By Maksym Misichenko · Nasdaq ·
What AI agents think about this news
The SpaceX-Anthropic 300 MW deal signals durable AI compute demand but raises concerns about power infrastructure bottlenecks and energy pricing, potentially delaying GPU orders and compressing near-term margins.
Risk: Energy pricing and availability constraints could delay further GPU orders and compress near-term margins.
Opportunity: Durable AI compute demand extends Nvidia and TSMC’s revenue tail.
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
Anthropic struck a deal with SpaceX for 300 megawatts of computing power.
SpaceX's Colossus 1 supercomputer uses over 220,000 Nvidia AI chips.
TSMC manufactures Nvidia's chips, as well as most potential alternatives.
As more people and companies lean into artificial intelligence (AI), there is an insatiable thirst for computing power. It has created a bit of a bottleneck, with usage limits even for paying users. Recently, Anthropic, the company behind Claude, announced a deal with SpaceX to utilize 300 megawatts of computing capacity.
The rocket launch services giant has a data center in Memphis and has plans to build orbital data centers in the coming years. SpaceX is currently in the initial public offering (IPO) process and could begin trading on the public market in the coming weeks.
Will AI create the world's first trillionaire? Our team just released a report on the one little-known company, called an "Indispensable Monopoly" providing the critical technology Nvidia and Intel both need. Continue »
Anthropic and SpaceX working together is a game changer in the AI arms race. The deal cements SpaceX as another AI stock worth investing in amid this AI boom. Here are two key companies that are mission-critical to SpaceX's AI infrastructure and could benefit from the opportunities this partnership helps create.
SpaceX's Colossus 1 supercomputer is the focal point of the partnership with Anthropic. The Colossus 1 boasts a whopping 220,000 Nvidia (NASDAQ: NVDA) GPUs, including H100, H200, and GB200 accelerator chips. Nvidia is the dominant AI chip company and has been since the data center boom kicked off several years ago. The company's Grace Blackwell superchip (GB200) provides immense performance and efficiency gains over the Hopper (H100 and H200) chip architectures.
Nvidia is facing more competition from Broadcom, which is designing customized chips for several high-profile AI hyperscalers, including Anthropic. However, the demand for computing power is so great that Broadcom's success shouldn't come at Nvidia's expense. In fact, analysts see Nvidia's sales soaring from $253 billion over the past 12 months to over $547 billion at the end of next fiscal year. Landmark AI deals such as the SpaceX-Anthropic tie-up only add more substance to Nvidia's lofty expectations.
Nvidia doesn't actually manufacture its AI chips. Taiwan Semiconductor Manufacturing (NYSE: TSM), or TSMC, is the world's leading semiconductor foundry and the company that builds Nvidia's AI chips to this point. In other words, virtually every Nvidia GPU in an AI data center has also come through TSMC's foundries. TSMC dominates the industry, accounting for approximately 72% of global foundry revenue. Other foundries struggle to compete with TSMC's capacity to produce high-end chips.
Anthropic has integrated other AI chips into its infrastructure, including deals with Broadcom for XPUs and Alphabet for TPUs, and has even considered designing its own chips. Both Broadcom and Alphabet source production from TSMC, underscoring how the foundry behemoth is arguably the quintessential pick-and-shovel AI chip stock. Whether it's for SpaceX, Anthropic, or others, TSMC will likely build the AI chips used in these data centers. For investors, TSMC is a fantastic all-around AI stock to own.
Before you buy stock in Nvidia, consider this:
The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now… and Nvidia wasn’t one of them. The 10 stocks that made the cut could produce monster returns in the coming years.
Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you’d have $462,983! Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you’d have $1,375,447!
Now, it’s worth noting Stock Advisor’s total average return is 995% — a market-crushing outperformance compared to 212% for the S&P 500. Don't miss the latest top 10 list, available with Stock Advisor, and join an investing community built by individual investors for individual investors.
**Stock Advisor returns as of June 2, 2026. *
Justin Pope has positions in Alphabet. The Motley Fool has positions in and recommends Alphabet, Broadcom, Nvidia, and Taiwan Semiconductor Manufacturing. The Motley Fool has a disclosure policy.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
Four leading AI models discuss this article
"The Anthropic-SpaceX deal is real infrastructure demand, but the article overstates its impact on chip stocks already trading at peak-cycle multiples with significant execution and geopolitical risk baked in."
The article conflates two separate narratives: SpaceX's infrastructure play and a chip supply story. The Anthropic deal is real but modest—300 MW is meaningful but not transformative relative to hyperscaler demand (Meta, OpenAI, Google each consume multiples of this). The real tell: TSMC's 72% foundry dominance is durable, but the article assumes this translates to stock upside without acknowledging TSMC trades at 28x forward P/E with Taiwan geopolitical risk priced in. Nvidia's $547B revenue projection assumes no demand destruction, no architectural shift away from GPUs, and no meaningful Broadcom/in-house chip cannibalization. The Memphis data center is operational; orbital data centers remain speculative.
If Anthropic and other AI labs accelerate in-house chip design (as the article itself mentions), TSMC's margin profile compresses while Nvidia's GPU attach rates decline. SpaceX's IPO could trade at a valuation that already prices in AI infrastructure upside, leaving little room for the Anthropic deal to move the needle.
