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Porsche Taycan win against Tesla Model S is suspicious, says veteran drag racer

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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. 

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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. 

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Watch Brook’s breakdown of Top Gear‘s Porsche Taycan Turbo S vs Tesla Model S Performance drag race in the video below. 

Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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Elon Musk

Elon Musk teases crazy outlook for xAI against its competitors

Musk’s response was vintage hyperbole, designed to rally supporters and dismiss doubters, something his responses on social media often do.

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Credit: NVIDIA

Elon Musk has never been one to shy away from crazy timelines, massive expectations, and outrageous outlooks. However, his recent plans for xAI and where he believes it will end up compared to its competitors are sure to stimulate conversation.

In a bold and characteristic response on X, Elon Musk fired back at a recent analysis that positioned his AI venture, xAI, as lagging behind industry frontrunners.

The post, from March 14, came as a direct reply to forecaster Peter Wildeford’s assessment, which drew from benchmarks and reporting to rank AI developers.

Wildeford placed Anthropic, Google, and OpenAI in a virtual tie at the top, with xAI and Meta trailing by about seven months. Chinese players like Moonshot, Deepseek, zAI, and Alibaba were estimated to be nine months behind, while France’s Mistral lagged by about a year and a half.

Musk’s response was vintage hyperbole, designed to rally supporters and dismiss doubters, something his responses on social media often do.

He claimed xAI would “catch up this year,” meaning by the end of 2026, erasing that seven-month deficit against the leaders. But he didn’t stop there.

Musk escalated his vision to 2029, predicting xAI would “exceed them all by such a long distance” that observers would need the James Webb Space Telescope, NASA’s orbiting observatory stationed about 930,000 miles from Earth, to spot whoever lands in second place. This analogy underscores Musk’s confidence in xAI’s trajectory, implying an astronomical lead that could redefine the AI landscape.

Breaking down these claims reveals Musk’s strategic optimism. First, the short-term catch-up: xAI, launched in 2023, has already released models like Grok, but recent benchmarks, including those for Grok 4.2, have shown it falling short in capabilities compared to rivals.

Anthropic’s Claude series, Google’s Gemini, and OpenAI’s GPT models dominate in areas like reasoning, coding, and multimodal tasks. Musk’s assertion suggests aggressive scaling in compute, talent, or architecture, perhaps leveraging xAI’s ties to Tesla’s Dojo supercomputers or Musk’s vast resources, to close the gap swiftly.

The longer-term dominance by 2029 paints an even more audacious picture. Musk envisions xAI not just parity but supremacy, outpacing competitors in innovation speed and model sophistication.

This could involve breakthroughs in energy-efficient training, real-world integration, like Tesla’s robotics, or ethical AI alignment, aligning with Musk’s stated goal of “understanding the universe.”

Critics, however, point to parallels with Tesla’s Full Self-Driving delays; one reply highlighted Musk’s 2023 promise of FSD readiness. Musk has made this promise for many years, and although the system has been strong and improving, it is still a ways off from the completely autonomous operation that was expected by now.

Tesla Full Self-Driving v14.2.2.5 might be the most confusing release ever

Musk’s comment highlights the intensifying U.S.-centric AI race, with xAI challenging the “three-way” dominance noted by Wharton professor Ethan Mollick, whom Wildeford quoted. As geopolitical tensions rise—evident in the Chinese firms’ lag—Musk’s tease could spur investment and talent wars.

Yet, it also invites scrutiny: Will xAI deliver, or is this another telescope-needed mirage? In an industry where timelines slip but stakes soar, Musk’s words keep the spotlight on xAI’s ambitious path forward.

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Tesla Terafab set for launch: Inside the $20B AI chip factory that will reshape the auto industry

Tesla set to launch “Terafab Project: A vertically integrated chip fabrication effort combining logic processing, memory, and advanced packaging.

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Tesla is making one of the boldest bets in its history. On March 14, Elon Musk posted on X that the “Terafab Project launches in 7 days,” pointing to March 21, 2026 as the start date for what he has described as a vertically integrated chip fabrication effort combining logic processing, memory, and advanced packaging.

Tesla first confirmed Terafab on its January 28, 2026 earnings call, where Musk told investors the company needs to build a chip fabrication facility to avoid a supply constraint projected to materialize within three to four years. But the seeds were planted even earlier. At Tesla’s annual general meeting last year, Musk warned that even in the best-case scenario for chip production from their suppliers, it still wouldn’t be enough, and declared that building a “gigantic chip fab” simply had to be done.

