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Porsche Taycan’s repeatable performance claims put to the test by veteran drag racer

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When Porsche launched the Taycan last year, its message was clear. It’s an all-electric performance car built for the track. You can take it with a battery half charged and you’ll still get the same level of performance you’d expect at full charge. At least that’s what Porsche promises.

DragTimes YouTube channel host and Tesla owner Brooks Weisblat recently put the Taycan Turbo’s repeatable performance claim to a real-world test. He took a Taycan Turbo and the more powerful Turbo S out on the track to see how they would perform launching from 0 to 60 mph and covering the 1/4 mile.

Weisblat specifically asked the engineers at Champion Porsche in Pompano Beach, FL to have both cars ready at full charge. However, while the Turbo had a 91% charge when he arrived, while the Turbo S was only at 57%. This presented a unique opportunity to test just how well the vehicles performed with such discrepancy in their battery levels.

At just a little bit more than half charge, the $185,000 Turbo S went from 0 to 60 mph in 2.67 seconds and ran a quarter-mile at 124 mph. It’s impressive for an all-electric vehicle but not so much for one housing the world’s first two-speed gearbox in an electric car.

“I kind of expected it to be a little better especially given it having the transmission,” Weisblat says. “I was expecting track speeds near 130 mph. The launch I wasn’t so sure because Porsche’s claiming it does 0 to 60 in 2.8 seconds.”

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Previous testing done by DragTimes shows the Tesla Model S with a 96 percent charge can go from 0 to 60 mph in 2.45 seconds. That’s a couple of tenths of a second faster than the Turbo S, which has acceleration and speed advantages due to its two-speed transmission.

The Turbo, which has 90 less horsepower than the Turbo S, went from 0 to 60 mph at 2.8 seconds. It’s not as fast as the Turbo S but it’s nothing to scoff at. But here’s the kicker. After the first 60 mph, the Turbo S didn’t have much of an advantage over the less powerful Turbo. If the state of charge doesn’t matter as Porsche says, the Turbo should have at least similar or less performance.

But Weisblat’s testing shows the Turbo at 91% charge went from 60 to 100 mph in 8.41 seconds and took the 1/4 mile at 127 mph. That’s a whole 3 mph faster than the Turbo S, which was at 56% charge when testing began. Had both cars been raced against each other, the Turbo would have won hands down over the Turbo S. Weisblat also says that both Turbo and Turbo S used up about 2% of the battery after each 1/4 mile.

“State of charge does matter with the Porsche. There’s no question about it. Because the Taycan Turbo S sitting at 56 percent is tracking at 124 mph. The Turbo at 91 percent is going 3 mph faster. For those of you who don’t know about road racing or drag racing, that is a significant difference,” he said.

The results would have been different had both cars been charged fully. Weisblat estimates the Turbo S could go the 1/4 mile at 130 mph and launch from 0 to 60 mph at around 2.5 seconds so that it’s right in line with the Tesla Model S. However, he believes that the Turbo S would further drop to 7 seconds once it goes from 60 to 130 mph, just up to par with a Lamborghini Huracan. If so, he says the Model S could be “in trouble,” at least when you take it down to the race track.

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To maintain these numbers, Porsche has to keep the Taycan’s battery at optimal temperatures using a unique battery thermal management system. Unfortunately, because the car relies purely on electricity, the Taycan uses up extra energy from the battery just to maintain its energy-intensive temperature control system.

It’s a double-edged sword, especially for an electric vehicle. Porsche had to sacrifice a few things in exchange for performance. A lot of people weren’t happy to hear that the EPA gave the Taycan Turbo S a range rating of 192 miles. The Taycan Turbo didn’t do much better at 201 miles, which is 182 whole miles less than the 373 miles of the Model S Long Range.

But then again, the Taycan isn’t exactly made for most people. In fact, with a six-figure price tag and the Porsche logo on its hood, it’s not even made for mainstream EV buyers. And it’s a good thing for the electric car market as a whole.

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SpaceX wants to catch Starship for launch 14, Elon Musk says

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Credit: SpaceX

Just hours after Starship Flight 13 achieved a successful soft splashdown of its upper stage in the Indian Ocean on July 24, Elon Musk announced an ambitious next step for the company’s next launch of the rocket.

“Unless we discover problems after mission data review, SpaceX will attempt to catch the ship with the tower on [the] next flight,” the SpaceX CEO posted on X on Friday.

That “next flight” is expected to be Flight 14. The plan involves returning the Starship upper stage, commonly called the “ship,” to the Starbase launch tower in Texas and catching it mid-air using the same mechanical “chopsticks” arms that have already proven themselves with the Super Heavy booster.

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A successful catch would mark the first time an orbital-class upper stage has been recovered this way, advancing SpaceX’s goal of full and rapid reusability for the entire vehicle.

SpaceX has already demonstrated the tower-catch technique multiple times with Super Heavy. The first successful catch came on Flight 5 in October 2024, when Booster 12 was plucked from the sky by the Mechazilla arms. Subsequent flights, including those involving Boosters 14 and 15, repeated the feat. Several of those recovered boosters were later inspected, refurbished, and flown again, proving the system’s viability for quick turnaround.

