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SpaceX’s first Starship test flight imminent as rocket nosecone nears completion

CEO Elon Musk has published the latest glimpse inside SpaceX's South Texas Starship rocket factory. (Elon Musk)

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Elon Musk has posted a new glimpse inside SpaceX’s South Texas Starship factory, revealing a nearly-completed rocket nosecone and indicating that the first upgraded Starship prototype’s flight debut is imminent.

SpaceX teams have been working around the clock for a little over a month to build the first full-scale, flightworthy Starship prototype, a process that only began after two ‘test tanks’ were fabricated, assembled, and pressurized until they burst on January 10th and 28th. Built with improved tools and methods, those test results – particularly from the second test tank – allowed SpaceX to empirically confirm that its current infrastructure and techniques are ready to manufacture orbital-class (and even human-rated) Starships right now.

And so work on the first truly flightworthy Starship prototype – known as SN01 (serial number 01) – thus began in earnest around mid-January, perhaps less than a month ago. Over the course of that month, SpaceX’s South Texas team has made spectacular progress. Starship SN01’s business half – comprised of a Raptor engine section, a liquid oxygen tank, a methane tank, and all associated tank domes and plumbing – is likely just a single big stacking and welding event away from being structurally complete. The upper section of the prototype – Starship’s curved nose and a few less-critical steel rings – has, however, been a bit more elusive.

Aside from a few partial glimpses earlier this month, that nose appeared for the first time two or so weeks on a local resident’s livestream earlier today – just a few hours before Musk offered an even better view inside the same tent it was spotted in. Situated in the second large sprung structure erected at SpaceX’s Boca Chica, Texas facilities, Musk’s video revealed that that tent – really only completed less than two weeks ago – is already full of Starship production hardware.

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An almost identical tent shown off on February 8th appears to be more dedicated to Starship tank production, while the second tent (top, February 19th) is focused primarily on Starship nose section production. (Elon Musk)

Without exaggerating, it’s safe to say that SpaceX has effectively gone from a handful of parts worth of Texas rocket production to a multi-vehicle, Starship production line concurrently manufacturing multiple vehicles in about eight weeks. While it would be theoretically easy for critics and a more general audience to see little more than some cheap stainless steel parts in a few hastily-constructed temporary tents, the reality is that SpaceX has already proven – at a minimum – that a steel Starship built with the exact same tools, facilities, and methods will likely be capable of spaceflight.

SpaceX’s January 2020 Starship test tank program proved as much, demonstrating that thin steel tanks built in tents can serve as orbital-class pressure vessels and survive at internal pressures greater as high as 8.5 bar (125 psi) while filled with cryogenic (extremely cold) liquid. Meanwhile, Tesla’s Fremont factory General Assembly line 4 (GA4) – having continuously churned out high-quality Model 3s for more than a year – has proven that sprung structures can make for fast, cheap, and more or less permanent factory solutions. Prospective SpaceX competitor Blue Origin even based its own brand new headquarters – opened in January 2020 – around an odd U-shaped sprung structure.

SpaceX’s first and second Starship test tanks pictured on January 9th and January 28th. (NASASpaceflight – bocachicagal)
Erected in less than two months, SpaceX’s twin-sprung-structure Starship factory represents some 80,000 ft² (7000 m²) of enclosed factory space. (NASASpaceflight – bocachicagal)

Nevertheless, SpaceX’s small test tank successes do not necessarily guarantee that the same kind of tests performed at full scale will be equally successful. The biggest proof of concept for SpaceX’s upgraded Starship production methods will involve manufacturing, fueling, static-firing, and – eventually – flying a complete Starship prototype built with the same methods as those test tanks.

The pressure vessel section of Starship SN01 – said pathfinder prototype – appears to be nearly complete, missing only its integrated engine section and oxygen tank dome before it could theoretically be ready to start cryogenic testing. Incredibly, information acquired and published by NASASpaceflight.com reporter Michael Baylor indicates that SpaceX wants to complete the prototype and transport Starship to its nearby launch site just ten days from now.

Starship SN01’s tank and engine section is likely just a few days away from being structurally complete. (SPadre – 02/17/20)

A step further, if things go as planned, SpaceX wants to install Starship SN01’s three Raptor engines and perform a live static fire test as soon as early March. In short, SpaceX’s Starship program is likely about to enter a new period of ambitious, rapid-fire testing. Stay tuned!

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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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SpaceX confirms third massive compute deal at Colossus data center

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Credit: xAI Memphis

SpaceX confirmed today that it has officially signed its third massive compute deal, providing compute at its Colossus data center in Southaven, Tennessee.

