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Tesla Model 3 Performance drag races McLaren 570S in impressive 1/4 mile showdown
There is no denying that the Model 3 Performance is quick, especially considering VBOX data validating the car’s 0-60 mph acceleration figures. But the question is, would it be fast enough to beat an actual supercar on the drag strip? Perhaps, even something as daunting as a McLaren 570S?
This was something explored recently by Tesla owner-enthusiast Erik Strait, better known as the host of YouTube’s DÆrik channel. Thanks to a friendly owner in the area, Erik has been able to test out the capabilities of the Model 3 Performance, which adds dual motors and a $5,000 Performance Upgrade package to the base trim, including 20″ Performance Wheels, Michelin Pilot Sport 4S summer tires, a carbon fiber rear spoiler, aluminum alloy pedals, and a top speed boost that enables the electric car to max out at 155 mph.
Tesla lists the Model 3 Performance with a 0-60 mph time of 3.5 seconds, which is plenty fast for a high-performance midsize sedan. Erik’s tests have shown that the Model 3 Performance is actually quicker than Tesla’s estimates, with the electric car hitting 60 mph in as low as 3.18 seconds when fully charged. Nevertheless, with a McLaren 570S as its opponent, the cards are stacked against the Model 3 Performance.
McLaren’s supercars are actually embedded in the history of Tesla, with CEO Elon Musk famously buying a McLaren F1 when he made his first millions after selling Zip2, his first company. Musk would later infamously wreck his McLaren F1 in a joyride with Peter Thiel, but the supercar would hold a special place in the Tesla CEO’s heart for years to come. When Musk unveiled the Model S P85D, for example, he made it a point to highlight that the electric car’s 0-60 mph time of 3.2 seconds is comparable to the acceleration of the supercar.
The 570S is McLaren’s “baby” supercar, slightly less powerful than its flagship vehicles like the 650S but incredibly fast just the same. The 570S is equipped with a twin-turbo 3.8-liter V8 engine making 562 hp and 443 lb-ft of torque. The car is also fitted with a slick-shifting 7-speed dual-clutch automatic transmission, which helps propel the vehicle from 0-60 mph in 3.0 seconds. The 570S’ top speed of 204 mph places it beside popular supercars like the Lamborghini Huracan 610-4 Spyder and the Ferrari 488 Spider 3.9 V8 Turbo. Compared to the McLaren 570S, the Model 3 Performance appears completely outclasses, with its dual motors producing a combined 450 hp and 471 lb-ft of torque and its top speed of 155 mph.
The Model 3 Performance dueled the McLaren 570S twice, and on both times, the electric car left the gas-powered supercar off the line. The Model 3 Performance did get the jump on the 570S to the quarter-mile mark, but stats-wise, Tesla’s electric car fell just around .2 seconds short of the supercar. The Model 3 Performance finished the quarter mile in 11.79 seconds at a speed of 115.18 mph in the first round, which was just slightly lower than the McLaren 570S’ 11.62 seconds and 124 mph. A second race rendered similar results, with the Model 3 Performance finishing the run in 11.79 seconds at 115.35 mph and the 570S completing the run in 11.58 seconds at 125.68 mph.
The Model 3 Performance is not a supercar, both in design and in function. While the McLaren 570S had bad launches on both races, the time differences between the two vehicles’ quarter-mile runs were just way too close. With stickier tires and a possible Ludicrous upgrade in the future, the Model 3 Performance could most certainly establish itself as a force to be reckoned with on the drag strip, just like its two larger siblings — the Model S P100D and the Model X P100D.
Watch the Model 3 Performance stand up to the McLaren 570S in the video below.
Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
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Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Elon Musk
Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.
A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial.
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.
Judge says disputed facts warrant a trial
At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.
Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”
OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.
Rivalries and Microsoft ties
The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.
The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.
Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
