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SpaceX’s upgraded Starship completes second Raptor engine test in ~24 hours

SpaceX has fired up Starship SN15 for the second time in ~24 hours. (NASASpaceflight.com)

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SpaceX Starship prototype SN15 has completed a second ‘static fire’ test of its Raptor engines in the last 24 hours, hopefully setting up the rocket for a launch and landing attempt on Thursday or Friday.

While Monday’s test was a total success, it’s unclear if April 27th’s static fire went according to plan. Notably, it was much shorter than the Monday engine test and involved either one or two – but not all three – of Starship SN15’s Raptor engines. Historically, unusually brief static fires (~2-3 seconds) aren’t unprecedented, but they’ve generally been part of a process of troubleshooting after a prototype runs into technical issues during earlier testing.

According to Musk, SpaceX also moved to reigniting all three sea level Raptors for landing burns from Starship SN10 onwards, meaning that an intentional two-engine SN15 static fire is either a reversion to earlier two-engine landing burns or a sign of a static fire abort or engine ignition failure. If SpaceX needs to perform another test, particularly if one or more Raptors need to be replaced, Starship SN15’s launch will likely slip into early May. Stay tuned for updates.

SpaceX CEO Elon Musk says that the next Starship launch could happen “later this week” after the company’s first ‘upgraded’ prototype aced a three-engine static fire test on the first try.

While substantially delayed from optimistic initial targets just a week or two after the rocket rolled from factory to launch pad, upgraded Starship prototype serial number 15 (SN15) – outfitted with “hundreds of improvements” – fired up its three Raptor engines for a few seconds around 5pm CDT on Monday, April 26th. Also upgraded, the rocket’s engines seemed to perform nominally and SpaceX ultimately closed out the evening’s testing a few hours early.

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Around the same time as SN15’s first static fire attempt was wrapping up, SpaceX distributed safety notices to Boca Chica Village residents, indicating that a second static fire test may be planned on Tuesday. Musk didn’t mention plans for a second static fire, but he did imply that the first test was completed successfully enough to enable Starship SN15 to launch just a few days from now.

Like four other “high-altitude” flight tests before it, Starship SN15 is expected to target a similar ~10-12 kilometer (6-8 mi) apogee and once again attempt to perform a complete ascent, controlled bellyflop, landing flip maneuver, and soft touchdown. Between December 2020 and April 2021, Starships SN8 through SN11 tried and failed to survive that challenge intact, though prototype SN10 did manage to survive for around ten minutes on the ground before its still-hard landing led to an explosion.

All four failures ultimately had different causes. Starship SN8 lost fuel tank pressure, starving its Raptors and causing a near-total loss of thrust seconds before touchdown. One of SN9’s Raptors failed to ignite for a landing burn, triggering an even more aggressive impact with the ground. Starship SN10 landed in one piece but its lone landing engine underperformed when it began to ingest helium ullage gas – a quick-fix implemented after SN8’s pressurization issue. SN11 exploded almost immediately after attempting to ignite its three engines for landing, failing even earlier than its predecessors.

All four flight tests saw each respective Starship prototypes narrowly miss a fully successful and survivable landing, providing SpaceX a great deal of data and direct experience to improve the rocket’s design and operations with. Two of the four failures – SN9 and SN11 – appear to have been the fault of one or more of Starship’s three Raptor engines. Beginning with Starship SN15, SpaceX has moved to an upgraded iteration of the next-generation engine, raising hopes that whatever changes the company has implemented will substantially improve reliability and thus the odds of a successful high-altitude launch and landing test.

As of April 26th and in spite of one or two weeks of delays, the fact that Starship SN15 managed to complete a three-Raptor static fire test on its first true attempt is a great sign that the rocket’s many “improvements” may already be paying dividends. A launch “later this week” would make the effects of those improvements even harder to deny. A successful launch and landing in the next few days would all but guarantee that SpaceX’s process of iterative development is working like a charm. Regardless of whether SN15 survives its first flight, Starship SN16 will likely be ready to take over a matter of days later.

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Eric Ralph is Teslarati's senior spaceflight reporter and has been covering the industry in some capacity for almost half a decade, largely spurred in 2016 by a trip to Mexico to watch Elon Musk reveal SpaceX's plans for Mars in person. Aside from spreading interest and excitement about spaceflight far and wide, his primary goal is to cover humanity's ongoing efforts to expand beyond Earth to the Moon, Mars, and elsewhere.

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Nvidia CEO Jensen Huang explains difference between Tesla FSD and Alpamayo

“Tesla’s FSD stack is completely world-class,” the Nvidia CEO said.

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Credit: Grok Imagine

NVIDIA CEO Jensen Huang has offered high praise for Tesla’s Full Self-Driving (FSD) system during a Q&A at CES 2026, calling it “world-class” and “state-of-the-art” in design, training, and performance. 

More importantly, he also shared some insights about the key differences between FSD and Nvidia’s recently announced Alpamayo system. 

Jensen Huang’s praise for Tesla FSD

Nvidia made headlines at CES following its announcement of Alpamayo, which uses artificial intelligence to accelerate the development of autonomous driving solutions. Due to its focus on AI, many started speculating that Alpamayo would be a direct rival to FSD. This was somewhat addressed by Elon Musk, who predicted that “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.”

