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Porsche Taycan’s repeatable performance claims put to the test by veteran drag racer
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.”
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.
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.
SpaceX confirmed today that it has officially signed its third massive compute deal, providing compute at its Colossus data center in Southaven, Tennessee.
Reflection AI will gain immediate access to NVIDIA GB300 chips at SpaceX’s Colossus 2 data center. In return, Reflection will pay SpaceX $150 million per month starting on July 1, with total payments reaching approximately $6.3 billion if the contract runs through its duration, which is until 2029. Either party can terminate the agreement with 90 days’ notice after the initial three-month period.
CNBC first reported the deal.
🚨 SpaceXAI has agreed to a new compute deal with Reflection AI.
Reflection gets access to NIVIDIA GB300s, and will pay $150M per month to SpaceXAI for the compute. pic.twitter.com/bNPare8U5u
— TESLARATI (@Teslarati) June 22, 2026
This latest partnership highlights SpaceX’s strategy of commercializing its massive Colossus supercomputing infrastructure, originally developed to power Elon Musk’s Grok AI models. The company has rapidly expanded its customer base in the AI sector following its February 2026 merger with xAI, a transaction that valued the combined entity at $1.25 trillion.
SpaceX has previously signed significant compute deals with other major players.
It granted Anthropic exclusive access to the full capacity of its Colossus 1 data center, which exceeds 300 megawatts and includes over 220,000 NVIDIA GPUs. Details from SpaceX’s IPO filings indicate Anthropic will pay $1.25 billion per month through May 2029, potentially generating around $45 billion over the term of the deal.
Additionally, Google agreed to pay SpaceX $920 million per month for compute capacity from October 2026 through June 2029. This 32-month period will provide Google access to roughly 110,000 NVIDIA GPUs, along with supporting processors and memory. Capacity ramps up through September at a reduced fee, with termination options after the first year.
SpaceXA also established arrangements for computing power with Cursor, an AI coding startup. SpaceX acquired them in a $60 billion all-stock deal.
These arrangements position SpaceX’s collective position as an AI infrastructure powerhouse with high-margin revenue potential. The Google deal alone could generate nearly $29.5 billion over its term, while the Reflection contract adds another $6.3 billion.
Combined with the Anthropic arrangement, SpaceX stands to realize tens of billions in revenue from compute leasing in the coming years, which diversifies beyond SpaceX’s traditional rocket launches and Starlink operation.
The deals underscore growing demand for advanced AI training and inference capacity amid chip shortages and surging model development needs. Reflection, valued at $25 billion and focused on “American open intelligence” with government and national security ties, cited recent restrictions on closed models as validation for open-source approaches.
For SpaceX, the partnerships transform capital-intensive data centers into flexible revenue sources while supporting its broader AI ambitions after the company has gone public.
It is safe to say SpaceX won’t be going for electric rockets anytime soon.
In a characteristically blunt reply on X, SpaceX frontman Elon Musk stated, “Unfortunately, electric rockets are impossible,” following reports that MSCI had assigned SpaceX its lowest possible ESG rating of CCC.
The assessment, issued just this past week, coinciding closely with SpaceX’s public market debut, placed the company on par with nations like Russia in sustainability scoring and cited significant risks in environmental, social, and governance areas.
MSCI flagged SpaceX’s exposure to rocket emissions and other operational impacts, alongside governance concerns such as concentrated control by Musk and limited shareholder protections. Musk’s terse comment directly addressed the environmental pillar, underscoring a core physical constraint that ESG frameworks often overlook when evaluating high-thrust industries.
Unfortunately, electric rockets are impossible
— Elon Musk (@elonmusk) June 21, 2026
Electric propulsion systems do exist and are widely used in space. Ion thrusters and Hall-effect thrusters accelerate ionized propellant, typically xenon or krypton, using electric fields, achieving very high specific impulse, often exceeding 3,000 seconds compared to roughly 300–450 seconds for chemical rockets.
This efficiency makes them ideal for satellite station-keeping, orbit raising, and deep-space missions where low thrust over long durations is sufficient. SpaceX’s own Starlink satellites employ electric propulsion for these purposes.
However, launching from Earth’s surface demands something entirely different: enormous thrust delivered rapidly to overcome gravity and atmospheric drag. A typical orbital-class booster must generate thrust far exceeding its weight, often in the millions of Newtons within seconds.
Chemical rockets achieve this through exothermic combustion of dense propellants, producing high-mass-flow, high-velocity exhaust. Electric systems, by contrast, expel very small amounts of mass at extremely high speeds. Generating equivalent thrust would require impractical onboard power levels, massive energy storage or generation systems, and prohibitive added mass, rendering the approach infeasible with current or near-term technology.
