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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.
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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.
Elon Musk
SpaceX’s next trillion dollar bet has nothing to do with rockets, Musk tells staff
Elon Musk told SpaceX staff AI revenue will soon dwarf rockets and Starlink combined entirely.
Elon Musk told SpaceX employees this week that artificial intelligence, not rockets, will soon carry the company’s revenue. In a roughly 29 minute internal address posted on SpaceX’s X account on Tuesday, Musk said AI revenue will pass every other line of business at SpaceX “probably in September” and pull further ahead by the fourth quarter.
The numbers he gave are specific. SpaceX currently runs 1.4 gigawatts of AI compute capacity. Musk wants that at 10 gigawatts by the end of 2027, a jump he tied directly to revenue: “if we bring 10GW of AI online by the end of next year, it will be $300 billion to $500 billion a year in revenue.” He called those “big numbers,” which undersells a projection larger than what most countries produce in a year.
We made rockets reusable and are rebuilding the internet in space. The next challenge: making life multiplanetary and understanding the true nature of the universe
Watch @ElonMusk deliver a company update to @SpaceX employees pic.twitter.com/5c8rxoCQfu
— SpaceX (@SpaceX) August 11, 2026
Musk went further on where AI fits into SpaceX’s future. “Probably in four or five years, AI will be 99% of the value of SpaceX,” he told staff, adding that digital intelligence would eventually run “a trillion times” ahead of biological intelligence as computing scales. He tied that growth to the company’s founding mission, telling employees “we must win on AI, because the future is overwhelmingly AI and robots,” with the payoff meant to help fund Starship and a Mars program that increasingly runs through Terafab, the joint Tesla, SpaceX and xAI chip plant.
Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry
None of this is entirely new territory. SpaceX told investors much the same story during its first earnings call as a public company on August 4, where Musk moved the company’s $1 trillion revenue target up a year to 2030 and said Starlink could someday carry a majority of the world’s internet. What the all hands video adds is a hard deadline and a specific power figure Musk had not given publicly before, along with a franker pitch to his own workforce that AI, not launch cadence, is now the thing SpaceX is betting its future on.
The AI revenue itself is not coming from SpaceX training its own models. It is largely Starlink acting as the network layer for xAI’s workloads, plus SpaceX renting out compute capacity directly, the same approach behind the roughly $16 billion the company spent on AI infrastructure in a single quarter.
Musk closed the video with a pitch aimed at recruiting and retention rather than investors, telling employees that anyone who helps SpaceX win the AI race will eventually get the chance to go to the moon or Mars themselves. Whether SpaceX can turn 1.4 gigawatts into 10 in seventeen months is the more immediate question, and one that will show up in quarterly numbers well before anyone leaves Earth.
In a new note to investors on Tuesday, Morgan Stanley analyst Andrew Percoco said that Tesla has one big financial question to answer for investors regarding its Robotaxi rollout, Full Self-Driving software, and Optimus.
Percoco said in the note that, for the most part, investors are still very positive about the direction the company is headed. However, there are some things the firm would like to see, and they have to do with financials.
Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue
Tesla bulls are more than convinced that the company’s Full Self-Driving software is proof it can develop physical AI. Financially, however, there are still some questions, especially on elevated spending, which CEO Elon Musk said would occur as the company works to roll out Robotaxi faster and continue developing its Optimus robot.
The latter two are where Tesla will have to prove progress to investors, as Percoco writes that both projects “will require clearer evidence that Robotaxi is scaling and more tangible Optimus proof points to support the ROI on elevated capex.”
Percoco said the second quarter earnings call did not change his long-term thesis of where Tesla is positioned in the AI race, which is out in front. However, there are concerns that weaker gross margins and higher R&D spend will stress financials, and that has “sharpened our (and investors’) focus on measurable progress across Robotaxi and Optimus.”
Additionally, Robotaxi still needs to be proven with more operation in existing cities while maintaining safety but improving how many rides it gives in any given time, he said. For Optimus, Percoco wrote that he is “still looking for evidence beyond commentary around SOP.”
Morgan Stanley put Percoco in charge of covering Tesla after long-time analyst Adam Jonas transitioned to the automotive side.
Currently, Morgan Stanley has a $415 price target on Tesla and a ‘Hold’ rating on the stock. It is trading at around $330 at the time of publication, which was 2:30 P.M. on the East Coast.
SpaceX’s massive investment in AI will make it a big winner, Argus Research said after the company’s successful earnings call last week.
The firm also upgraded shares to a Buy from Hold and set a $160 price target.
SpaceX (NASDAQ: SPCX) is currently recovering from its heavy AI infrastructure investments, as it spent nearly $16 billion in Q2 alone. The company did this primarily by monetizing high-demand GPU compute capacity at a much faster pace than traditional data center economics would suggest.
Company CFO Bret Johnsen said that SpaceX would be able to pay back anything on new deployments within a year.
There are plenty of ways the company can do this:
Leasing excess compute capacity through contracts
SpaceX has already built Colossus and Colossus II, largely for its own model training. However, much of that capacity is already rented out to third parties. It already has major deals with Anthropic, Google, and Reflection AI. These partnerships are adding billions per month to SpaceX’s spreadsheet.
High utilization driven by industry-wide scarcity
The demand for advanced AI training and inference capacity continues to exceed what is available for use. SpaceX can fill new racks quickly after they come online, so the capital deployed converts into revenue with minimal idle time.
Additionally, management and outside observers have described the new compute capital as behaving more like a cost-of-goods-sold than traditional multi-year capex, especially because of this rapid monetization pattern.
Capacity has already scaled from ~0.4 GW a year to 1.4 GW annually by the end of Q2. There are targets of more than 2 GW by year-end.
High incremental margins on the rental business once capacity is online
GPU cloud providers often operate at strong gross margins. SpaceX can monetize capacity that was already partially built or can be added efficiently. This means that incremental EBITDA margins on the rental revenue are usually high. This accelerates cash recovery relative to the gross capital outlay.
Parallel monetization of its own AI software and applications
Beyond pure infrastructure rental, SpaceX also generates revenue from Grok through subscriptions and usage, from X through ads, data, and other related services, enterprise APIs, and the planned integration of the Cursor coding tools acquisition.
These application layers ride on the same compute infrastructure and provide additional high-margin streams that could offset build-out costs. AI-segment revenue overall rose sharply to about $2.6 billion in Q2, according to Motley Fool. This was driven primarily by the infrastructure contracts, but the software side is also partially responsible.
Efficient, large-scale deployment and vertical integration advantages
SpaceX has emphasized the rapid construction of power and cooling infrastructure and favorable cost-per-megawatt economics relative to industry benchmarks in some disclosures.
Combined with its ability to scale capacity aggressively and the fact that many contracts start generating revenue within months of capacity coming online, the effective payback compresses dramatically compared with more conventional multi-year data-center projects.
SpaceX’s dominant near-term recovery path will turn the AI clusters into a hyperscale-style compute rental business for other leading AI companies while still using a portion for internal models.
SpaceX’s next trillion dollar bet has nothing to do with rockets, Musk tells staff
Tesla has one big financial question to answer for investors: Morgan Stanley
