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Top Gear doubles down on Tesla vs Porsche race, claims Model S’ actual results are worse

(Credit: Top Gear/YouTube)

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Top Gear‘s saga involving a drag race between the Tesla Model S Performance and the Porsche Taycan Turbo S continues to unravel, as CEO Elon Musk expressed his comments on Twitter and the motoring publication posted an update defending its results. 

Following the release of a thorough analysis of the Model S vs Porsche Taycan drag race which suggested that Top Gear did not engage the Tesla’s Launch Mode and full Ludicrous Plus capabilities in the race, CEO Elon Musk took to Twitter to offer his take on the two vehicles’ bout. According to Musk, Top Gear did miss the Model S’ real performance figures, especially since the numbers published by the motoring publication were inconsistent with what regular Tesla owners have recorded on their vehicles. 

Amidst criticism from the electric car community, Top Gear has issued a response explaining its Model S Performance vs Taycan Turbo S drag race results. Quite surprisingly, the motoring publication admitted that they did use Model S figures from a previous race in the Tesla vs Porsche drag battle. Even more surprisingly, Top Gear claimed that this was done in favor of the Tesla Model S Performance. 

Explaining its results, Top Gear stated that the best figures recorded for the Tesla Model S Performance during its battle with the Taycan were a 0-60 mph time of 2.83 seconds, a 0-100 mph time of 6.64 seconds, and a quarter-mile time of 11.23 seconds at 123.2 mph. These figures were worse than the 0-60 mph time of 2.68 seconds, 0-100 mph time of 6.46 seconds, and quarter-mile time of 11.08 seconds at 124.0 mph listed by the publication in its comparative video. 

“These were numbers we recorded in a Model S on a previous occasion. We ran them because these are the best figures we’ve achieved in a Model S to date so we know that’s what the car is capable of. And just to be clear, the Tesla was in Ludicrous+ mode, the battery was pre-conditioned and both cars had around 85 per cent charge before the first run,” Top Gear wrote

Looking at Top Gear‘s statement and clarification, it appears that the motoring publication is suggesting that the Raven Model S Performance actually has worse capbilities than a vehicle that it used from back in 2017. This does not align with the experiences of Tesla owners at all, many of whom have reported that the Raven Model S Performance can actually outrun a Tesla Model S P100D in the quarter-mile. 

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Interestingly, Top Gear‘s clarification did not address the main concern expressed by the Tesla community about the Model S vs Taycan race — that the Tesla was not in Launch Mode during its drag battle with the German-made all-electric sports car. This, apart from the fact that a video of the Model S’ interior while it was racing with the Taycan showed that the vehicle’s Range Mode was activated, further clouds Top Gear‘s defense of its race. 

Overall, it is quite disappointing to see Top Gear standing by its Tesla Model S Performance vs Porsche Taycan Turbo S drag race results. With the race practically debunked, it would not be in the Porsche Taycan’s best interests to run away with a win from the Model S at this point. The Taycan deserves a clean win, and it is something that it can actually achieve, considering its dual-speed gearbox. Simply put, it would be better for Top Gear at this point to race the two vehicles again, this time with both cars on Launch Control, and this time with an actual Raven Model S, to provide an accurate depiction of a drag race between these two excellent vehicles.

Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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Tesla crosses major Unsupervised Self-Driving milestone

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Credit: Tesla

Tesla has reached a notable benchmark in its autonomous driving program after its Robotaxi fleet surpassed one million miles of unsupervised operation. The company made the announcement during its Cybercab event in Austin on September 3.

Tesla Vice President of AI Ashok Elluswamy told attendees he was happy to report the fleet had achieved one million miles of unsupervised Robotaxi operation as a testament to safety.

The new total marked a sharp increase from the 380,000 unsupervised miles Tesla disclosed during its second-quarter 2026 earnings update in late July.

In roughly six weeks, the company added about 620,000 miles. That acceleration followed Tesla’s decision to remove in-vehicle safety monitors from most of its operations outside the San Francisco Bay Area.

Credit: Tesla

Tesla first launched Robotaxi service in Austin in June 2025 with safety drivers present. It later began fully unsupervised rides and expanded into Dallas, Houston, Miami, Orlando, and Tampa. The San Francisco Bay Area remains the exception, where a safety monitor still rides in the vehicle under California permitting rules.

The company has not released a city-by-city breakdown of the one million unsupervised miles.

The milestone arrived as Tesla began offering public Cybercab rides in Austin. The purpose-built vehicle has no steering wheel or pedals and is designed only for autonomous ride-hailing. Production versions joined the existing fleet of modified Tesla vehicles already operating in the service.

Tesla’s unsupervised mileage is growing at a double-digit weekly rate according to earlier company comments, yet its fleet size remains modest compared with established competitors. Waymo has accumulated more than 200 million fully autonomous rider-only miles. Tesla has described its own unsupervised operations as having recorded zero notable incidents in the period leading up to the July update.

