News
SpaceX CEO Elon Musk says major Starship engine bug is fixed as Raptor testing continues
SpaceX CEO Elon Musk has revealed the latest official photo of the company’s Raptor engine in action and indicated that a major technical issue with vibration appears to have been solved, hopefully paving the way for Starhopper’s first untethered flights.
Partly due to Musk’s own involvement in the program, SpaceX’s propulsion development team have struggled to get any single Raptor engine to survive more than 50-100 seconds of cumulative test fires. According to information from sources familiar with the program, Musk has enforced an exceptionally hardware-rich development program for the first full-scale Raptor engines to such an extent that several have been destroyed so completely that they could barely be used to inform design optimization work. Although likely more strenuous and inefficient than it needed to be, the exceptionally hardware-rich test program appears to have begun to show fruit, with the sixth engine built (SN06) passing its first tests without exhibiting signs of a problem that has plagued most of the five Raptors that came before it.
Resonance: not even once
In his tweet, Musk cryptically noted that a “600 Hz Raptor vibration problem” appears to have been fixed as of SN06’s first few static fire tests since arriving in McGregor, Texas. More likely than not, the self-taught SpaceX executive is referring to the hell that is mechanical resonance in complex machines and structures. Shown below, the Tacoma Narrows Bridge’s 1940 collapse – quite possibly the single most famous civil engineering failure of all time – is an iconic example of the unintuitive power of resonance in complex systems.
When it was inaugurated, the first Tacoma Narrows Bridge was one of the longest suspension bridges ever built and implemented new techniques and technologies that had never been tried at such a large scale. As Grady (Practical Engineer) aptly notes, mechanical resonance – in this case, triggered by consistent winds running through the Puget Sound – simply wasn’t something that period engineers knew they had to worry about. When rapidly pushing the envelope of engineering and construction, the chances of discovering entirely novel failure modes also increases – it’s simply one of the costs of extreme innovation.



Luckily for SpaceX, the company doesn’t have to clash with the immense challenge of testing something as large, complex, and expensive as a suspension bridge. Raptor, Starship, and Super Heavy need not necessarily be perfect on SpaceX’s first try, whereas civil bridges must essentially be flawless on the first try, despite being one of a kind. This is why SpaceX has been chewing through an average of one Raptor engine per month since February 2019 – by testing engines to destruction and aggressively comparing engineering expectations with observed behavior and post-test hardware conditions, rapid progress can (theoretically) be made.
Instead of spending another year or more analyzing models and testing subscale engines and components, SpaceX dove into integrated testing of a sort of minimum-viable-product Raptor design, accepting that the path to a flightworthy, finalized design would likely be paved with one or several dozen destroyed engines. According to Musk, the biggest pressing design deficiency involved a mode of mechanical resonance that may or may not have been predicted over the course of the design process. Dealing with unprecedented conditions, it’s not particularly surprising that some sort of new resonance mode was discovered in Raptor.
For the time being, SpaceX continues to work around the clock to build its first two orbital Starship prototypes (one in Texas, one in Florida), while also outfitting Starhopper and completing any possible engine-less tests in anticipation of the first flightworthy Raptor’s arrival. If Musk’s early analysis proves correct and Raptor SN06 makes it through lengthier static fire tests unscathed over the next week or so, the engine could potentially be delivered to Boca Chica as early as mid-July.
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Elon Musk
SpaceX’s next trillion dollar bet has nothing to do with rockets, Musk tells staff
Elon Musk told SpaceX staff AI revenue will soon dwarf rockets and Starlink combined entirely.
Elon Musk told SpaceX employees this week that artificial intelligence, not rockets, will soon carry the company’s revenue. In a roughly 29 minute internal address posted on SpaceX’s X account on Tuesday, Musk said AI revenue will pass every other line of business at SpaceX “probably in September” and pull further ahead by the fourth quarter.
The numbers he gave are specific. SpaceX currently runs 1.4 gigawatts of AI compute capacity. Musk wants that at 10 gigawatts by the end of 2027, a jump he tied directly to revenue: “if we bring 10GW of AI online by the end of next year, it will be $300 billion to $500 billion a year in revenue.” He called those “big numbers,” which undersells a projection larger than what most countries produce in a year.
We made rockets reusable and are rebuilding the internet in space. The next challenge: making life multiplanetary and understanding the true nature of the universe
Watch @ElonMusk deliver a company update to @SpaceX employees pic.twitter.com/5c8rxoCQfu
— SpaceX (@SpaceX) August 11, 2026
Musk went further on where AI fits into SpaceX’s future. “Probably in four or five years, AI will be 99% of the value of SpaceX,” he told staff, adding that digital intelligence would eventually run “a trillion times” ahead of biological intelligence as computing scales. He tied that growth to the company’s founding mission, telling employees “we must win on AI, because the future is overwhelmingly AI and robots,” with the payoff meant to help fund Starship and a Mars program that increasingly runs through Terafab, the joint Tesla, SpaceX and xAI chip plant.
Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry
None of this is entirely new territory. SpaceX told investors much the same story during its first earnings call as a public company on August 4, where Musk moved the company’s $1 trillion revenue target up a year to 2030 and said Starlink could someday carry a majority of the world’s internet. What the all hands video adds is a hard deadline and a specific power figure Musk had not given publicly before, along with a franker pitch to his own workforce that AI, not launch cadence, is now the thing SpaceX is betting its future on.