Musk has previously expressed a similar sentiment, noting a desire for electric orbital rockets while acknowledging the inescapable requirements of Newton’s third law and energy delivery. The distinction is clear: electric propulsion excels once a vehicle is already in space; it cannot replace the high-thrust chemical phase required to reach orbit from the ground.
The episode illustrates broader critiques of ESG ratings. Proponents argue they incentivize better risk management and long-term sustainability. Detractors, including Musk—who has previously called ESG a “scam”—contend that such metrics can penalize essential activities when no practical alternative exists, potentially discouraging innovation in sectors like space access.
Elon Musk dubs the S&P 500 ESG as “outrageous scam” after Tesla gets booted from index
SpaceX has sought to mitigate launch-related impacts through reusability: Falcon 9 boosters have flown more than 30 times in some cases, dramatically lowering the manufacturing and emissions burden per kilogram delivered to orbit. Starship’s design further emphasizes rapid reusability and methane propellant, which can theoretically be produced via sustainable pathways.
Ultimately, Musk’s remark serves as a reminder that certain engineering realities persist regardless of scoring systems. As humanity expands its presence in space for communications, science, and exploration, balancing genuine environmental progress with technological necessity remains a central challenge.
ESG frameworks may evolve, but the fundamental limits of electric launch propulsion are unlikely to change soon.
Tesla just trademarked ‘MEGAPOD’ with the United States Patent and Trademark Office (USPTO), its latest move in what seems to be a hint that the company is incredibly focused on its AI efforts and storage needs as compute increases.
The application carries serial number 99893717 and lists the applicant as Tesla, Inc., located at 1 Tesla Road, Austin, Texas 78725.
The filing remains in ‘live pending’ status, and it is a new application waiting for assignment to an examining attorney. It has not yet been published or registered.
Tesla just trademarked MEGAPOD
Summary:
“Modular data center hardware systems for artificial intelligence computing, comprised of computer servers, computer hardware for artificial intelligence processing, computer networking hardware, electrical power distribution units, and… pic.twitter.com/3l85DsKadl— Robin (@xdNiBoR) June 19, 2026
According to the official goods and services description in the application, Tesla describes ‘MEGAPOD’ as:
“Modular data center hardware systems for artificial intelligence computing, comprised of computer servers, computer hardware for artificial intelligence processing, computer networking hardware, electrical power distribution units, and cooling systems, sold as a unit; self-contained modular computing hardware systems for artificial intelligence workloads; integrated computer hardware platforms for artificial intelligence computing, namely, enclosures containing computer hardware, power distribution hardware, and cooling hardware, sold as a unit; downloadable software for monitoring, managing, optimizing, and regulating modular artificial intelligence computing hardware systems.”
This description specifies complete, self-contained modular units that integrate servers and specialized AI processing hardware with networking components, power distribution, and cooling systems. It also includes associated downloadable software for oversight and optimization of these systems. The language emphasizes hardware sold “as a unit” and enclosures that combine the necessary elements for AI computing workloads.
Tesla has an established history of developing and commercializing modular hardware systems. Its Megapack product line, for example, consists of utility-scale battery energy storage systems designed as containerized units for grid applications. The MEGAPOD filing follows a similar pattern of protecting a name for modular, integrated hardware platforms, this time focused on artificial intelligence computing infrastructure.
This could be an early move, especially as Tesla did not have trademark rights to the word ‘Cybercab,’ the name of its self-driving, ride-hailing-focused vehicle.
Trademark applications of this type allow companies to secure priority rights to a name for defined categories of goods and services. The USPTO examines applications for compliance with legal requirements, including distinctiveness and absence of conflicts with prior marks. If the application proceeds successfully through examination, publication, and any opposition period, it could result in a federal trademark registration providing nationwide protection. This is what Tesla’s obvious intention is with ‘MEGAPOD.’
Public reports and analysis suggest MEGAPOD could represent modular, container-style AI computing pods designed for easy deployment. These would bundle servers, AI accelerators, power systems, and cooling into self-contained units suitable for distributed AI workloads. This approach aligns with Tesla’s announced AI compute strategy.
In March 2026, Elon Musk outlined plans for “Digital Optimus” (also referred to as Macrohard), a joint Tesla-xAI project for AI agents capable of handling complex digital tasks. The plans include running these agents on Tesla’s AI4 hardware in parked vehicles as well as dedicated compute units installed at Supercharger stations, which collectively offer substantial unused electrical capacity.
What is Digital Optimus? The new Tesla and xAI project explained
A modular hardware platform like the one described in the ‘MEGAPOD’ filing would support scalable, rapid deployment of such distributed compute resources. It could complement Tesla’s other AI infrastructure efforts, including the Dojo supercomputer used for training models and the development of AI systems for autonomous driving and robotics, by enabling edge or regional AI inference without reliance on traditional centralized data centers.
SpaceX confirms third massive compute deal at Colossus data center
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