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Tesla Model S shows drastic consistency improvements after update, ties Taycan in Car & Driver test
Back in February, esteemed motoring publication Car and Driver pitted the Tesla Model S Performance against the Porsche Taycan Turbo S. And while the publication ultimately granted the win to the Model S due to its value for money, the tests showed that the Taycan had the better performance between the two vehicles. This was especially true when it came to consecutive quarter-mile runs.
The Model S shone against the Taycan in rolling-start 5-60 mph runs, but in actual sprints to the quarter-mile, the Tesla ended up being slower than the Porsche. The publication noted that on its hero run, the Model S Performance was able to hit 60 mph in 2.5 seconds, which was only 0.1 seconds slower than the Taycan Turbo S’ 2.4 seconds. However, the gap between the two cars was about 3 seconds by 150 mph.
Shockingly, the Model S’ 0-60 mph times fell off rapidly after its first couple of runs, and by the 15th launch, the flagship Tesla sedan was hitting highway speeds nearly at the pace of the Chevy Bolt EV. That was the case, at least, until Tesla rolled out its Cheetah Stance update for the Model S. Once that was rolled out, everything changed.
With the exact same car on hand, Car and Driver opted to retest the Model S Performance’s capabilities with its Cheetah Stance update. The only difference was that this time, the test track used for the all-electric sedan’s launches was in Michigan instead of Southern California. Needless to say, the Tesla Model S got better after its update — a whole lot better.
The hero run of the Model S Performance was already impressive back in February, but with its Cheetah Mode update, the vehicle was able to show a 0-60 mph time of 2.4 seconds, matching the Taycan Turbo S’ best time. Inasmuch as the results from this past February were shocking, the results from the Model S’ retest were equally astounding. The vehicle’s 0-60 mph time only ranged from 2.7 to 3.8 seconds, and quarter-mile passes ranged from 11.3 to 12.9 seconds.
Ultimately, after 15 consecutive launches, the average time in both metrics dropped by around 2 seconds compared to the tests last February. This stunning improvement in consistency, which was evidently only due to new software, was something that truly impressed Car and Driver.
“Across all 15 runs, the average time in both metrics dropped by a massive two seconds compared to our previous test. That’s a staggering gain in performance from twiddling a few lines of code, and we continue to marvel at the breadth and depth of the changes Tesla is making with its continual software updates,” the publication wrote.
What is rather interesting is that the Tesla Model S Performance today is not done receiving improvements from the electric car maker. Tesla stands apart from the competition with its mastery of over-the-air software updates, and if Car and Driver’s tests are any indication, these improvements are incredibly evident. It could, for one, match the consistency and performance of a flagship electric car like the Porsche Taycan Turbo S, at a fraction of the price.
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
