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SpaceX delays Starhopper’s first flight a few days despite Raptor preburner test success

According to NASASpaceflight.com, SpaceX's Starhopper successfully completed a Raptor preburner taste on July 15th. A static fire ignition test should follow on July 16th.(NASASpaceflight - bocachicagal)

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SpaceX has (partially) ignited Starhopper’s freshly-installed Raptor engine, successfully verifying that the engine is ready for its next major test: a full ignition and static firing. Although successful, SpaceX still has some work to do before the vehicle is ready for its first untethered flight(s).

July 15th’s progress is just the latest in a several day-series of preflight tests designed to reduce the likelihood that Starhopper is destroyed over the coming days and (hopefully) weeks. If all goes planned during the awkward Starship prototype’s first foray into hover tests, SpaceX CEO Elon Musk has stated that he will provide an official presentation updating the public on the status of the company’s ever-changing next-generation rocket.

The past week or so of Starhopper preflight testing began with Raptor serial number 6 (SN06) completing the last of a series of acceptance test fires in McGregor, Texas on June 10th. Even on its own, this was a major milestone for the new SpaceX engine: Raptor SN06 was the first of the new, full-scale engines to pass the acceptance test program with flying colors. According to Musk, for the engine to complete those tests so successfully, SpaceX had to solve a challenging bug in which some sort of mechanical resonance (i.e. vibration) damaged or destroyed Raptors SN01-05.

Hours later, the engine began a short ~450 mi (720 km) journey south to Starhopper, located in Boca Chica, Texas. The engine arrived on July 11th and was fully installed on Starhopper by the following evening (July 12th), at which point SpaceX put Starhopper and Raptor through some mild but valuable thrust vector controller (TVC) tests, wiggling the car-sized engine to ensure it can accurately steer the prototype rocket.

Around two days after the above ‘wiggle’ test was successfully completed, SpaceX moved into the next stage, partially fueling Starhopper with liquid methane and oxygen propellant and helium pressurant in what is known in rocketry as a wet dress rehearsal (WDR). The (implicitly) successful WDR was capped off with a duo of what can now safely be concluded were some sort of Raptor test preceding even pre-ignition operations. Whatever the tests were, they appear to have been completed successfully.

That appears to be the case because less than 24 hours after their completion, on July 15th, SpaceX once again began loading Starhopper with propellant and pressurant for a second round of wet testing. This time around, SpaceX got right into more critical Raptor tests once enough propellant was loaded, igniting the engine’s interwoven oxygen and methane preburners.

Starhopper (technically) came alive for the third time ever on July 15th, albeit only partially. SpaceX ignited the engine’s preburners as a precursor to a full static fire, now NET July 16th. (LabPadre – YouTube livestream)

Previously discussed 24 hours ago in a Teslarati article focused on Raptor wiggles and other miscellaneous tests, Raptor is an extremely advanced rocket engine based on a cycle (i.e. how propellant is turned into thrust) known as full-flow staged combustion.

In a staged-combustion engine like Raptor, getting from the supercool liquid oxygen and methane propellant to 200+ tons of thrust is quite literally staged, meaning that the ignition doesn’t happen all at once. Rather, the preburners – essentially their own, unique combustion chambers – ignite an oxygen- or methane-rich mixture, the burning of which produces the gas and pressure that powers the turbines that bring fuel into the main combustion chamber. That fuel then ignites, producing thrust as they exit the engine’s bell-shaped nozzle.

Unintuitively, conditions inside the preburner – hidden away from view – are actually far more intense than the iconic blue, purple, and pink flame that visibly exists Raptor’s nozzle. Much like hot water will cool while traveling through pipes, the superheated gaseous propellant that Raptor ignites to produce thrust will also cool (and thus lose pressure) as it travels from Raptor’s preburner to its main combustion chamber. If the pressure produced in the preburners is too low, Raptor’s thrust will be (roughly speaking) proportionally limited at best. At worst, low pressure in the preburners can trigger a “hard start” or shutdown that could destroy the engine. According to Elon Musk, Raptor’s oxygen preburner thus has the worst of it, operating at pressures as high or higher than 800 bar (11,600 psi, 80 megapascals).”

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In full-flow staged combustion (FFSC), even more complexity is added as all propellant that touches the engine must necessarily end up traveling through the main combustion chamber to eke every last ounce of thrust out of the finite propellant a rocket lifts off with. As such, FFSC engines can be about as efficient as the laws of physics allow any given chemical rocket engine to be, at the cost of exceptional complexity and brutally difficult development.