The one-million-mile figure reflects Tesla’s shift from supervised testing to broader driverless service in multiple states. It also highlights the company’s strategy of using both existing Model Y vehicles and the new Cybercab to scale its network.

Credit: Tesla

Whether the rapid recent growth continues will depend on further city expansions, regulatory approvals, and the performance of the purpose-built Cybercab in everyday paid rides. Tesla has not specified how many of the latest miles involved the new vehicle versus the rest of the fleet.

The announcement underscores Tesla’s progress toward a larger robotaxi network while illustrating the remaining gap in total autonomous experience relative to longer-operating rivals.

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Tesla Robotaxi will be a 24/7 service: here’s when

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Credit: @AdanGuajardo/X

Tesla AI lead Ashok Elluswamy said this week that 24-hour Robotaxi service is close. Replying on X to a rider who wanted Cybercab trips all night, he wrote that the capability would arrive “next month or so” once “the next tech to merge on the v15 plan” is ready.

The comment landed on September 4, one day after Tesla opened public Cybercab rides in Austin. It is the clearest near-term timeline yet for overnight unsupervised operation. Tesla’s paid Robotaxi network currently runs from 6 a.m. to 10 p.m. seven days a week across Austin, Dallas, Houston, Miami, Orlando, and Tampa.

That 16-hour window is shorter than the 6 a.m. to 2 a.m. schedule the company used for much of the prior year.

Elluswamy did not name the specific feature or say whether the change would apply first to purpose-built Cybercabs, the existing Model Y fleet, or both. He also offered no city-by-city rollout list. The link to Full Self-Driving v15 is nevertheless significant.

Tesla has described v15 as a step-change architecture with seven parallel improvement tracks and roughly ten times more parameters than earlier builds. Early versions of that software already operate on the Robotaxi fleet and contain about 40 percent of the planned gains.

By July 2026, the unsupervised fleet had logged more than 380,000 miles across six cities in two states with what the company called an impeccable safety record and no notable incidents caused by the vehicles themselves. Tesla has repeatedly argued that camera-based end-to-end neural networks, rather than extra sensors, are the core of the solution.

Overnight service would test that claim in lower-light conditions and would also raise vehicle utilization, a key variable for Robotaxi unit economics. The company has already begun using public Superchargers at night and is building dedicated Robotaxi charging sites.

Riders have asked why software must change if the cars already drive in the dark. The practical answer appears to be reliability and scale: Tesla has held back mass expansion until more of the v15 stack is merged, citing the need for higher confidence before putting thousands of unoccupied vehicles on streets around the clock.

If the next module arrives on the timetable Elluswamy sketched, 24-hour service could begin in October 2026 in at least some markets.

That would mark a shift from a daytime-bounded pilot to a service that can run whenever demand exists, including the late-night hours that have so far remained out of reach.

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Tesla Full Self-Driving will now overtake manual driving to avoid disaster

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Credit: Tesla

Tesla is beginning to roll out Full Self-Driving Supervised v14.3.9 with a new active safety layer that can take control even when the driver is operating the car manually.

Tesla AI said the software can activate FSD on the driver’s behalf when an imminent collision is detected and Automatic Emergency Braking may not be enough. It may also engage if the system detects heavy distraction or an accidental FSD disengagement.

The capability is essentially Automatic Collision Evasion. However, unlike conventional AEB, which mainly applies the brakes in a straight line, this feature can use steering, braking, and acceleration together if the car calculates that stopping alone will not prevent impact and a safer path exists. The system may change lanes or move toward a shoulder when conditions allow, then continue driving after the immediate threat is handled rather than simply coming to a stop.

The intervention is meant as a last-resort safety net, not a replacement for attentive driving.

Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident

Tesla’s own description still frames FSD as supervised assistance. Secondary reports on internal release notes say the feature can fire while the car is being driven manually if cabin-camera monitoring suggests the driver is not sufficiently attentive, such as reaching toward the back seat, or if FSD appears to have been turned off unintentionally.

After the emergency maneuver, the car is expected to alert the driver and request a return to manual control.

The safety case is straightforward. Many collisions happen in the last second because a driver is looking away, fumbles a control, or faces an obstacle that braking cannot fully solve. A system that can both recognize that AEB is insufficient and execute a coordinated evasive path can reduce those remaining high-severity events.

Re-engaging after accidental disengagement also addresses a practical failure mode: a small steering nudge that drops FSD at the worst moment. The advantage is a background safety net that uses the same vision stack already running in v14, instead of leaving the car solely to emergency braking once the driver is no longer in command.

The feature still depends on FSD being enabled and, according to reports, an active FSD purchase or subscription. It does not make the vehicle unsupervised. Drivers remain responsible, and Tesla has not published how often the system is expected to intervene or how it will handle false positives.

If the rollout is conservative and the false-alarm rate stays low, the update is a meaningful step: FSD is no longer only a feature the driver turns on. In the rare moments when disaster is already forming, it can step in.

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