While there has been no official announcement on where Tesla plans to break ground on the massive Terafab, all signs point to the North Campus of Giga Texas in Austin.

Months of speculation has surrounded Tesla’s North Campus expansion at Giga Texas, where drone footage captured by observer Joe Tegtmeyer revealed massive construction site preparation just north of the existing factory on a scale that rivals the original Giga Texas footprint itself.

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The project is projected to produce 100–200 billion AI and memory chips annually, targeting 100,000 wafer starts per month, at an estimated cost of $20 billion. Tesla is targeting 2-nanometre process technology and anticipated to be the most advanced node currently in commercial production. Dubbed the Tesla AI5 chip, the chip will pack 40x–50x more compute performance and 9x more memory than AI4, and will be among the first products Terafab factory is set to produce. This highly optimized, and massively powerful inference chip is designed to make full self-driving (FSD) and Tesla’s Optimus robots faster, safer, and with full autonomy.

tesla-optimus-pilot-production-line

(Credit: Tesla)

This is where Terafab becomes a genuine game-changer. If Tesla successfully builds a 2nm chip fab at scale, it becomes one of only a handful of entities that’s capable of producing AI silicon in-house, with competitive implications that extend far beyond Tesla’s own vehicles, and potentially positioning Tesla as a chip supplier or licensor to other industries.

The next-gen Tesla AI chips will power advancements in Full Self-Driving software, the Cybercab Robotaxi program, and the Optimus humanoid robot line. Musk’s projections for Optimus require chip volumes that no existing external supplier can commit to on Tesla’s timeline.Competitors like Waymo and GM’s Cruise remain dependent on third-party silicon, leaving them exposed to the same supply chain vulnerabilities Tesla is now working to eliminate entirely.

The Terafab launch this week may not mean a factory opens its doors overnight, but it signals Tesla is serious about owning the entire AI stack, from software to silicon.

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What is Digital Optimus? The new Tesla and xAI project explained

At its core, Digital Optimus operates through a dual-process architecture inspired by human cognition.

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Credit: Grok

Tesla and xAI announced their groundbreaking joint project, Digital Optimus, also nicknamed “Macrohard” in a humorous jab at Microsoft, earlier this week.

This software-based AI agent is designed to automate complex office workflows by observing and replicating human interactions with computers. As the first major outcome of Tesla’s $2 billion investment in xAI, it represents a powerful fusion of hardware efficiency and advanced reasoning.

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At its core, Digital Optimus operates through a dual-process architecture inspired by human cognition.

Tesla’s specialized AI acts as “System 1”—the fast, instinctive executor—processing the past five seconds of real-time computer screen video along with keyboard and mouse actions to perform immediate tasks.

xAI’s Grok model serves as “System 2,” the strategic “master conductor” or navigator, providing high-level reasoning, world understanding, and directional oversight, much like an advanced turn-by-turn navigation system.

When combined, the two can create a powerful AI-based assistant that can complete everything from accounting work to HR tasks.

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The system runs primarily on Tesla’s low-cost AI4 inference chip, minimizing expensive Nvidia resources from xAI for competitive, real-time performance.

Elon Musk described it as “the only real-time smart AI system” capable, in principle, of emulating the functions of entire companies, handling everything from accounting and HR to repetitive digital operations.

Timelines point to swift deployment. Announced just days ago, Musk expects Digital Optimus to be ready for user experience within about six months, targeting rollout around September 2026.

It will integrate into all AI4-equipped Tesla vehicles, enabling parked cars to handle office work during downtime. Millions of dedicated units are also planned for deployment at Supercharger stations, tapping into roughly 7 gigawatts of available power.

Digital Optimus directly supports Tesla’s broader autonomy strategy. It leverages the same end-to-end neural networks, computer vision, and real-time decision-making tech that power Full Self-Driving (FSD) software and the physical Optimus humanoid robot.

By repurposing idle vehicle compute and extending AI4 hardware beyond driving, the project scales Tesla’s autonomy ecosystem from roads to digital workspaces.

As a virtual counterpart to physical Optimus, it divides labor: software agents manage screen-based tasks while humanoid robots tackle physical ones, accelerating Tesla’s vision of general-purpose AI for productivity, Robotaxi fleets, and beyond.

In essence, Digital Optimus bridges Tesla’s vehicle and robotics autonomy with enterprise-scale AI, promising massive efficiency gains. No other company currently matches its real-time capabilities on such accessible hardware.

It really could be one of the most crucial developments Tesla and xAI begin to integrate, as it could revolutionize how people work and travel.

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