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Relativity Space’s first 3D-printed rocket goes vertical for launch debut
Relativity Space’s first 3D-printed Terran 1 rocket has rolled out to the startup’s Florida pad and been raised vertical ahead of its launch debut.
Founded in 2015, the private Los Angeles-based spaceflight company shipped its first complete rocket prototype to Florida in June 2022. Prior to that major milestone, Relativity qualified Terran 1’s orbital second stage at leased facilities located at NASA’s Stennis Space Center in southwest Mississippi, and – alongside a nosecone and interstage – arrived at Cape Canaveral Space Force Station (CCSFS) more or less ready to fly.
The last six months have been almost exclusively dedicated to testing Terran 1’s larger and more powerful first stage (booster) as thoroughly as possible. Instead of building a dedicated booster test stand in Mississippi, Relativity chose to modify Terran 1’s lone LC-16 launch pad for the crucial task. Ultimately, the startup was able to complete a large amount of booster testing on the ground, significantly increasing the odds that Terran 1 will perform as expected when it lifts off for the first time.
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
Beginning with cryogenic proofing, propellant loading, ‘spin starts,’ and several shorter static fire tests, Relativity’s first Terran 1 booster test campaign culminated with two long-duration static fires in September 2022. The final 57 and 82-second static fires weren’t quite the “full mission duration” tests Relativity had hoped for, but the company concluded that the data gathered was enough to clear the booster for flight.
According to Ellis, one of the most important insights gained from those tests was into Terran 1’s uncharacteristically complex autogenous pressurization system – unprecedented for such a small rocket. Generally speaking, orbital-class rockets store helium gas in small ultra-high-pressure tanks (COPVs) and use helium to pressurize their propellant tanks as they are drained of propellant. Autogenous pressurization refers to an alternative in which a portion of a rocket’s liquid oxidizer and fuel are turned into hot gas and injected back into their respective tanks to pressurize them.
Helium is extremely expensive and an unrenewable resource. In theory, autogenous pressurization – at the cost of being significantly more complex and finicky – can also reduce the amount of dry mass reserved for tank pressurization. While Terran 1 wasn’t able to complete a full-duration static fire, the tests it did complete showed Relativity that its autogenous pressurization systems are unlikely to be a problem in flight, mostly eliminating a major source of uncertainty.
Following the final 82 or 88-second static fire, Relativity returned Terran 1’s booster to LC-16’s hangar and shifted its focus to fully assembling the two-stage rocket and finishing the launch pad. In early December, the company announced that it had fully assembled the first Terran 1. Days later, the rocket was installed on the pad’s “Transporter Erector.” The T/E responsible for transporting the rocket and raising it vertical, but it also needs to connect the rocket to ground systems (propellant, power, comms, etc.) and hold it down before liftoff.
On or around December 6th, Terran 1 rolled out to the pad and was raised vertical soon after. According to Ellis, all that stands between Terran 1 and its first launch is a short integrated static fire test and a launch license from the Federal Aviation Administration (FAA). It’s impossible to say how long the FAA will take, but it’s likely that Relativity will be technically ready to launch just a handful of weeks from now.
Beyond building a relativity impressive rocket, Relativity’s claim to fame is large-scale 3D printing. The startup says that the first Terran 1 rocket – booster, upper stage, fairing, engines, and all – is 85% 3D-printed by mass and the largest single 3D-printed object ever built. Terran 1 reportedly weighs around 9.3 tons (20,500 lb) empty; will measure around 33 meters (110 ft) tall and 2.3 meters (7.5 ft) wide; and will produce around 90 tons (~200,000 lbf) of thrust at liftoff. The rocket is designed to launch 1.25 tons (~2750 lb) to low Earth orbit for $12 million
Tesla’s Head of AI, Ashok Elluswamy, says that something that was expected with version 14.3 of the company’s Full Self-Driving platform has already partially shipped with the current build of version 14.2.
Tesla and CEO Elon Musk have teased on several occasions that reasoning will be a big piece of future Full Self-Driving builds, helping bring forth the “sentient” narrative that the company has pushed for these more advanced FSD versions.
Back in October on the Q3 Earnings Call, Musk said:
“With reasoning, it’s literally going to think about which parking spot to pick. It’ll drop you off at the entrance of the store, then go find a parking spot. It’s going to spot empty spots much better than a human. It’s going to use reasoning to solve things.”
Musk said in the same month:
“By v14.3, your car will feel like it is sentient.”
Amazingly, Tesla Full Self-Driving v14.2.2.2, which is the most recent iteration released, is very close to this sentient feeling. However, there are more things that need to be improved, and logic appears to be in the future plans to help with decision-making in general, alongside other refinements and features.
On Thursday evening, Elluswamy revealed that some of the reasoning features have already been rolled out, confirming that it has been added to navigation route changes during construction, as well as with parking options.
He added that “more and more reasoning will ship in Q1.”
🚨 Tesla’s Ashok Elluswamy reveals Nav decisions when encountering construction and parking options contain “some elements of reasoning”
More uses of reasoning will be shipped later this quarter, a big tidbit of info as we wait v14.3 https://t.co/jty8llgsKM
— TESLARATI (@Teslarati) January 9, 2026
Interestingly, parking improvements were hinted at being added in the initial rollout of v14.2 several months ago. These had not rolled out to vehicles quite yet, as they were listed under the future improvements portion of the release notes, but it appears things have already started to make their way to cars in a limited fashion.
Tesla Full Self-Driving v14.2 – Full Review, the Good and the Bad
As reasoning is more involved in more of the Full Self-Driving suite, it is likely we will see cars make better decisions in terms of routing and navigation, which is a big complaint of many owners (including me).
Additionally, the operation as a whole should be smoother and more comfortable to owners, which is hard to believe considering how good it is already. Nevertheless, there are absolutely improvements that need to be made before Tesla can introduce completely unsupervised FSD.
Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
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Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Tesla AI Head says future FSD feature has already partially shipped
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
