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Tesla Model 3 duels the Porsche Taycan Turbo S in track race–with surprising results
The Tesla Model 3 is starting to become a popular vehicle for track enthusiasts in Japan. In the recently held All Japan EV Grand Prix at the Fuji Speedway in Oyama, the event’s flagship EV-1 category featured five Model 3s from several different teams. But this time around, the event also hosted a new, formidable electric car—the 560 KW Porsche Taycan Turbo S.
The Porsche Taycan Turbo S is a powerhouse all-electric sports car that was bred on the cruel turns of the Nurburgring. As such, the organizers of the All-Japan EV Grand Prix were quite excited about the vehicle. The Taycan Turbo S was deployed by the GULF Racing Team, which also had a Model 3 in the race. Other Teslas in the event included a pair of modified Model 3s from Team Taisan, which were partially modified with parts from aftermarket EV company Unplugged Performance.
The exact modifications to the Porsche Taycan Turbo S from GULF Racing were not disclosed on the All Japan EV Grand Prix’s program, though racers who participated in the event noted that the German track monster was fitted with Hoosier R7 tires. And for all intents and purposes, the Taycan did perform very well, recording the fastest lap in the race at 1:55.885 and an average speed of 141.751 km/h (88.079 mph).
But surprisingly enough, the Porsche Taycan Turbo S did not take the overall win of the day. That honor went to one of Team Taisan’s partially modified Tesla Model 3s. Interestingly enough, Unplugged Performance CEO Ben Schaffer noted that Team Taisan’s Model 3 actually had fewer aerodynamic mods due to Japan’s race regulations. But despite this, the Model 3 came out as the overall winner in the All Japan EV Grand Prix’s EV-1 segment, with a total lap time of 24:29.801 and an average speed of 133.370 km/h (82.872 mph).
The fastest lap was set by Taycan at 1'54.882, but slowed down at the end of the 5th lap. Taycan drove the Nurburgring distance in 5 laps at Fuji. pic.twitter.com/9tWgfl62T0
— あまりりりりす (@Amaririlyllis) April 12, 2021
Particularly interesting is that the Tesla Model 3s practically dominated the event. Following Team Taisan’s partially modified Model 3 were three other Teslas, all of which performed very well. The Porsche Taycan Turbo S came in 5th place with a total lap time of 25:30.408 and an average speed of 128.088 km/h (79.590 mph), about one minute behind Team Taisan’s Model 3.
The Model 3 may be Tesla’s entry-level car, but the midsize sedan has a lot of bite. And thanks to its track capability, it is arguably the most fun vehicle to drive among Tesla’s existing lineup. That is, at least, until Tesla releases the Model S Plaid and Model S Plaid+, both of which were also tested in the unforgiving turns of the Nurburgring.
Check out the All Japan EV Grand Prix’s program in the video below.
EV2021 r1 Program by Simon Alvarez on Scribd
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Tesla’s Head of AI, Ashok Elluswamy, says that something that was expected with version 14.3 of the company’s Full Self-Driving platform has already partially shipped with the current build of version 14.2.
Tesla and CEO Elon Musk have teased on several occasions that reasoning will be a big piece of future Full Self-Driving builds, helping bring forth the “sentient” narrative that the company has pushed for these more advanced FSD versions.
Back in October on the Q3 Earnings Call, Musk said:
“With reasoning, it’s literally going to think about which parking spot to pick. It’ll drop you off at the entrance of the store, then go find a parking spot. It’s going to spot empty spots much better than a human. It’s going to use reasoning to solve things.”
Musk said in the same month:
“By v14.3, your car will feel like it is sentient.”
Amazingly, Tesla Full Self-Driving v14.2.2.2, which is the most recent iteration released, is very close to this sentient feeling. However, there are more things that need to be improved, and logic appears to be in the future plans to help with decision-making in general, alongside other refinements and features.
On Thursday evening, Elluswamy revealed that some of the reasoning features have already been rolled out, confirming that it has been added to navigation route changes during construction, as well as with parking options.
He added that “more and more reasoning will ship in Q1.”
🚨 Tesla’s Ashok Elluswamy reveals Nav decisions when encountering construction and parking options contain “some elements of reasoning”
More uses of reasoning will be shipped later this quarter, a big tidbit of info as we wait v14.3 https://t.co/jty8llgsKM
— TESLARATI (@Teslarati) January 9, 2026
Interestingly, parking improvements were hinted at being added in the initial rollout of v14.2 several months ago. These had not rolled out to vehicles quite yet, as they were listed under the future improvements portion of the release notes, but it appears things have already started to make their way to cars in a limited fashion.
Tesla Full Self-Driving v14.2 – Full Review, the Good and the Bad
As reasoning is more involved in more of the Full Self-Driving suite, it is likely we will see cars make better decisions in terms of routing and navigation, which is a big complaint of many owners (including me).
Additionally, the operation as a whole should be smoother and more comfortable to owners, which is hard to believe considering how good it is already. Nevertheless, there are absolutely improvements that need to be made before Tesla can introduce completely unsupervised FSD.
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.
Tesla AI Head says future FSD feature has already partially shipped
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