Traditional reusable rockets, such as SpaceX’s own Falcon 9 or Blue Origin’s New Shepard, land on legs either on land or droneships. Rocket Lab has recovered its small Electron first stages by helicopter, but those are far lighter vehicles.

SpaceX Starship just nailed something it’s never done before

The China Academy of Launch Vehicle Technology (CALT), a subsidiary of the China Aerospace Science and Technology Corp. (CASC), completed a catch of its booster on July 10. They are the only entity besides SpaceX to attempt and complete the feat.

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Flight 13 provided encouraging data. The ship executed a controlled reentry, flipped, and soft-landed intact in the ocean after deploying Starlink satellites, offering the first clear post-splashdown views of an undamaged heat shield. The Super Heavy booster, meanwhile, experienced a harder splashdown in the Gulf of Mexico.

Musk has previously stressed that ship catches would only follow multiple successful soft ocean landings to minimize risk of debris over land.

If Flight 14 succeeds, SpaceX would take a major stride toward routine, rapid reuse of both stages—critical for lowering launch costs and supporting ambitious plans for lunar and Mars missions. For now, teams are reviewing the Flight 13 data. Should everything check out, the next Starship flight could deliver one of the most spectacular recoveries in aerospace history.

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Tesla to open source Model S and Model X designs and software

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Credit: Tesla

In a move echoing its earlier commitment to open innovation, Tesla CEO Elon Musk announced recently that the company plans to make the design and software of its Model S and Model X fully open source.

This follows the same approach Tesla took with its original Roadster, releasing all available design, engineering, and diagnostic materials in November 2023 so that “whatever we have, you now have.”

The Model S, introduced in 2012, was Tesla’s first mass-produced vehicle and a groundbreaking luxury electric sedan. It offered impressive range, rapid acceleration, and over-the-air software updates that redefined expectations for electric cars.

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The Model X, launched in 2015, built on that foundation as a high-performance electric SUV notable for its distinctive falcon-wing doors, spacious interior, and advanced safety features. Both models served as flagships that helped establish Tesla as a leader in the EV industry and popularized long-range battery-electric vehicles.

Production of the Model S and Model X was wound down earlier in 2026, with manufacturing ending in the second quarter. Tesla redirected the Fremont factory space previously used for these vehicles toward higher-priority projects, including Optimus humanoid robots and the Cybercab autonomous vehicle.

By the time of Musk’s open-source announcement, custom orders had closed and only remaining inventory was available.

Open-sourcing the designs and software offers several clear advantages. Owners of these aging but still capable vehicles gain better access to technical documentation, diagnostic tools, and software resources, making independent repairs and modifications easier and more affordable.

Independent repair shops and third-party specialists can support the large existing fleet without relying solely on Tesla’s service network. Enthusiasts and engineers can study real-world implementations of Tesla’s battery, powertrain, and software systems, potentially accelerating broader industry progress in electric mobility.

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The step aligns with Tesla’s 2014 patent pledge and its overall mission to advance sustainable transport by sharing hard-won knowledge rather than locking it behind proprietary walls.

By releasing these materials now that the models have left production, Tesla ensures continued support for its early adopters while freeing internal resources for future technologies. The open-source release of the original Roadster already enabled simulations, community projects, and deeper technical understanding.

Extending that practice to the Model S and Model X should deliver similar benefits on a larger scale, helping keep these influential vehicles relevant and repairable for years to come

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Tesla flexes incredible Robotaxi metric that skeptics will hate

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Credit: Tesla

Tesla flexed one incredible Robotaxi metric during the Q2 Earnings Call that skeptics have to hate to hear. The company’s platform has already driven more than 380,000 miles of unsupervised ride-hailing across several states with no notable incidents.

During the company’s Q2 Earnings Call on Wednesday, Vice President of AI, Ashok Elluswamy, said:

“First of all, I’d like to state that the Robotaxi program has been operating extremely well. Especially in terms of safety, the program has had an impeccable safety record. We have driven more than 380,000 miles of unsupervised Robotaxi, now across six cities in two different states. We have had zero notable incidents. Any reports have been of other actors impacting us when we were stationary. I like to emphasize how safe the operation has been so far. Zero notable incidents over 380,000 miles.”

Elluswamy’s claim over Robotaxi miles is a significant milestone for Tesla in the grand scheme, especially considering this is a sizeable number of miles without any incident.

Tesla’s self-driving approach is much different than that of other companies. Tesla has maintained that vision is the only thing needed to have a solid and effective self-driving suite. Many self-driving companies utilize things like LiDAR, sensors, and other elements to improve performance, but Elluswamy sent a jab at those who believe it’s needed.

“Historically, the so-called experts have always claimed that you need LiDARs, radars, HD maps, and the entire kitchen sink to drive safely. Here we show that such is not true. You can have safe, comfortable, and affordable autonomy with just cameras. This record should be a huge validation of Tesla’s entire AI approach.”

The feat of accumulating this many miles without any driver behind the wheel is impressive. The thing is, Tesla is also doing this across several different locations, with varying traffic rules, pedestrian levels, weather patterns, and other important factors.

While Tesla is not ready to roll out an unsupervised platform completely, it is a slow but steady indication that the company is well on its way to figuring things out.

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The company’s attitude toward expansion is slow, safe, and controlled, and despite this huge milestone, it will still be some time until we see Tesla truly unleash unsupervised rides more aggressively.

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