Tucked inside SpaceX’s pre-IPO S-1 filing are two project names most investors have never heard. Macrohard is an agentic AI software platform, and Terafab is a vertically integrated chip fabrication initiative. Tesla is the partner on both. SpaceX disclosed that financial terms, intellectual property rights, and the ultimate term of the collaboration are not yet finalized, and that both projects are in very early stages.
The underlying trend is the AI infrastructure buildout and the race to own the chip stack. Several companies benefit, but exposure varies. I looked at three stocks to see who actually wins.
Three Companies Betting on Vertically Integrated AI Compute
Tesla (NASDAQ: TSLA | TSLA Price Prediction) sells electric vehicles and energy products, but the AI roadmap is now central. Q1 brought $22.39 billion in revenue, up 15.8% year over year, and 1.28 million active FSD subscriptions, up 51%. Tesla also disclosed a semiconductor research fab groundbreaking at Gigafactory Texas in partnership with SpaceX alongside a $2 billion equity investment in SpaceX.
NVIDIA (NASDAQ: NVDA) sells the GPUs and networking that power the AI factories every hyperscaler is racing to build. I’ve owned NVIDIA for over 15 years now, and the latest earnings report still surprised me. Q1 FY27 revenue hit $81.6 billion, up 85% year over year, with Data Center revenue of $75.25 billion, up 92%.
Applied Materials (NASDAQ: AMAT) is the picks and shovels equipment maker behind every leading edge fab on earth. TSMC, Samsung, SK hynix, Micron, and Intel all buy its gear. Q2 FY26 revenue hit $7.91 billion, up 11.4%, and management raised its calendar 2026 semiconductor equipment growth outlook to more than 30%.
How Each Business Is Positioned
| Company | What They Sell | Trend Exposure | Key Advantage |
|---|---|---|---|
| Tesla | EVs, FSD, custom AI silicon | High, long-dated | Vertical integration via Terafab and Macrohard |
| NVIDIA | AI GPUs, networking, software | High, immediate | Platform that runs in every cloud |
| Applied Materials | Fab equipment, services | High, durable | Sells into every advanced node fab |
NVIDIA is converting the AI buildout into cash today. Applied Materials benefits no matter which chip company wins, because all of them buy its deposition, etch, and packaging tools. Tesla’s Terafab bet is the most differentiated of the three, but per SpaceX’s own disclosure, the projects remain very early stage.
The price action supports the read. AMAT is up 66% year to date, NVIDIA up 20%, and Tesla down 7%.
Straight From the Earnings Calls
NVIDIA CEO Jensen Huang: “Agentic AI has arrived, doing productive work, generating real value and scaling rapidly across companies and industries.”
Applied Materials CEO Gary Dickerson: “The rapid global build-out of AI computing infrastructure combined with Applied’s strong leadership positions in leading-edge logic, DRAM and advanced packaging provide an exceptionally strong foundation for sustained, multi-year revenue and profit growth.”
Tesla’s Q1 materials did not include direct management quotes on Terafab or Macrohard. The narrative is leaking out through SpaceX’s S-1 rather than surfacing on Tesla’s earnings call.
Who Actually Benefits Most
Based on customer base, revenue exposure, and where dollars are flowing today, Applied Materials looks best positioned to benefit regardless of how the chip race shakes out. If Terafab gets built, AMAT sells the tools. If it never breaks ground, TSMC and Samsung still buy. NVIDIA is the cleanest near-term winner with the strongest financial momentum. Tesla offers the most asymmetric upside, but Polymarket assigns only 15.5% odds to a formal Tesla and SpaceX merger announcement by year end, suggesting the JV optionality is real but largely unpriced.
The Bottom Line
The AI compute buildout is the trend. Applied Materials is the broadest beneficiary, NVIDIA the loudest, and Tesla the wildcard. Macrohard and Terafab remain very early stage per SpaceX’s S-1, with no finalized terms. Watch Tesla’s next earnings call for any signal that these projects move from disclosure to detail.