• Intel joins Musk’s Terafab project with Tesla and SpaceX to build AI chips.
• Project aims to expand computing capacity as AI demand grows.

Intel is stepping into a large-scale chip project tied to Elon Musk’s plans for robotics and AI infrastructure, marking a change in how the company positions itself in the race for advanced computing.

The partnership links Intel with Musk’s Terafab initiative, which also involves SpaceX and Tesla. The project is aimed at building processors for robotics systems and AI data centres. Intel’s stock rose more than 2% following the news. The move follows earlier plans from Tesla to build a chip manufacturing site to support its work on self-driving vehicles and AI. At the time, Musk had hinted that Intel could play a role.

Intel said its manufacturing abilities could help Terafab reach its target of producing one terawatt of compute power each year. To put that figure in context, the planned output would represent a large increase in available compute capacity, highlighting the scale of demand Musk expects from AI and robotics workloads in the coming years.

The project is expected to require tens of billions of dollars in investment, with some early estimates placing costs at around US$20 billion or more depending on how the facilities are built and expanded. In a post on social media, Intel CEO Lip-Bu Tan said, “Elon has a proven track record of re-imagining entire industries. The is exactly what is needed in semiconductor manufacturing today. Terafab represents a step change in how silicon logic, memory and packaging will get built in the future.”

Unlike traditional chip supply chains, which are spread in multiple companies and regions, Terafab is expected to bring parts of chip design and packaging into a more unified setup.

Musk has also outlined plans to build two chip factories in Austin, Texas, one to support Tesla’s vehicles and humanoid robots, and the other for AI data centres, including systems designed for use in space. The chips are expected to support a range of workloads, from training AI models to running autonomous driving systems and robotics platforms, all of which require large amounts of processing power.

Demand for AI compute has risen sharply in recent years, driven by larger models, real-time systems, and growing volumes of data.

SpaceX, AI demand, and expanding compute needs

At the same time, SpaceX has filed confidentially for a US initial public offering. The listing could take place later this year and may rank among the largest in the market.

The move also comes amid closer coordination between SpaceX and Musk’s AI efforts, pointing to stronger links between space infrastructure and AI development. Some of these systems could rely on specialised chips designed for space-based computing, adding another layer to the demand for computing power.

Intel’s turnaround and foundry strategy

The deal comes as Intel tries to recover ground in AI and advanced chip manufacturing after facing strong competition in high-performance processors for AI workloads.

Gil Luria, an analyst at D.A. Davidson, said Intel needs to show it can handle major projects, and described the Tesla-related work as an important step in that direction. CEO Lip-Bu Tan has been leading a restructuring effort for over a year that includes job cuts, asset sales, and efforts to stabilise Intel’s finances. Intel has also received funding from Nvidia and the US government, which now holds a major stake.

The company has been trying to position itself as both a chip designer and a contract manufacturer, aiming to win business from firms that want alternatives to existing foundry providers.

A central part of Intel’s strategy is its contract manufacturing business, Intel Foundry, which has struggled to turn a profit. It reported an operating loss of $10.32 billion in 2025, while revenue grew by just 3%. Intel is now placing more focus on its 18A manufacturing process, which was initially reserved for internal use but may be offered to external customers.

If adopted more widely, the process could play a role in future chip production for large-scale AI systems, including projects like Terafab. The scale and complexity of Terafab mean there are still open questions around execution. Building chip facilities of this size is difficult, and timelines can change due to technical and supply constraints.

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