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SpaceX rocket catch simulation raises more questions about concept

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CEO Elon Musk has published the first official visualization of what SpaceX’s plans to catch Super Heavy boosters might look like in real life. However, the simulation he shared raises just as many questions as it answers.

Since at least late 2020, SpaceX CEO Elon Musk has been floating the idea of catching Starships and Super Heavy boosters out of the sky as an alternative to having the several-dozen-ton steel rockets use basic legs to land on the ground. This would be a major departure from SpaceX’s highly successful Falcon family, which land on a relatively complex set of deployable legs that can be retracted after most landings. The flexible, lightweight structures have mostly been reliable and easily reusable but Falcon boosters occasionally have rough landings, which can use up disposable shock absorbers or even damage the legs and make boosters hard to safely recover and slower to reuse.

As a smaller rocket, Falcon boosters have to be extremely lightweight to ensure healthy payload margins and likely weigh about 25-30 tons empty and 450 tons fully fueled – an excellent mass ratio for a reusable rocket. While it’s still good to continue that practice of rigorous mass optimization with Starship, the vehicle is an entirely different story. Once plans to stretch the Starship upper stage’s tanks and add three more Raptors are realized, it’s quite possible that Starship will be capable of launching more than 200 tons (~440,000 lb) of payload to low Earth orbit (LEO) with ship and booster recovery.

One might think that SpaceX, with the most capable rocket ever built potentially on its hands, would want to take advantage of that unprecedented performance to make the rocket itself – also likely to be one of the most complex launch vehicles ever – simpler and more reliable early on in the development process. Generally speaking, that would involve sacrificing some of its payload capability and adding systems that are heavier but simpler and more robust. Once Starship is regularly flying to orbit and gathering extensive flight experience and data, SpaceX might then be able refine the rocket, gradually reducing its mass and improving payload to orbit by optimizing or fully replacing suboptimal systems and designs.

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Instead, SpaceX appears to be trying to substantially optimize Starship before it’s attempted a single orbital launch. The biggest example is Elon Musk’s plan to catch Super Heavy boosters – and maybe Starships, too – for the sole purpose of, in his own words, “[saving] landing leg mass [and enabling] immediate reflight of [a giant, unwieldy rocket].” Musk, SpaceX executives, or both appear to be attempting to refine a rocket that has never flown. Further, based on a simulation of a Super Heavy “catch” Musk shared on January 20th, all that oddly timed effort may end up producing a solution that’s actually worse than what it’s trying to replace.

Based on the simulated telemetry shown in the visualization, Super Heavy’s descent to the landing zone appears to be considerably gentler than the ‘suicide burn’ SpaceX routinely uses on Falcon. By decelerating as quickly as possible and making landing burns as short as possible, Falcon saves a considerable amount of propellant during recovery – extra propellant that, if otherwise required, would effectively increase Falcon’s dry mass and decrease its payload to orbit. In the Super Heavy “catch” Musk shared, the booster actually appears to be landing – just on an incredibly small patch of steel on the tower’s ‘Mechazilla’ arms instead of a concrete pad on the ground.

Aside from a tiny bit of lateral motion, the arms appear motionless during the ‘catch,’ making it more of a landing. Further, Super Heavy is shown decelerating rather slowly throughout the simulation and appears to hover for almost 10 seconds near the end. That slow, cautious descent and even slower touchdown may be necessary because of how incredibly accurate Super Heavy has to be to land on a pair of hardpoints with inches of lateral margin for error and maybe a few square feet of usable surface area. The challenge is a bit like if SpaceX, for some reason, made Falcon boosters land on two elevated ledges about as wide as car tires. Aside from demanding accurate rotational control, even the slightest lateral deviation would cause the booster to topple off the pillars and – in the case of Super Heavy – fall about a hundred feet onto concrete, where it would obviously explode.

What that slow descent and final hover mean is that the Super Heavy landing shown would likely cost significantly more delta V (propellant) than a Falcon-style suicide burn. Propellant has mass, so Super Heavy would likely need to burn at least 5-10 tons more to carefully land on arms that aren’t actively matching the booster’s position and velocity. Ironically, SpaceX could probably quite easily add rudimentary, fixed legs – removing most of the bad aspects of Falcon legs – to Super Heavy with a mass budget of 10 tons. But even if SpaceX were to make those legs as simple, dumb, and reliable as physically possible and they wound up weighing 20 tons total, the inherent physics of rocketry mean that adding 20 tons to Super Heavy’s likely 200-ton dry mass would only reduce the rocket’s payload to orbit by about 3-5 tons or 1-3%.

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Further, per Musk’s argument that landing on the arms would enhance the speed of reuse, it’s difficult to see how landing Super Heavy or Starship in the exact same corridor – but on the ground instead of on the arms – would change anything. If Super Heavy is accurate enough to land on a few square meters of steel, it must inherently be accurate enough to land within the far larger breadth of those arms. The only process landing on the arms would clearly remove is reattaching the arms to a landed booster or ship, which it’s impossible to imagine would save more than a handful of minutes or maybe an hour of work. SpaceX’s Falcon booster turnaround record is currently 27 days, so it’s even harder to imagine why SpaceX would be worrying about cutting minutes or a few hours off of the turnaround and reuse of a rocket that has never even performed a full static fire test – let alone attempted an orbital-class launch, reentry, or landing.

Put simply, while Starbase’s launch tower arms will undoubtedly be useful for quickly lifting and stacking Super Heavy and Starship, it’s looking more and more likely that using those arms as a landing platform will, at best, be an inferior alternative to basic Falcon-style landings. More importantly, even if everything works perfectly, the arms actually cooperate with boosters to catch them, and it’s possible for Super Heavy to avoid hovering and use a more efficient suicide burn, the apparent best-case outcome of all that effort is marginally faster reuse and perhaps a 5% increase in payload to orbit. Only time will tell if such a radical change proves to be worth such marginal benefits.

