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Relativity’s first 3D-printed rocket aims to debut a new rocket fuel
Relativity can almost taste the vacuum of space. A substantial amount of work remains, but the startup continues to defy expectations with its relentless and methodical push towards the first orbital launch of a 3D-printed rocket.
Founded in 2015, the Los Angeles-based aerospace company has taken its few years of obligatory delays in stride while pursuing a 2020 debut for its (relatively) small Terran 1 rocket. In a world with dozens of serious rocket startups, missing one’s initial launch target is practically a rite of passage – the path to orbit is never as straight and bump-free as the highway on-ramps that are often promised in pitch decks. Relativity Space, however, is no average rocket startup.
Save for SpaceX, which operates in a league of its own, no other private rocket startup has come close to matching the $1.3 billion Relativity has raised to develop Terran 1 and the much larger Terran R. More importantly, in a recent interview with Aviation Week, CEO Tim Ellis (a former Blue Origin engineer) revealed that the company could be “weeks away” from the first launch of Terran 1, a rocket that is 85% 3D-printed by mass and could simultaneously debut a new kind of rocket fuel.
Once fully assembled, Terran 1 – weighing around 9.3 tons (~20,500 lb) empty and measuring 33.5 meters (110 ft) tall – will be the largest metal 3D-printed object in the history of the technology. From that perspective, it’s hardly surprising that Relativity Space is a few years behind schedule. In fact, it’s odd that the startup isn’t more delayed, and it’s even more impressive that Terran 1’s first launch campaign has gone as smoothly as it has.
Slow, Smooth and Fast
Terran 1 Flight 1’s booster stage and upper stage both arrived at the company’s leased Cape Canaveral Space Force Station LC-16 pad sometime in May 2022. Terran 1’s first stage came directly from the California factory. The second stage (S2), however, first shipped to a Mississippi test stand a few months prior and, on its first try, completed a full-duration multi-minute static fire test known as a mission duty cycle (MDC) – about as close as it’s possible to get to replicating orbital upper stage operations on the ground. The flawless MDC was preceded by a number of simpler precursor tests, of course, but the rocket performed more or less as expected throughout the entire qualification program. If Terran’s second stage ignites again, it’ll be at the edge of space.
Since June, the critical path for Terran 1’s launch debut has thus been qualifying the first finished Terran booster. Rather than modify its Mississippi test facilities, Relativity decided to temporarily modify its heavily upgraded LC-16 pad to support booster qualification testing. Thanks to the heroic work of a shockingly small team of five people, the pad was ready to kick off testing as soon as the Terran 1 booster arrived in Florida. Even more surprisingly, senior manager Lorenzo Locante says that LC-16 – practically a new pad after Relativity’s extensive modifications – has “performed perfectly” during every booster qualification test attempted thus far.
That testing has included pneumatic proofing (an ambient-temperature gas pressure test), possible cryogenic proof tests, multiple rounds of propellant loading, preignition testing of its nine Aeon engines, and multiple spin-start tests (the last step before static fire testing) with the same engines. Given that LC-16 and Terran 1 must handle cryogenic oxidizer (liquid oxygen) and cryogenic fuel (liquid methane), which can easily create a flammable and bomb-like mixture of gases from even the smallest of leaks, it’s difficult to emphasize just how difficult it is to ensure that a complex launch pad and rocket perform nominally during their first joint testing.
According to engineers onsite during a private Teslarati tour of Relativity’s Florida launch facilities, Terran 1 S1’s next goal is to fully ignite its Aeon engines. After one or more successful static fires, the booster will be integrated with the upper stage and nosecone for a final full-duration static fire test that will also double as a full wet dress rehearsal (WDR). Testing the fully-integrated Terran 1 rocket will only be possible once LC-16’s full strongback and launch mount (also known as a transporter/erector) is completed, but that final piece of the puzzle should be ready any day now.
De Terra Ad Astra
The coming weeks will likely be some of the company’s riskiest and most difficult yet. If the rocket and LC-16 continue to operate as smoothly as they have been, however, there’s a nonzero chance that Terran 1 could beat the likes of SpaceX (Starship), Blue Origin (New Glenn), and the United Launch Alliance (Vulcan Centaur) to the punch to become the first methane and oxygen-fueled rocket in history to attempt an orbital launch.*
*While SpaceX’s Starship is technically the first large-scale suborbital methalox rocket to attempt (and complete) a launch, there has never been an orbital methalox launch attempt.