Reflection AI will gain immediate access to NVIDIA GB300 chips at SpaceX’s Colossus 2 data center. In return, Reflection will pay SpaceX $150 million per month starting on July 1, with total payments reaching approximately $6.3 billion if the contract runs through its duration, which is until 2029. Either party can terminate the agreement with 90 days’ notice after the initial three-month period.

CNBC first reported the deal.

This latest partnership highlights SpaceX’s strategy of commercializing its massive Colossus supercomputing infrastructure, originally developed to power Elon Musk’s Grok AI models. The company has rapidly expanded its customer base in the AI sector following its February 2026 merger with xAI, a transaction that valued the combined entity at $1.25 trillion.

SpaceX has previously signed significant compute deals with other major players.

It granted Anthropic exclusive access to the full capacity of its Colossus 1 data center, which exceeds 300 megawatts and includes over 220,000 NVIDIA GPUs. Details from SpaceX’s IPO filings indicate Anthropic will pay $1.25 billion per month through May 2029, potentially generating around $45 billion over the term of the deal.

Additionally, Google agreed to pay SpaceX $920 million per month for compute capacity from October 2026 through June 2029. This 32-month period will provide Google access to roughly 110,000 NVIDIA GPUs, along with supporting processors and memory. Capacity ramps up through September at a reduced fee, with termination options after the first year.

SpaceXA also established arrangements for computing power with Cursor, an AI coding startup. SpaceX acquired them in a $60 billion all-stock deal.

SpaceX makes first acquisition post-IPO

These arrangements position SpaceX’s collective position as an AI infrastructure powerhouse with high-margin revenue potential. The Google deal alone could generate nearly $29.5 billion over its term, while the Reflection contract adds another $6.3 billion.

Combined with the Anthropic arrangement, SpaceX stands to realize tens of billions in revenue from compute leasing in the coming years, which diversifies beyond SpaceX’s traditional rocket launches and Starlink operation.

The deals underscore growing demand for advanced AI training and inference capacity amid chip shortages and surging model development needs. Reflection, valued at $25 billion and focused on “American open intelligence” with government and national security ties, cited recent restrictions on closed models as validation for open-source approaches.

For SpaceX, the partnerships transform capital-intensive data centers into flexible revenue sources while supporting its broader AI ambitions after the company has gone public.

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Elon Musk responds to SpaceX’s ESG rating and says its rockets won’t go electric

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(Credit: SpaceX)

It is safe to say SpaceX won’t be going for electric rockets anytime soon.

In a characteristically blunt reply on X, SpaceX frontman Elon Musk stated, “Unfortunately, electric rockets are impossible,” following reports that MSCI had assigned SpaceX its lowest possible ESG rating of CCC.

The assessment, issued just this past week, coinciding closely with SpaceX’s public market debut, placed the company on par with nations like Russia in sustainability scoring and cited significant risks in environmental, social, and governance areas.

MSCI flagged SpaceX’s exposure to rocket emissions and other operational impacts, alongside governance concerns such as concentrated control by Musk and limited shareholder protections. Musk’s terse comment directly addressed the environmental pillar, underscoring a core physical constraint that ESG frameworks often overlook when evaluating high-thrust industries.

Electric propulsion systems do exist and are widely used in space. Ion thrusters and Hall-effect thrusters accelerate ionized propellant, typically xenon or krypton, using electric fields, achieving very high specific impulse, often exceeding 3,000 seconds compared to roughly 300–450 seconds for chemical rockets.

This efficiency makes them ideal for satellite station-keeping, orbit raising, and deep-space missions where low thrust over long durations is sufficient. SpaceX’s own Starlink satellites employ electric propulsion for these purposes.

However, launching from Earth’s surface demands something entirely different: enormous thrust delivered rapidly to overcome gravity and atmospheric drag. A typical orbital-class booster must generate thrust far exceeding its weight, often in the millions of Newtons within seconds.

Chemical rockets achieve this through exothermic combustion of dense propellants, producing high-mass-flow, high-velocity exhaust. Electric systems, by contrast, expel very small amounts of mass at extremely high speeds. Generating equivalent thrust would require impractical onboard power levels, massive energy storage or generation systems, and prohibitive added mass, rendering the approach infeasible with current or near-term technology.

