News
Porsche Taycan win against Tesla Model S is suspicious, says veteran drag racer
Just recently, motoring publication Top Gear posted a video comparing the Porsche Taycan Turbo S to the Tesla Model S Performance. The publication featured a drag race between the two vehicles which ended with the Taycan taking the win from the Model S. The quarter-mile race seemed to be a clean win for the Porsche, but according to a veteran drag racer, there are some aspects of the race that were, to say the least, suspicious.
Brooks of DragTimes has extensive experience on the drag strip, being the owner of vehicles like the McLaren 720S and the new Ford GT. With a garage filled with high-performance cars and innumerable straight-line races under his belt, Brooks knows a thing or two about drag racing. His experiences with his Model S P100D also make him a veteran Tesla owner who knows all the quirks of the all-electric sedan inside out when launching from a straight line.
With this in mind, the veteran drag racer noted that there seems to be several things that are wrong about the results of Top Gear‘s quarter-mile race between the Porsche Taycan Turbo S and the Tesla Model S Performance. The motoring publication listed the Model S’ 0-60 mph time at 2.68 seconds, its 0-100 mph at 6.46 seconds, and its quarter-mile time at 11.08 seconds at 124.0 mph. The DragTimes host noted that this immediately rings some alarm bells, as the Model S Performance is known to clock 10.6-second quarter-mile times regularly.
But it gets stranger. Looking at the figures listed by Top Gear after the two vehicles’ drag race, it appears that the publication basically copy-pasted the exact same performance figures of the Model S from a race against a Mercedes AMG E63S from 2017. This, according to Brooks, is highly suspicious, since the chances of a vehicle having the exact same 0-60 mph, 0-100 mph, quarter-mile time, and trap speed in two different drag races are incredibly thin.
Apart from this, the DragTimes host argued that the Model S which raced against the Taycan Turbo S did not seem to be in Launch Mode. This is because the Model S squats when Launch Mode is engaged, something that did not seem to happen in Top Gear‘s video. The motoring publication did not seem to engage the full capabilities of Ludicrous Plus Mode as well, as the graphics on the vehicle’s MCU and instrument cluster do not feature the same settings as a Model S with its maximum performance enabled.
Top Gear noted that the Porsche Taycan Turbo S completed the quarter-mile in 10.69 seconds, which is 0.39 seconds faster than the Model S’ 11.08-second quarter-mile time. Brooks noted that in drag races, a 0.39-second gap would usually correspond to about four car lengths. This is pretty odd since in the Top Gear video, the Taycan Turbo S was only one car length ahead of the Model S Performance when it crossed the quarter-mile mark.
If the DragTimes host’s observations are correct, then it means that Top Gear misrepresented the Tesla Model S in its recent comparative video against the Porsche Taycan Turbo S. This is unfortunate, as the two vehicles are actually neck-in-neck, and they do feature quarter-mile performance that can make an exciting drag race. The Porsche Taycan Turbo S is a great vehicle too, and its two-speed gearbox will likely give it an advantage over the Tesla Model S Performance at high speeds.
Simply put, the Porsche Taycan Turbo S is a worthy competitor that has the potential to win against a Raven Tesla Model S Performance with Launch Mode and Ludicrous Plus fair and square. Misrepresentations, whether intentional or not, only do Porsche an injustice. The Model S deserves better, and the Taycan Turbo S does too.
Watch Brook’s breakdown of Top Gear‘s Porsche Taycan Turbo S vs Tesla Model S Performance drag race in the video below.
News
Tesla crosses major Unsupervised Self-Driving milestone
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.
News
Tesla Robotaxi will be a 24/7 service: here’s when
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.
next month or so. the next tech to merge on the v15 plan will enable it.
— Ashok Elluswamy (@aelluswamy) September 4, 2026
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.
News
Tesla Full Self-Driving will now overtake manual driving to avoid disaster
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.
FSD Supervised v14.3.9 starting to roll out shortly
This release includes a new active safety feature set: FSD Supervised can now activate on your behalf when an imminent collision is detected and Automatic Emergency Braking (AEB) may not be enough.
It may also engage if we…
— Tesla AI (@Tesla_AI) September 4, 2026
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.