Capable of carrying up to 1.25 tons (~2750 lb) to low Earth orbit for as little as $12 million, Terran 1 also has a shot at becoming the first new privately-developed 1-ton-class rocket of any kind to successfully reach orbit. On that front, though, Relativity is in a neck-and-neck race with Firefly Aerospace and ABL Space, both of which intend to launch similarly-sized rockets at some point in the next few months. It’s never been less clear who will cross the finish line first but one would be hard-pressed to count Relativity out.
Elon Musk dismissed reports claiming SpaceX had placed a massive order for NVIDIA GPUs worth $52 billion. The denial came hours after Taiwanese media, citing unnamed industry sources, reported that SpaceX planned to acquire approximately 13,000 AI server racks, equating to roughly 1 million GB300 GPUs, from Foxconn.
Each rack was estimated at around $4 million, with deliveries potentially starting in late 2025.
The story suggested this would mark SpaceX’s first major foray into Foxconn-manufactured NVIDIA hardware, breaking from suppliers like Supermicro and Dell. Musk responded bluntly on X:
This is fake news
— Elon Musk (@elonmusk) July 20, 2026
Despite the denial, the rumored scale aligns with SpaceX’s explosive growth in AI infrastructure. NVIDIA’s GB300 (successor to the GB200 NVL) racks deliver unprecedented performance for large-scale training and inference. A $52 billion commitment would dwarf most corporate AI budgets and provide the compute muscle needed for frontier models.
SpaceX already operates gigawatt-scale terrestrial clusters like Colossus in Memphis, Tennessee, and has monetized them aggressively through leasing deals.
SpaceX’s newest Starmind will make earth data centers obsolete
Major customers include Anthropic (paying ~$1.25 billion monthly for 220,000+ GPUs), Google (~$920 million monthly for 110,000 GPUs), and Reflection AI. These arrangements are projected to generate tens of billions in annual revenue, far outpacing traditional SpaceX businesses.
Such an investment would fuel internal AI efforts, particularly Grok models under the integrated SpaceXAI division, while supporting ambitious orbital data center plans. SpaceX envisions launching thousands of AI-optimized satellites powered by solar energy and cooled in space, bypassing terrestrial power and land constraints.
This “Starmind” constellation could position the company as a leader in space-based computing.
SpaceX as an Emerging AI Powerhouse
Once primarily known for reusable rockets and Starlink satellite internet, SpaceX has transformed into a multifaceted AI player.
The 2026 acquisition of xAI integrated Grok development directly into the company. Starlink’s low-latency global network complements massive compute clusters, enabling efficient data flow for training and serving AI models.
Musk has long argued that AI scaling demands solutions beyond Earth, citing things like real estate and electricity limits on the ground.
While the Foxconn deal may not be in the cards, SpaceX’s trajectory is continuing on the path of blending aerospace engineering with hyperscale AI to dominate both launches and intelligence infrastructure.
Elon Musk shed more details on the upcoming improvements to Tesla’s Full Self-Driving suite, specifically one that the CEO mentioned last week, which should help owners see fewer interventions.
Last week, Musk hinted that one major improvement that Tesla planned to roll out to Full Self-Driving users was the car’s ability “to remember your specific interventions and match each person’s individual preferences.”
Elon Musk says your Tesla will start to learn your individual preferences
This small bit of detail was linked to a post from Tesla community member Whole Mars, who said that FSD’s tendency to exit the carpool lane, a feature that owners can turn on but at times the car will disregard.
It sounds like, based on Musk’s two responses since that original post, it is safe to say the things FSD will start to remember are wide-ranging. However, it seems the biggest differences will be noticed with parking performance, which Musk continues to mention.
Highway Lane Preferences
The initial post Musk mentioned, with these new remembered preferences soon to arrive for Tesla owners everywhere, was the Carpool/Express Lane.
Tesla has a setting in the FSD menu that lets drivers enable HOV Lane travel. However, the car won’t always stay in that suggested or preferred lane.
