News
SpaceX Starship booster survives record-breaking 31-engine static fire
SpaceX’s Starship rocket has survived a record-breaking engine test – potentially the most powerful static fire in the history of rocketry.
According to CEO Elon Musk, Super Heavy Booster 7 (B7) ultimately ignited 31 of its 33 Raptor engines. One engine was manually disabled “just before” the static fire, while the other faulty engine automatically shut down while attempting to ignite. The other 31 Raptors, however, completed a “full duration” static fire that lasted about five seconds. Musk says that even with two engines disabled, those that remained were “still enough…to reach orbit” – an excellent result despite the static fire’s imperfections.
Most importantly, Super Heavy Booster 7 survived the test without catching fire, exploding, or popping its tanks. To partially counteract the thrust of its Raptor engines, the rocket’s tanks were filled with some 3000 tons (6.6M lbs) of liquid oxygen and methane propellant. The stool-like orbital launch mount (OLM), which also survived the test in one piece, held Starship down with 20 clamps to counteract any remaining thrust. From SpaceX’s perspective, the fact alone that its only orbital-class Starship launch site survived the ordeal is likely enough for it to consider the static fire a success. But the test was much more than that.
The update that's rolling out to the fleet makes full use of the front and rear steering travel to minimize turning circle. In this case a reduction of 1.6 feet just over the air— Wes (@wmorrill3) April 16, 2024
Incinerating rocket records
Despite losing two Raptors, SpaceX still broke the all-time record for the number of rocket engines ignited simultaneously. That record was held by the Soviet N1 rocket, which launched four times with 30 NK-15 engines in the late 1960s and early 1970s. None of its test flights were successful, but N1 still set the record for the most thrust produced by a single rocket, generating up to 4500 tons (9.9M lbf) of thrust at liftoff.
Neither SpaceX nor CEO Elon Musk has confirmed it, reducing the odds that Super Heavy Booster 7 broke that historic thrust record. But it certainly could have. Each Raptor 2 engine can generate up to 230 tons (507,000 lbf) of thrust at sea level. Raptor is theoretically designed to throttle as low as 40%, or 92 tons (~200,000 lbf) of thrust. With 33 engines operating nominally at their minimum throttle setting, Super Heavy would have produced 3036 tons (~6.7M lbf) of thrust during today’s static fire – not a record.
For 31 Raptors to break N1’s thrust record, the average throttle setting would have had to be around 64% or higher – far from unreasonable. From a data-gathering perspective, a full-thrust static fire would be the most valuable 33-engine test SpaceX could attempt, but it would also be the riskiest and most stressful for the rocket and pad.
Former SpaceX executive Tom Mueller says that SpaceX broke N1’s record. Mueller is effectively the father of the Raptor engine, and likely still gets information straight from SpaceX engineers he used to work with. Still, one would expect SpaceX itself to proudly confirm as much if a rocket it built became the most powerful in history.
The most powerful rocket test in history?
Whether or not Starship became the most powerful rocket in history, it has likely become the most powerful rocket ever tested on the ground. The first stage of Saturn V produced around 3400 tons (7.5M lbf) of thrust during its first sea-level static fire in 1965. Likely contributing to its failure, N1’s booster was never static-fired. Other powerful rockets like the Space Shuttle and SLS use or used a combination of solid rocket boosters and liquid engines that cannot be tested together on the ground.
Unless SpaceX’s goal was a minimum-throttle static fire, Starship’s 31-Raptor static fire likely beat Saturn V’s record to become the most powerful ground test in the history of rocketry.
SpaceX’s next steps
While the 31 that did ignite appeared to perform about as well as SpaceX could have hoped, the two engines missing from February 9th’s historic Starship static fire have probably complicated the company’s next steps. To be fully confident in Starship’s ability to launch and fly a safe distance away from the launch site, SpaceX would likely need to complete a full 33-engine test. Meanwhile, Starship can’t fly until the Federal Aviation Administration approves a launch license, and the FAA could be stodgy enough to deny SpaceX a license without a perfect 33-engine static fire.
Alternatively, the FAA may accept that Starship could still safely launch and reach orbit while missing several Raptors. SpaceX could also guarantee that it will only allow Starship to lift off if all 33 engines are active, in which case a second 33-engine static fire attempt may not be necessary.
If SpaceX is happy with Booster 7’s 31-engine test results and isn’t too put off by any pad damage the test may or may not have caused, it will likely focus on finishing Starship 24. Ship 24 will then be transported back to the pad and reinstalled on top of Booster 7. SpaceX may choose to conduct another wet dress rehearsal or a static fire with the fully-stacked Starship, but it may also deem additional testing unnecessary.
Once all those tasks are completed, Ship 24 and Booster 7 will be ready to support Starship’s first orbital launch attempt. Prior to February 9th’s static fire, SpaceX CEO Elon Musk and COO/President Gwynne Shotwell agreed that Starship’s orbital launch debut could happen as early as March 2023. After today’s test, a March 2023 launch may be within reach.
Rewatch Super Heavy Booster 7’s historic static fire below.
News
Nvidia CEO Jensen Huang explains difference between Tesla FSD and Alpamayo
“Tesla’s FSD stack is completely world-class,” the Nvidia CEO said.
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.
“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.”
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.
Elon Musk
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.
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.”
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.
Elon Musk
Elon Musk’s xAI closes upsized $20B Series E funding round
xAI announced the investment round in a post on its official website.
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.”
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.
Nvidia CEO Jensen Huang explains difference between Tesla FSD and Alpamayo
Elon Musk confirms xAI’s purchase of five 380 MW natural gas turbines
