News
Tesla Model S vs Porsche Taycan comparison finally hits the nail on the head
For the longest time, the Tesla Model S and the Porsche Taycan have been compared in a manner that one would not necessarily be considered completely fair. Some would focus on the badge and build quality and automatically give the win to Porsche, while some would focus on tech and driver-assist features and give the win automatically to Tesla. But giving the crown of the best luxury EV on the market today is no joke, and comparing these two vehicles requires a deep dive.
This is something that Roadshow was actually able to accomplish recently. In a video shared on its YouTube channel, the motoring publication compared the Model S and the Taycan on five fronts: Range and Charging, Acceleration, Handling, Design, and Price and Value. Using this metric, the publication was able to reach a result that is actually very fair to both vehicles.
First up is range and charging, and in this sense, there is really no contest. Tesla’s years of work on battery research has paid off in spades, and this is shown by the Model S’ nearly 400-mile range. The Supercharger Network is icing on the cake, providing the Model S with a convenient way to charge its batteries during road trips. The Taycan has a tendency to exceed its EPA range figures, and it’s supported by a vast charging network too. But compared to Tesla’s raw range and Supercharger Network, the gap is simply too big. One win for Tesla.
Acceleration is something that both vehicles excel at. In this sense, Roadshow noted that the top-tier versions of the two premium EVs, the Model S Performance and the Taycan Turbo S, are both insanely quick. The Taycan Turbo S is rated by Porsche with a 0-60 time of 2.6 seconds, but tests from publications have recorded the vehicle hitting 2.4 seconds instead. This was originally faster than the Model S Performance’s 2.5 seconds, but after Tesla’s Cheetah Stance Launch Mode update, the flagship sedan could now hit 60 mph in 2.3 seconds instead. That’s another win for Tesla, but only just.
Things change when handling is discussed. While both are large vehicles, Roadshow noted that the Taycan simply feels much better to throw around corners. This is where Porsche’s pedigree comes to light as a veteran sports car maker, since the Taycan simply feels a lot lighter than its over 5,000-pound weight. The Model S Performance handles great too, but when thrown into the same corners at the same speed as the Taycan, the Tesla’s large size simply becomes more evident. The Taycan wins this round.
Design is also something that was given to the Porsche. After all, the Model S has pretty much retained its design since its first iteration that was rolled out eight years ago. Save for a facelift, the Model S is still the same car that broke barriers back in 2012. Thus, the Taycan simply feels much newer and more fresh in this sense. The fact that the Taycan’s interior is filled to the brim with premium materials worthy of its price also adds to its edge against the Tesla Model S.
But when it comes to the price and value of the two vehicles, it is difficult not to be impressed by the Tesla Model S. Roadshow opted to compare the Taycan 4S and the Model S Long Range, which are the more conservatively priced and specced versions of the two cars. But even then, a fully loaded Model S Long Range is still cheaper than a Taycan 4S that is so basic, it doesn’t even have adaptive cruise control. This, ultimately, proves that eight years on, Tesla’s flagship sedan still has a lot of fight left in it, and it’s not about to give up its crown easily either.
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.
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.
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.
Tesla crosses major Unsupervised Self-Driving milestone
Tesla Robotaxi will be a 24/7 service: here’s when