The car will start to remember your specific interventions and match each person’s individual preferences
— Elon Musk (@elonmusk) July 18, 2026
Some owners have also complained of left lane camping, an illegal maneuver in at least some states. Cruising in the passing lane has resulted in tickets for some, as it is illegal in over 30 states in the U.S.
Tesla did not confirm if these preferences would also be included in new FSD behaviors, but it would certainly help move the company toward fewer interventions.
Parking Preferences
This seems to be the real focus of the entire operation, as Musk stated several weeks ago that parking was overwhelmingly the most frequent reason for interventions.
The major issue with parking is not necessarily the parking “performance,” as FSD is generally good at parking. It definitely has its issues; we’ve recorded plenty of them, including this one as recent as last week:
Yeah it seems like FSD v14.3.5 is having some issues with parking early on https://t.co/Bw5ULfVmDq pic.twitter.com/RHdpjOEpIo
— TESLARATI (@Teslarati) July 13, 2026
However, the changes coming are more about preferences, meaning where you park and how your car enters the spot, either pulling in or backing in. Owners have also reported that pulling into the correct driveway is a relatively rare thing for FSD, something else that needs to be confronted.
Musk basically confirmed that all of these things would be part of Tesla’s plan to address driver preferences with FSD:
Yes
— Elon Musk (@elonmusk) July 20, 2026
It’s obvious there is something big coming with FSD, and the company’s focus seems to be eliminating any intervention that would be related to preferences. This is probably the biggest bottleneck between Tesla and being fully autonomous. Critical interventions do occur, but they are much less frequent.
The only time a driver should be taking over is because of a critical intervention; this seems to be the goal of Tesla right now.
This all seems to be a priority as Tesla continues to move closer to the prospect of unsupervised driving.
Elon Musk said today on X that Teslas will start to learn your individual preferences. This is something that he seemed to hint toward earlier this month when he said parking was by far the biggest reason drivers intervene with Full Self-Driving.
Musk made the comment in response to notable Tesla influencer Whole Mars, who said that his vehicle will sometimes disobey the settings he has enabled for his car. He responded to the post, stating that “The car will start to remember your specific interventions and match each person’s individual preferences.”
The car will start to remember your specific interventions and match each person’s individual preferences
— Elon Musk (@elonmusk) July 18, 2026
This is something that could be perhaps one of the biggest ways Tesla could minimize or even work closer toward eliminating interventions altogether. While FSD does a lot of things really well, many people intervene a vast majority of the time not due to major or critical safety errors.
Instead, many take over because the car is doing something that they do not like as a preference; it might park in a parking spot that is not preferred by the driver, it might linger too long in the left lane on the highway (a personal favorite), or it could even take a route that the driver does not like.
These all lead to interventions, but they are not triggered by a major safety issue. Instead, it’s just preference.
READ OUR REVIEW OF TESLA’S LATEST FSD VERSION:
Tesla Full Self-Driving v14.3.5 Early Impressions: new features and early performance
If Teslas could start to learn the personal preferences of the person who owns them, interventions will truly begin to be less frequent. Some of this is already pretty evident, in my opinion. Teslas use a neural network to learn behaviors and accumulate data to improve performance.
For months now, we’ve tracked FSD’s performance at “Except Right Turn” stop signs, something that is very common in Pennsylvania, but many of our readers located in other parts of the U.S. have never heard of. FSD handles one Except Right Turn stop sign very well, one that I travel past frequently. Others that I do not navigate through as often do not have as confident a performance. It seems like the cars might already be doing this to an extent.
🚨 Tesla Full Self-Driving v14.3 proceeds through an Except Right Turn Stop Sign pic.twitter.com/YemRSlens7
— TESLARATI (@Teslarati) April 8, 2026
That example is also for something that is a street sign and not necessarily a driver preference; however, I still feel it is worth mentioning because it only handles that commonly passed Except Right Turn stop sign with true confidence. Others it still seems to struggle with.
This could be one of Tesla’s big moves toward full autonomy, and it could be a pathway to truly unsupervised driving. Every day, millions of cars on the road travel at a human driver’s personal preferences with no incident. Why can’t autonomous vehicles still cater to a passenger’s preferences while being autonomous? Tesla seems to have the idea that it would be possible.
Elon Musk dispels $52 billion SpaceX-NVIDIA GPU deal: ‘Fake news’
Elon Musk sheds details on Tesla FSD’s upcoming improvements