Musk has previously expressed a similar sentiment, noting a desire for electric orbital rockets while acknowledging the inescapable requirements of Newton’s third law and energy delivery. The distinction is clear: electric propulsion excels once a vehicle is already in space; it cannot replace the high-thrust chemical phase required to reach orbit from the ground.

The episode illustrates broader critiques of ESG ratings. Proponents argue they incentivize better risk management and long-term sustainability. Detractors, including Musk—who has previously called ESG a “scam”—contend that such metrics can penalize essential activities when no practical alternative exists, potentially discouraging innovation in sectors like space access.

Elon Musk dubs the S&P 500 ESG as “outrageous scam” after Tesla gets booted from index

SpaceX has sought to mitigate launch-related impacts through reusability: Falcon 9 boosters have flown more than 30 times in some cases, dramatically lowering the manufacturing and emissions burden per kilogram delivered to orbit. Starship’s design further emphasizes rapid reusability and methane propellant, which can theoretically be produced via sustainable pathways.

Ultimately, Musk’s remark serves as a reminder that certain engineering realities persist regardless of scoring systems. As humanity expands its presence in space for communications, science, and exploration, balancing genuine environmental progress with technological necessity remains a central challenge.

ESG frameworks may evolve, but the fundamental limits of electric launch propulsion are unlikely to change soon.

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Tesla just trademarked MEGAPOD: here’s what it is

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tesla showroom
(Credit: Tesla)

Tesla just trademarked ‘MEGAPOD’ with the United States Patent and Trademark Office (USPTO), its latest move in what seems to be a hint that the company is incredibly focused on its AI efforts and storage needs as compute increases.

The application carries serial number 99893717 and lists the applicant as Tesla, Inc., located at 1 Tesla Road, Austin, Texas 78725.

The filing remains in ‘live pending’ status, and it is a new application waiting for assignment to an examining attorney. It has not yet been published or registered.

According to the official goods and services description in the application, Tesla describes ‘MEGAPOD’ as:

“Modular data center hardware systems for artificial intelligence computing, comprised of computer servers, computer hardware for artificial intelligence processing, computer networking hardware, electrical power distribution units, and cooling systems, sold as a unit; self-contained modular computing hardware systems for artificial intelligence workloads; integrated computer hardware platforms for artificial intelligence computing, namely, enclosures containing computer hardware, power distribution hardware, and cooling hardware, sold as a unit; downloadable software for monitoring, managing, optimizing, and regulating modular artificial intelligence computing hardware systems.”

This description specifies complete, self-contained modular units that integrate servers and specialized AI processing hardware with networking components, power distribution, and cooling systems. It also includes associated downloadable software for oversight and optimization of these systems. The language emphasizes hardware sold “as a unit” and enclosures that combine the necessary elements for AI computing workloads.

Tesla has an established history of developing and commercializing modular hardware systems. Its Megapack product line, for example, consists of utility-scale battery energy storage systems designed as containerized units for grid applications. The MEGAPOD filing follows a similar pattern of protecting a name for modular, integrated hardware platforms, this time focused on artificial intelligence computing infrastructure.

This could be an early move, especially as Tesla did not have trademark rights to the word ‘Cybercab,’ the name of its self-driving, ride-hailing-focused vehicle.

Trademark applications of this type allow companies to secure priority rights to a name for defined categories of goods and services. The USPTO examines applications for compliance with legal requirements, including distinctiveness and absence of conflicts with prior marks. If the application proceeds successfully through examination, publication, and any opposition period, it could result in a federal trademark registration providing nationwide protection. This is what Tesla’s obvious intention is with ‘MEGAPOD.’

Public reports and analysis suggest MEGAPOD could represent modular, container-style AI computing pods designed for easy deployment. These would bundle servers, AI accelerators, power systems, and cooling into self-contained units suitable for distributed AI workloads. This approach aligns with Tesla’s announced AI compute strategy.

In March 2026, Elon Musk outlined plans for “Digital Optimus” (also referred to as Macrohard), a joint Tesla-xAI project for AI agents capable of handling complex digital tasks. The plans include running these agents on Tesla’s AI4 hardware in parked vehicles as well as dedicated compute units installed at Supercharger stations, which collectively offer substantial unused electrical capacity.

What is Digital Optimus? The new Tesla and xAI project explained

A modular hardware platform like the one described in the ‘MEGAPOD’ filing would support scalable, rapid deployment of such distributed compute resources. It could complement Tesla’s other AI infrastructure efforts, including the Dojo supercomputer used for training models and the development of AI systems for autonomous driving and robotics, by enabling edge or regional AI inference without reliance on traditional centralized data centers.

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