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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Elon Musk

Tesla confirmed HW3 can’t do Unsupervised FSD but there’s more to the story

Tesla confirmed HW3 vehicles cannot run unsupervised FSD, replacing its free upgrade promise with a discounted trade-in.

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tesla autopilot

Tesla has officially confirmed that early vehicles with its Autopilot Hardware 3 (HW3) will not be capable of unsupervised Full Self-Driving, while extending a path forward for legacy owners through a discounted trade-in program. The announcement came by way of Elon Musk in today’s Tesla Q1 2026 earnings call.

The history here matters. HW3 launched in April 2019, and Tesla sold Full Self-Driving packages to owners on the understanding that the hardware was sufficient for full autonomy. Some owners paid between $8,000 and $15,000 for FSD during that period. For years, as FSD’s AI models grew more demanding, HW3 vehicles fell progressively further behind, eventually landing on FSD v12.6 in January 2025 while AI4 vehicles moved to v13 and then v14. When Musk acknowledged in January 2025 that HW3 simply could not reach unsupervised operation, and alluded to a difficult hardware retrofit.

The near-term offering is more concrete. Tesla’s head of Autopilot Ashok Elluswamy confirmed on today’s call that a V14-lite will be coming to HW3 vehicles in late June, bringing all the V14 features currently running on AI4 hardware. That is a meaningful software update for owners who have been frozen at v12.6 for over a year, and it represents genuine effort to keep older hardware relevant. Unsupervised FSD for vehicles is now targeted for Q4 2026 at the earliest, with Musk describing it as a gradual, geography-limited rollout.

For HW3 owners, the over-the-air V14-lite update is welcomed, and the discounted trade-in path at least acknowledges an old obligation. What happens next with the trade-in pricing will define how this chapter ultimately gets written. If Tesla prices the hardware path fairly, acknowledges what early adopters are owed, and delivers V14-lite on the June timeline it committed to today, it has a real opportunity to convert one of the longest-running sore subjects among early adopters into a loyalty story.

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Elon Musk

Tesla isn’t joking about building Optimus at an industrial scale: Here we go

Tesla’s Optimus factory in Texas targets 10 million robots yearly, with 5.2 million square feet under construction.

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Tesla’s Q1 2026 Update Letter, released today, confirms that first generation Optimus production lines are now well underway at its Fremont, California factory, with a pilot line targeting one million robots per year to start. Of bigger note is a shared aerial image of a large piece of land adjacent to Gigafactory Texas, that Tesla has prominently labeled “Optimus factory site preparation.”

Permit documents show Tesla is seeking to add over 5.2 million square feet of new building space to the Giga Texas North Campus by the end of 2026, at an estimated construction investment of $5 billion to $10 billion. The longer term production target for that facility is 10 million Optimus units per year. Giga Texas already sits on 2,500 acres with over 10 million square feet of existing factory floor, and the North Campus expansion is being built to support multiple projects, including the dedicated Optimus factory, the Terafab chip fabrication facility (a joint Tesla/SpaceX/xAI venture), a Cybercab test track, road infrastructure, and supporting facilities.

Credit: TESLA

Texas makes strategic sense beyond the existing infrastructure. The state’s tax structure, lower labor costs relative to California, and the proximity to Tesla’s AI training cluster Cortex 1 and 2, both located at Giga Texas and now totaling over 230,000 H100 equivalent GPUs, means the Optimus software stack and the factory producing the hardware will share the same campus. Tesla’s Q1 report also confirmed completion of the AI5 chip tape out in April, the inference processor designed specifically to power Optimus units in the field.

As Teslarati reported, the Texas facility is intended to house Optimus V4 production at full scale. Musk told the World Economic Forum in January that Tesla plans to sell Optimus to the public by end of 2027 at a price between $20,000 and $30,000, stating, “I think everyone on earth is going to have one and want one.” He has previously pegged long term demand for general purpose humanoid robots at over 20 billion units globally, citing both consumer and industrial use cases.

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Investor's Corner

Tesla (TSLA) Q1 2026 earnings results: beat on EPS and revenues

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Credit: Tesla

Tesla (NASDAQ: TSLA) reported its earnings for the first quarter of 2026 on Wednesday afternoon. Here’s what the company reported compared to what Wall Street analysts expected.

The earnings results come after Tesla reported a miss on vehicle deliveries for the first quarter, delivering 358,023 vehicles and building 408,386 cars during the three-month span.

As Tesla transitions more toward AI and sees itself as less of a car company, expectations for deliveries will begin to become less of a central point in the consensus of how the quarter is perceived.

Nevertheless, Tesla is leaning on its strong foundation as a car company to carry forward its AI ambitions. The first quarter is a good ground layer for the rest of the year.

Tesla Q1 2026 Earnings Results

Tesla’s Earnings Results are as follows:

  • Non-GAAP EPS – $0.41 Reported vs. $0.36 Expected
  • Revenues – $22.387 billion vs. $22.35 billion Expected
  • Free Cash Flow – $1.444 billion
  • Profit – $4.72 billion

Tesla beat analyst expectations, so it will be interesting to see how the stock responds. IN the past, we’ve seen Tesla beat analyst expectations considerably, followed by a sharp drop in stock price.

On the same token, we’ve seen Tesla miss and the stock price go up the following trading session.

Tesla will hold its Q1 2026 Earnings Call in about 90 minutes at 5:30 p.m. on the East Coast. Remarks will be made by CEO Elon Musk and other executives, who will shed some light on the investor questions that we covered earlier this week.

You can stream it below. Additionally, we will be doing our Live Blog on X and Facebook.

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