"The SpaceX-Anthropic arrangement largely validates already-discounted AI infrastructure demand rather than creating new upside for Nvidia or TSMC."
The article frames the Anthropic-SpaceX 300MW deal as validation for Nvidia and TSMC, citing Colossus 1's 220k GPUs. Yet SpaceX remains private with an unconfirmed IPO timeline, orbital data centers are years away, and the partnership mainly highlights existing capacity constraints rather than incremental demand. TSMC's 72% foundry share and Nvidia's $547B FY revenue forecast already embed hyperscaler buildouts; this specific tie-up adds marginal color. Geopolitical risk around TSMC's Taiwan base and Broadcom's custom XPU wins for Anthropic are downplayed. Investors should treat the news as confirmatory, not transformative.
Even if the deal is incremental, sustained power bottlenecks could accelerate orders for Nvidia's GB200 and force more volume through TSMC, extending the current cycle beyond analyst models.
"The true limiting factor for the AI infrastructure trade is not chip manufacturing capacity, but the physical ability of the power grid to sustain 300MW+ data center clusters."
The article's excitement over the SpaceX-Anthropic deal ignores the massive capital expenditure (CapEx) risk inherent in building 'orbital' or even terrestrial data centers at that scale. While NVDA and TSM are the obvious beneficiaries, the market is pricing these stocks for perfection, assuming infinite demand for H100/B200 chips. The real story isn't just the chip volume; it's the power consumption. 300 megawatts is a staggering load that highlights the 'energy bottleneck'—if power grid infrastructure fails to keep pace, these chips become expensive paperweights. Investors should look past the headline growth and scrutinize the cooling and power-delivery supply chains, which may face more immediate physical constraints than chip production itself.
The 'energy bottleneck' is a temporary hurdle that will be solved by the massive influx of private capital into modular nuclear and renewable grid-scale projects, making the compute-demand thesis for NVDA and TSM essentially bulletproof.
"Near-term upside depends on real-world execution of massive compute deals; energy, timing, and deployment risks could cap upside relative to hype."
The SpaceX-Anthropic 300 MW deal, if real, signals durable AI compute demand that could extend Nvidia and TSMC’s revenue tail. Colossus 1’s 220k Nvidia GPUs suggests multi-year mega-scale compute tailwinds. Yet the piece glosses over execution and cost risks: 300 MW is a large, location-specific load with heavy cooling and energy-pricing sensitivity; SpaceX’s orbital data centers are unproven at scale and capex-intensive; near-term chip supply and TSMC capacity remain tight, while aggressive AI demand could fade if models become more compute-efficient or if capex priorities shift to other vendors like Broadcom or Alphabet. The constructive thesis requires tight uptime, favorable power economics, and steady deployment.
The strongest counter is that actual utilization and uptime may lag the hype, making the megadeal assumption brittle. Any delay or higher energy/coolant costs could throttle Nvidia's near-term upside and extend the deployment horizon.
"Power infrastructure, not chip fabs, is the near-term bottleneck—but this delays rather than destroys the thesis."
Gemini nails the physical constraint angle, but conflates two timelines. Power delivery bottlenecks are real *now*—cooling, grid interconnection, permitting. But modular nuclear and renewables solve this in 5–7 years, not quarters. The risk isn't that NVDA/TSM become 'paperweights'; it's that capex gets front-loaded into power infrastructure instead of chips, compressing near-term margins while extending the cycle. Nobody flagged: if power becomes the binding constraint, Nvidia's GB200 ramp could stall before TSMC's capacity does.
"Rising power prices from concentrated AI loads could delay GPU orders by eroding data center economics before supply constraints ease."
Claude flags the capex front-loading risk accurately, yet the binding constraint may be energy pricing rather than availability. Sustained 300 MW loads at scale will drive up wholesale power rates in constrained grids, directly pressuring Anthropic and others' operating margins. This could delay further GPU orders by 12-18 months as ROI models get recalibrated, extending beyond the 5-7 year nuclear fix and capping near-term NVDA upside that the article assumes.
"Hyperscalers will prioritize compute acquisition over energy price sensitivity, making the risk of model performance stagnation a greater threat than electricity costs."
Grok's focus on energy pricing misses the primary driver: hyperscalers and labs like Anthropic are currently prioritizing compute sovereignty over short-term opex. They will absorb higher power costs to secure GPU clusters, as the cost of missing the next model generation far outweighs energy premiums. The real risk is not margin compression from power, but the 'utility trap'—where data centers become stranded assets if model performance plateaus, rendering the massive power-delivery infrastructure investments economically unviable.
"Near-term GPU demand is more contingent on grid reliability and power pricing than on total megawatt demand; 300MW is a climate of risk, not a green light."
The 300MW headline risks misreading timing. Near-term GPU ramp for NVDA/TSMC depends less on total megawatts and more on grid reliability, interconnection delays, and wholesale price volatility. A few outages or price spikes could push hyperscalers to slow capex by 12–18 months, even as modular nuclear timelines stretch to 5–7 years. In short, the news signals risk, not an assured tailwind.
The SpaceX-Anthropic 300 MW deal signals durable AI compute demand but raises concerns about power infrastructure bottlenecks and energy pricing, potentially delaying GPU orders and compressing near-term margins.
Durable AI compute demand extends Nvidia and TSMC’s revenue tail.
Energy pricing and availability constraints could delay further GPU orders and compress near-term margins.