During his Q&A, Nvidia CEO Jensen Huang was asked about the difference between FSD and Alpamayo. His response was extensive:

“Tesla’s FSD stack is completely world-class. They’ve been working on it for quite some time. It’s world-class not only in the number of miles it’s accumulated, but in the way it’s designed, the way they do training, data collection, curation, synthetic data generation, and all of their simulation technologies. 

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“Of course, the latest generation is end-to-end Full Self-Driving—meaning it’s one large model trained end to end. And so… Elon’s AD system is, in every way, 100% state-of-the-art. I’m really quite impressed by the technology. I have it, and I drive it in our house, and it works incredibly well,” the Nvidia CEO said. 

Nvidia’s platform approach vs Tesla’s integration

Huang also stated that Nvidia’s Alpamayo system was built around a fundamentally different philosophy from Tesla’s. Rather than developing self-driving cars itself, Nvidia supplies the full autonomous technology stack for other companies to use.

“Nvidia doesn’t build self-driving cars. We build the full stack so others can,” Huang said, explaining that Nvidia provides separate systems for training, simulation, and in-vehicle computing, all supported by shared software.

He added that customers can adopt as much or as little of the platform as they need, noting that Nvidia works across the industry, including with Tesla on training systems and companies like Waymo, XPeng, and Nuro on vehicle computing.

“So our system is really quite pervasive because we’re a technology platform provider. That’s the primary difference. There’s no question in our mind that, of the billion cars on the road today, in another 10 years’ time, hundreds of millions of them will have great autonomous capability. This is likely one of the largest, fastest-growing technology industries over the next decade.”

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He also emphasized Nvidia’s open approach, saying the company open-sources its models and helps partners train their own systems. “We’re not a self-driving car company. We’re enabling the autonomous industry,” Huang said.

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Elon Musk confirms xAI’s purchase of five 380 MW natural gas turbines

The deal, which was confirmed by Musk on X, highlights xAI’s effort to aggressively scale its operations.

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Credit: xAI/X

xAI, Elon Musk’s artificial intelligence startup, has purchased five additional 380 MW natural gas turbines from South Korea’s Doosan Enerbility to power its growing supercomputer clusters. 

The deal, which was confirmed by Musk on X, highlights xAI’s effort to aggressively scale its operations.

xAI’s turbine deal details

News of xAI’s new turbines was shared on social media platform X, with user @SemiAnalysis_ stating that the turbines were produced by South Korea’s Doosan Enerbility. As noted in an Asian Business Daily report, Doosan Enerbility announced last October that it signed a contract to supply two 380 MW gas turbines for a major U.S. tech company. Doosan later noted in December that it secured an order for three more 380 MW gas turbines.

As per the X user, the gas turbines would power an additional 600,000+ GB200 NVL72 equivalent size cluster. This should make xAI’s facilities among the largest in the world. In a reply, Elon Musk confirmed that xAI did purchase the turbines. “True,” Musk wrote in a post on X. 

xAI’s ambitions 

Recent reports have indicated that xAI closed an upsized $20 billion Series E funding round, exceeding the initial $15 billion target to fuel rapid infrastructure scaling and AI product development. The funding, as per the AI startup, “will accelerate our world-leading infrastructure buildout, enable the rapid development and deployment of transformative AI products.”

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The company also teased the rollout of its upcoming frontier AI model. “Looking ahead, Grok 5 is currently in training, and we are focused on launching innovative new consumer and enterprise products that harness the power of Grok, Colossus, and 𝕏 to transform how we live, work, and play,” xAI wrote in a post on its website. 

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Elon Musk’s xAI closes upsized $20B Series E funding round

xAI announced the investment round in a post on its official website. 

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Credit: xAI

xAI has closed an upsized $20 billion Series E funding round, exceeding the initial $15 billion target to fuel rapid infrastructure scaling and AI product development. 

xAI announced the investment round in a post on its official website. 

A $20 billion Series E round

As noted by the artificial intelligence startup in its post, the Series E funding round attracted a diverse group of investors, including Valor Equity Partners, Stepstone Group, Fidelity Management & Research Company, Qatar Investment Authority, MGX, and Baron Capital Group, among others. 

Strategic partners NVIDIA and Cisco Investments also continued support for building the world’s largest GPU clusters.

As xAI stated, “This financing will accelerate our world-leading infrastructure buildout, enable the rapid development and deployment of transformative AI products reaching billions of users, and fuel groundbreaking research advancing xAI’s core mission: Understanding the Universe.”

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xAI’s core mission

Th Series E funding builds on xAI’s previous rounds, powering Grok advancements and massive compute expansions like the Memphis supercluster. The upsized demand reflects growing recognition of xAI’s potential in frontier AI.

xAI also highlighted several of its breakthroughs in 2025, from the buildout of Colossus I and II, which ended with over 1 million H100 GPU equivalents, and the rollout of the Grok 4 Series, Grok Voice, and Grok Imagine, among others. The company also confirmed that work is already underway to train the flagship large language model’s next iteration, Grok 5. 

“Looking ahead, Grok 5 is currently in training, and we are focused on launching innovative new consumer and enterprise products that harness the power of Grok, Colossus, and 𝕏 to transform how we live, work, and play,” xAI wrote. 

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