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SpaceX ships Starship’s 200th upgraded Raptor engine
A day after revealing the completion of the 200th Falcon upper stage and Merlin Vacuum engine, SpaceX has announced that it also recently finished building Starship’s 200th upgraded Raptor engine.
Starship – and Raptor, by extension – has yet to reach orbit and is likely years away from scratching the surface of the established success and reliability of the Falcon upper stage and MVac. But compared to MVac, Raptor is more complex, more efficient, more than twice as powerful, experiences far more stress, and is three times younger.
And Raptor 2 isn’t the first version of the engine. Before SpaceX shipped its first Raptor 2 prototype, it manufactured 100 Raptor 1 engines between the start of full-scale testing in February 2018 and July 2021. By late 2021 or early 2022, when Raptor 2 took over, the total number of Raptor 1 engines produced likely reached somewhere between 125 and 150 – impressive but pale in comparison to SpaceX’s Raptor 2 ambitions.
From the start, Raptor 2’s purpose was to make future Raptors easier, faster, and cheaper to manufacture. The ultimate goal is to eventually reduce the cost of Raptor 2 production to $1000 per ton of thrust, or $230,000 at Raptor 2’s current target of 230 tons (~510,000 lbf) of thrust. As of mid-2019, Musk reported that each early Raptor 1 prototype cost “more” than $2 million for what would turn out to be 185 tons of thrust (~$11,000 per ton). It’s not clear if that ever appreciably changed.
In response, SpaceX strived to make Raptor 2 simpler wherever possible, removing a large part of the maze of primary, secondary, and tertiary plumbing. In 2022, CEO Elon Musk confirmed that SpaceX had even removed a complex torch igniter system for Raptor 2’s main combustion chamber. All that simplification made Raptor 2 much easier to build in theory, and SpaceX’s production figures have more than confirmed that theory. Despite those simplifications, SpaceX was also able to boost Raptor 2’s thrust by 25% by sacrificing just 1% of Raptor 1’s efficiency.
Beginning with its first delivery in February 2018, SpaceX produced the first 100 Raptor 1 engines in about 36 months. In the first 11 to 12 months of Raptor 2 production, SpaceX has delivered 200 engines. That translates to at least six times the average throughput, but the true figure is even higher. In June 2019, Musk stated that SpaceX was “aiming [to build a Raptor] engine every 12 hours by end of year.” As is usually the case, that progress took far longer to realize. But in October 2022, a senior NASA Artemis Program official revealed that SpaceX recently achieved sustained production of one Raptor 2 engine per day for a full week.
Such a high rate – likely making Raptor one of the fastest-produced orbital-class rocket engines in history – is required because SpaceX’s next-generation Starship rocket needs a huge amount of engines. The Starship upper stage currently requires three sea-level-optimized Raptors and three vacuum-optimized Raptors, and SpaceX has plans to increase that to nine engines total. Starship’s Super Heavy booster is powered by 33 sea-level Raptors.
Orbital-class versions of Starship and Super Heavy have never flown, let alone demonstrated successful recovery or reuse, so SpaceX has to operate under the assumption that every orbital test flight will consume 39 Raptors. Even after the reuse of Super Heavy boosters or Starships becomes viable, taking significant strain off of Raptor demand, SpaceX wants to manufacture a fleet of hundreds or even thousands of Starships and a similarly massive number of boosters. To outfit that massive fleet, SpaceX would have to mass-produce orbital-class Raptor engines at a scale that’s never been attempted.
But it will likely be years – if not a decade or longer – before SpaceX is in a position to attempt to create that mega-fleet. If the Raptor 2 engines SpaceX is already building are modestly reliable and reusable, and it doesn’t take more than 5-10 orbital test flights to begin reusing Starships and Super Heavy boosters, a production rate of one engine per day is arguably good enough to support the next few years of realistic engine demand.
SpaceX’s first orbital Starship launch attempt could occur as early as December 2022, although Q1 2023 is more likely. SpaceX currently has permission for up to five orbital Starship launches per year out of its Starbase, Texas facilities and will likely try to take full advantage of that with several back-to-back test flights in a period of 6-12 months.
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.
Elon Musk
Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.
A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial.
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.
Judge says disputed facts warrant a trial
At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.
Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”
OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.
Rivalries and Microsoft ties
The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.
The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.
Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
