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AIBusinessElon MuskIntelSpaceX

Intel joins Musk’s Terafab mega-fab with SpaceX, Tesla and xAI for 1TW AI chips

Intel is plugging into Elon Musk’s Terafab complex, teaming with SpaceX, Tesla and xAI to chase an audacious 1 terawatt of AI compute a year.

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Shubham Sawarkar
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ByShubham Sawarkar
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I’m a tech enthusiast who loves exploring gadgets, trends, and innovations. With certifications in CISCO Routing & Switching and Windows Server Administration, I bring a sharp...
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Apr 8, 2026, 3:55 AM EDT
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Intel CEO Lip-Bu Tan and Elon Musk shaking hands.
Photo: Intel
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Intel is sliding into Elon Musk’s most ambitious hardware play yet: Terafab, a mega chip project that aims to crank out an almost absurd 1 terawatt of AI compute per year for cars, robots and even space data centers. In one move, Intel goes from “trying to catch up in AI” to sitting at the same table as SpaceX, Tesla and xAI on what might be the wildest bet in the semiconductor world right now.

Terafab itself is already a flex. Musk pitched it as a fully vertically integrated fab complex built in Austin, designed to bring everything under one roof: chip design, advanced lithography, memory, packaging and final testing, instead of splitting that work across multiple companies and continents. The goal is not just “more chips,” but enough compute to dwarf today’s global AI capacity, with internal estimates targeting more than 1 terawatt of AI compute per year, compared with roughly tens of gigawatts for today’s entire AI stack worldwide.

Until now, Terafab has been framed as a Tesla–SpaceX–xAI joint venture, tightly aligned with Musk’s obsession with Full Self-Driving, robotaxis, Optimus humanoid robots and space-based AI infrastructure for Starlink and xAI’s Grok models. The rough split Musk and insiders keep pointing to is telling: about 20 percent of Terafab’s output is meant for terrestrial workloads like cars and robots, while a massive 80 percent is earmarked for orbital compute, running in space on solar power.

Into that picture walks Intel. In its post, the chipmaker called Terafab a “highly strategic project” and emphasized exactly the pieces Musk needs: the ability to design, fabricate and package ultra‑high‑performance chips at scale. Intel says those capabilities are meant to accelerate Terafab’s aim of producing 1 terawatt per year of compute for future advances in AI and robotics, which is marketing talk, but it’s also a quiet admission that this single project could sit at the center of the next wave of AI infrastructure.

On paper, the fit is strangely clean. Musk wants a single, insanely large pipeline that can turn capital expenditure into compute as efficiently as possible, without being held hostage by a handful of external foundries. Intel, meanwhile, has been trying to reinvent itself as a contract foundry, spending heavily to prove it can manufacture advanced chips not only for its own CPUs but also for external partners that might otherwise go to TSMC or Samsung.

Terafab is not a normal fab program; the scale being discussed here is almost cartoonish by today’s standards. Analysts estimate that hitting a true 1‑terawatt compute output could imply processing millions of advanced wafers a year and, in extreme scenarios, even dozens to hundreds of fab modules if the project ever fully matched Musk’s loftiest rhetoric. Even more conservative breakdowns describe Terafab as targeting 100,000 wafers per month initially, ramping toward a million wafers per month and output on the order of 100–200 billion AI chips per year across different product lines.

The product roadmap attached to this thing is equally aggressive. On the ground, Terafab is meant to feed Tesla’s fifth‑generation AI chip (often referred to as “AI5”) for Full Self‑Driving, the Cybercab robotaxi fleet and Optimus humanoid robots, with limited runs in 2026 and high‑volume production around 2027. In orbit, the project includes a radiation‑hardened “D3” chip line geared for hostile space environments, powering next‑gen Starlink nodes, on‑board Starship compute and xAI inference clusters hosted in orbital data centers.

This is where the Intel angle really matters. Building radiation‑tolerant, high‑reliability chips at advanced process nodes is not something you spin up overnight, especially at the volumes Musk is talking about. Intel has decades of experience in process engineering, packaging and yield optimization, and plugging that into Terafab could shave years off the learning curve of a brand‑new mega‑fab ecosystem that’s trying to leapfrog straight to bleeding‑edge nodes and exotic packaging.

There is also a money and risk story under the surface. Terafab has been described as a $20–25 billion project just for the first phase, separate from Tesla’s already huge annual capex. For Intel, allying with this project spreads some of that risk, but it also potentially locks in a long‑term, very high‑volume customer at a time when AI demand is one of the only reliable growth stories in chips.

On Musk’s side, bringing Intel into the tent is a way to signal that Terafab is not just a sci‑fi pitch but something anchored in real manufacturing muscle. SpaceX has already merged with xAI, Tesla keeps promising mass‑produced robots and robotaxis, and now the hardware engine behind all of that suddenly has a blue‑chip semiconductor partner attached to it. It also sends a message to NVIDIA, TSMC and others that Musk does not plan to stay a supplicant in the AI chip supply chain forever.

Investors noticed quickly. Intel’s stock ticked higher on the partnership news as markets tried to figure out whether this was Intel getting “rescued” by Musk’s demand pipeline, or Musk getting rescued by Intel’s fabs. The more realistic answer is that both sides are trading something they desperately need: Musk gets manufacturing credibility and process know‑how, while Intel gets relevance in the most hyped corner of the chip market.

The bigger question is whether Terafab can actually deliver the scale its creators are talking about. Turning 1 terawatt of theoretical compute into working hardware means conquering every problem that plagues the industry today: tool lead times, defect density, power and cooling, packaging bottlenecks, supply of advanced memory and, in Terafab’s case, even the challenge of operating huge AI data centers in orbit. If it works, though, the project could reshape how people think about AI infrastructure, shifting the conversation from “who can buy the most GPUs” to “who can control entire compute ecosystems from sand to satellite.”


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