titan’s shares fell 60% in 2024, the same year the firm slashed 15,000 roles and missed its own targets for AI hardware dominance.
Tan’s time as leader so far has been marked by a sharp strategic shift and stabilizing financials, though the firm still reported a net loss of $2.9 billion in its Q2 earnings statement.
In this light, the announcement with Nvidia could come as welcome news to Intel shareholders and help the company increase its US spending. Mario Morales, group vice president, Enabling Technologies and Semiconductors at IDC, said the partnership will be seen as a “positive move for both companies”.
Nvidia, however, will likely be the big winner given it now has an opportunity to capitalize on a broader array of markets.
“They are leveraging each other's strengths to deliver products to customers, particularly in the enterprise sector,” he said.
“This collaboration will help Nvidia expand into new markets beyond the data center, focusing on AI inferencing across various endpoints like PCs, smartphones, and autonomous systems that can leverage a collection of compute chiplets and dry the requirements of performance efficiency.”
The partnership comes just weeks after the US government took a 10% stake in Intel for $8.9 billion, amid financial woes, layoffs, and criticism of CEO Lip-Bu Tan by President Trump.
Under the terms of the deal, the purchase will be financed with a remaining grant of $5.7 billion from the US CHIPS Act and $3.2 billion from the Secure Enclave program – both legacies of the Biden administration.
The funding comes with the caveat of all spending needing to be carried out within the US, in alignment with each act’s stated aim of improving the US semiconductor industry and making it more competitive with China.
In the wake of tech tariffs and a greater focus by the Trump administration on domestic manufacturing, Nvidia has also been under pressure to reduce its reliance on firms such as Taiwan-based TSMC.
Its partnership with Intel will push it closer to US-centric operations, though the chip giant still heavily depends on TSMC, which produces 90% of the world’s advanced chips.
“The announcement today highlights the ongoing AI race between the US and China,” Morales added.
“While the US currently leads in technology, China is rapidly advancing with its own AI initiatives. The collaboration between Nvidia and Intel is seen as a strategic move to maintain US leadership in AI technology infrastructure and endpoints.”
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