Additionally, FFSC physically requires two separate preburners and then makes things even harder by making each separate preburner (methane and oxygen) depend on each other’s operation for the engine to fully ignite. This means that no individual preburner can be used to kickstart Raptor – instead, SpaceX must somehow spin the turbopumps that feed propellant into each preburner with some separate system. This is all just to emphasize the fact that Raptor’s ignition sequence is a spectacularly complex orchestra of valves, spark plugs, sensors, and magic. This is why it’s valuable for Raptor to test its preburner system independently of an actual ignition test, at least as long as the engine is still in the development stages.

A Raptor engine is pictured here during a static fire test in McGregor, Texas. (SpaceX)

According to NASASpaceflight.com managing editor Chris Bergin, what this practically translates to is a minor Starhopper hover test delay of 1-2 days, while the static fire has also been pushed roughly 24 hours from July 15th to July 16th. If that full static fire produces lots of happy data, Starhopper could be cleared for a hover test debut attempt as early as Wednesday or Thursday (July 17/18).

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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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Tesla announces crazy new Full Self-Driving milestone

The number of miles traveled has contextual significance for two reasons: one being the milestone itself, and another being Tesla’s continuing progress toward 10 billion miles of training data to achieve what CEO Elon Musk says will be the threshold needed to achieve unsupervised self-driving.

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Credit: Tesla

Tesla has announced a crazy new Full Self-Driving milestone, as it has officially confirmed drivers have surpassed over 8 billion miles traveled using the Full Self-Driving (Supervised) suite for semi-autonomous travel.

The FSD (Supervised) suite is one of the most robust on the market, and is among the safest from a data perspective available to the public.

On Wednesday, Tesla confirmed in a post on X that it has officially surpassed the 8 billion-mile mark, just a few months after reaching 7 billion cumulative miles, which was announced on December 27, 2025.

The number of miles traveled has contextual significance for two reasons: one being the milestone itself, and another being Tesla’s continuing progress toward 10 billion miles of training data to achieve what CEO Elon Musk says will be the threshold needed to achieve unsupervised self-driving.

The milestone itself is significant, especially considering Tesla has continued to gain valuable data from every mile traveled. However, the pace at which it is gathering these miles is getting faster.

Secondly, in January, Musk said the company would need “roughly 10 billion miles of training data” to achieve safe and unsupervised self-driving. “Reality has a super long tail of complexity,” Musk said.

Training data primarily means the fleet’s accumulated real-world miles that Tesla uses to train and improve its end-to-end AI models. This data captures the “long tail” — extremely rare, complex, or unpredictable situations that simulations alone cannot fully replicate at scale.

This is not the same as the total miles driven on Full Self-Driving, which is the 8 billion miles milestone that is being celebrated here.

The FSD-supervised miles contribute heavily to the training data, but the 10 billion figure is an estimate of the cumulative real-world exposure needed overall to push the system to human-level reliability.

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Tesla Cybercab production begins: The end of car ownership as we know it?

While this could unlock unprecedented mobility abundance — cheaper rides, reduced congestion, freed-up urban space, and massive environmental gains — it risks massive job displacement in ride-hailing, taxi services, and related sectors, forcing society to confront whether the benefits of AI-driven autonomy will outweigh the human costs.

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Credit: Tesla | X

The first Tesla Cybercab rolled off of production lines at Gigafactory Texas yesterday, and it is more than just a simple manufacturing milestone for the company — it’s the opening salvo in a profound economic transformation.

Priced at under $30,000 with volume production slated for April, the steering-wheel-free, pedal-less Robotaxi-geared vehicle promises to make personal car ownership optional for many, slashing transportation costs to as little as $0.20 per mile through shared fleets and high utilization.

While this could unlock unprecedented mobility abundance — cheaper rides, reduced congestion, freed-up urban space, and massive environmental gains — it risks massive job displacement in ride-hailing, taxi services, and related sectors, forcing society to confront whether the benefits of AI-driven autonomy will outweigh the human costs.

Let’s examine the positives and negatives of what the Cybercab could mean for passenger transportation and vehicle ownership as we know it.

The Promise – A Radical Shift in Transportation Economics

Tesla has geared every portion of the Cybercab to be cheaper and more efficient. Even its design — a compact, two-seater, optimized for fleets and ride-sharing, the development of inductive charging, around 300 miles of range on a small battery, half the parts of the Model 3, and revolutionary “unboxed” manufacturing — is all geared toward rapid production.

Operating at a fraction of what today’s rideshare prices are, the Cybercab enables on-demand autonomy for a variety of people in a variety of situations.