The AI revenue itself is not coming from SpaceX training its own models. It is largely Starlink acting as the network layer for xAI’s workloads, plus SpaceX renting out compute capacity directly, the same approach behind the roughly $16 billion the company spent on AI infrastructure in a single quarter.
Musk closed the video with a pitch aimed at recruiting and retention rather than investors, telling employees that anyone who helps SpaceX win the AI race will eventually get the chance to go to the moon or Mars themselves. Whether SpaceX can turn 1.4 gigawatts into 10 in seventeen months is the more immediate question, and one that will show up in quarterly numbers well before anyone leaves Earth.
Investor's Corner
Tesla has one big financial question to answer for investors: Morgan Stanley
In a new note to investors on Tuesday, Morgan Stanley analyst Andrew Percoco said that Tesla has one big financial question to answer for investors regarding its Robotaxi rollout, Full Self-Driving software, and Optimus.
Percoco said in the note that, for the most part, investors are still very positive about the direction the company is headed. However, there are some things the firm would like to see, and they have to do with financials.
Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue
Tesla bulls are more than convinced that the company’s Full Self-Driving software is proof it can develop physical AI. Financially, however, there are still some questions, especially on elevated spending, which CEO Elon Musk said would occur as the company works to roll out Robotaxi faster and continue developing its Optimus robot.
The latter two are where Tesla will have to prove progress to investors, as Percoco writes that both projects “will require clearer evidence that Robotaxi is scaling and more tangible Optimus proof points to support the ROI on elevated capex.”
Percoco said the second quarter earnings call did not change his long-term thesis of where Tesla is positioned in the AI race, which is out in front. However, there are concerns that weaker gross margins and higher R&D spend will stress financials, and that has “sharpened our (and investors’) focus on measurable progress across Robotaxi and Optimus.”
Additionally, Robotaxi still needs to be proven with more operation in existing cities while maintaining safety but improving how many rides it gives in any given time, he said. For Optimus, Percoco wrote that he is “still looking for evidence beyond commentary around SOP.”
Morgan Stanley put Percoco in charge of covering Tesla after long-time analyst Adam Jonas transitioned to the automotive side.
Currently, Morgan Stanley has a $415 price target on Tesla and a ‘Hold’ rating on the stock. It is trading at around $330 at the time of publication, which was 2:30 P.M. on the East Coast.
Investor's Corner
SpaceX AI investment gamble will make it a big winner, firm says
SpaceX’s massive investment in AI will make it a big winner, Argus Research said after the company’s successful earnings call last week.
The firm also upgraded shares to a Buy from Hold and set a $160 price target.
SpaceX (NASDAQ: SPCX) is currently recovering from its heavy AI infrastructure investments, as it spent nearly $16 billion in Q2 alone. The company did this primarily by monetizing high-demand GPU compute capacity at a much faster pace than traditional data center economics would suggest.
Company CFO Bret Johnsen said that SpaceX would be able to pay back anything on new deployments within a year.
There are plenty of ways the company can do this:
Leasing excess compute capacity through contracts
SpaceX has already built Colossus and Colossus II, largely for its own model training. However, much of that capacity is already rented out to third parties. It already has major deals with Anthropic, Google, and Reflection AI. These partnerships are adding billions per month to SpaceX’s spreadsheet.
High utilization driven by industry-wide scarcity
The demand for advanced AI training and inference capacity continues to exceed what is available for use. SpaceX can fill new racks quickly after they come online, so the capital deployed converts into revenue with minimal idle time.
Additionally, management and outside observers have described the new compute capital as behaving more like a cost-of-goods-sold than traditional multi-year capex, especially because of this rapid monetization pattern.
Capacity has already scaled from ~0.4 GW a year to 1.4 GW annually by the end of Q2. There are targets of more than 2 GW by year-end.
High incremental margins on the rental business once capacity is online
GPU cloud providers often operate at strong gross margins. SpaceX can monetize capacity that was already partially built or can be added efficiently. This means that incremental EBITDA margins on the rental revenue are usually high. This accelerates cash recovery relative to the gross capital outlay.
Parallel monetization of its own AI software and applications
Beyond pure infrastructure rental, SpaceX also generates revenue from Grok through subscriptions and usage, from X through ads, data, and other related services, enterprise APIs, and the planned integration of the Cursor coding tools acquisition.
These application layers ride on the same compute infrastructure and provide additional high-margin streams that could offset build-out costs. AI-segment revenue overall rose sharply to about $2.6 billion in Q2, according to Motley Fool. This was driven primarily by the infrastructure contracts, but the software side is also partially responsible.
Efficient, large-scale deployment and vertical integration advantages
SpaceX has emphasized the rapid construction of power and cooling infrastructure and favorable cost-per-megawatt economics relative to industry benchmarks in some disclosures.
Combined with its ability to scale capacity aggressively and the fact that many contracts start generating revenue within months of capacity coming online, the effective payback compresses dramatically compared with more conventional multi-year data-center projects.
SpaceX’s dominant near-term recovery path will turn the AI clusters into a hyperscale-style compute rental business for other leading AI companies while still using a portion for internal models.