Tesla ups Robotaxi fare price to another comical figure with service area expansion

It could also be the way people escape expensive and risky car ownership. Buying a vehicle requires expensive monthly commitments, including insurance and a payment if financed. It also immediately depreciates.

However, Cybercab could unlock potential profitability for owning a car by adding it to the Robotaxi network, enabling passive income. Cities could have parking lots repurposed into parks or housing, and emissions would drop as shared electric vehicles would outnumber gas cars (in time).

The first step of Tesla’s massive production efforts for the Cybercab could lead to millions of units annually, turning transportation into a utility like electricity — always available, cheap, and safe.

The Dark Side – Job Losses and Industry Upheaval

With Robotaxi and Cybercab, they present the same negatives as broadening AI — there’s a direct threat to the economy.

Uber, Lyft, and traditional taxis will rely on human drivers. Robotaxi will eliminate that labor cost, potentially displacing millions of jobs globally. In the U.S. alone, ride-hailing accounts for billions of miles of travel each year.

There are also potential ripple effects, as suppliers, mechanics, insurance adjusters, and even public transit could see reduced demand as shared autonomy grows. Past automation waves show job creation lags behind destruction, especially for lower-skilled workers.

Gig workers, like those who are seeking flexible income, face the brunt of this. Displaced drivers may struggle to retrain amid broader AI job shifts, as 2025 estimates bring between 50,000 and 300,000 layoffs tied to artificial intelligence.

It could also bring major changes to the overall competitive landscape. While Waymo and Uber have partnered, Tesla’s scale and lower costs could trigger a price war, squeezing incumbents and accelerating consolidation.

Balancing Act – Who Wins and Who Loses

There are two sides to this story, as there are with every other one.

The winners are consumers, Tesla investors, cities, and the environment. Consumers will see lower costs and safer mobility, while potentially alleviating themselves of awkward small talk in ride-sharing applications, a bigger complaint than one might think.

Elon Musk confirms Tesla Cybercab pricing and consumer release date

Tesla investors will be obvious winners, as the launch of self-driving rideshare programs on the company’s behalf will likely swell the company’s valuation and increase its share price.

Cities will have less traffic and parking needs, giving more room for housing or retail needs. Meanwhile, the environment will benefit from fewer tailpipes and more efficient fleets.

A Call for Thoughtful Transition

The Cybercab’s production debut forces us to weigh innovation against equity.

If Tesla delivers on its timeline and autonomy proves reliable, it could herald an era of abundant, affordable mobility that redefines urban life. But without proactive policies — retraining, safety nets, phased deployment — this revolution risks widening inequality and leaving millions behind.

The real question isn’t whether the Cybercab will disrupt — it’s already starting — it’s whether society is prepared for the economic earthquake it unleashes.

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Tesla Model 3 wins Edmunds’ Best EV of 2026 award

The publication rated the Model 3 at an 8.1 out of 10, and with its most recent upgrades and changes, Edmunds says, “This is the best Model 3 yet.”

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Credit: Tesla

The Tesla Model 3 has won Edmunds‘ Top Rated Electric Car of 2026 award, beating out several other highly-rated and exceptional EV offerings from various manufacturers.

This is the second consecutive year the Model 3 beat out other cars like the Model Y, Audi A6 Sportback E-tron, and the BMW i5.

The car, which is Tesla’s second-best-selling vehicle behind the popular Model Y crossover, has been in the company’s lineup for nearly a decade. It offers essentially everything consumers could want from an EV, including range, a quality interior, performance, and Tesla’s Full Self-Driving suite, which is one of the best in the world.

The publication rated the Model 3 at an 8.1 out of 10, and with its most recent upgrades and changes, Edmunds says, “This is the best Model 3 yet.”

In its Top Rated EVs piece on its website, it said about the Model 3:

“The Tesla Model 3 might be the best value electric car you can buy, combining an Edmunds Rating of 8.1 out of 10, a starting price of $43,880, and an Edmunds-tested range of 338 miles. This is the best Model 3 yet. It is impressively well-rounded thanks to improved build quality, ride comfort, and a compelling combination of efficiency, performance, and value.”

Additionally, Jonathan Elfalan, Edmunds’ Director of Vehicle Testing, said:

“The Model 3 offers just about the perfect combination of everything — speed, range, comfort, space, tech, accessibility, and convenience. It’s a no-brainer if you want a sensible EV.”

The Model 3 is the perfect balance of performance and practicality. With the numerous advantages that an EV offers, the Model 3 also comes in at an affordable $36,990 for its Rear-Wheel Drive trim level.

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