Tesla has announced that it is starting the rollout of Track Mode, a feature of the Model 3 Performance that allows the car to perform better on a racecourse, today. In light of the feature’s release, Tesla has published a blog post outlining the science behind Track Mode, as well as the feature’s specifics.
While Tesla’s other performance-oriented upgrades like Ludicrous Mode for the Model S and X help a vehicle with straight-line acceleration, Track Mode helps the company’s electric cars handle corners better. Tesla’s blog post notes that Track Mode was designed specifically to be used on closed autocross circuits and racetracks. The company also pointed out that its goal behind the development of Track Mode was simple — they wanted to use the power of the vehicle’s electric motor and instant torque to “make cornering on the track feel just as natural as forward acceleration.”
Track Mode enables vehicles to precisely control whether torque goes to the front or the rear wheels. This allows the Model 3 Performance to instantly increase or decrease the car’s rotation in a corner. With such a system in place, racing enthusiasts would find that highly technical driving sessions on a closed circuit would be a lot easier.
Track Mode starts rolling out today
— Tesla (@Tesla) November 8, 2018
Unlike the usual Sport Modes of legacy carmakers, which usually involve the disabling of stability control, the Model 3 Performance’s Track Mode adds features to the vehicle. Tesla accomplished this by replacing the electric car’s stability control system with its own Vehicle Dynamics Controller — a software specifically developed for the company’s electric vehicles that acts as both a stability control system and a performance enhancement on the track. Tesla also provided a summary of the features that are employed by Track Mode when it is activated.
Motor Torque for Rotation
Our Vehicle Dynamics Controller continually monitors the state of the vehicle and all of the inputs from the driver to determine the driver’s intention and affect the rotation of the car in a matter of milliseconds. Track Mode relies heavily on the front and rear motors to control the car’s rotation, and we have the ability to command a 100% torque bias. When cornering, if rotation is insufficient to the driver’s request, the system controls a rear biased torque. Conversely, when rotation is excessive, we command a front biased torque.
Increased Regenerative Braking
Heavy regenerative braking may not be comfortable for day-to-day driving, but on a track, it has several key advantages. It gives the driver more authority with a single pedal, improves the endurance of the braking system, and sends more energy back into the battery, maximizing the battery’s ability to deliver large amounts of power. It also gives the Vehicle Dynamics Controller more authority to create or arrest rotation with the motors when your foot is lifted off of the accelerator pedal.
Track Focused Powertrain Cooling
The high output power required for track driving generates a lot of heat, so endurance on the track requires more aggressive cooling of the powertrain. We proactively drop the temperatures of the battery and the drive units in preparation for the track and continue to cool them down in between drive sessions. We can also allow operation of the powertrain beyond typical thermal limits and increase our refrigerant system capacity by overclocking the AC compressor into higher speed ranges.
Enhanced Cornering Power
We typically think of using brakes to slow down a car, but you can actually use them to make the car faster out of a corner. All Model 3s are equipped with open differentials, which send an equal amount of torque from the motors to both the left and right wheels. When cornering, the wheels on the inside of the corner have less load on them, which means they can provide less tractive force than the outside wheels. To prevent excess slip on this inside tire, we have to limit the torque for both wheels, leaving power on the table. In Track Mode, we simultaneously apply brake and motor torque to produce a net increase in tractive force while cornering. This is similar to how a limited slip differential works, except when using the brakes, the differential can be optimized for various driving conditions.
What is particularly exciting about the release of Track Mode is the fact that it is just the first version of the system. On its blog post, Tesla noted that Track Mode is set to improve further in the future through over-the-air updates.
When Elon Musk announced the Model 3 Performance on Twitter, he noted that the vehicle would be around 15% faster than a BMW M3 on the track. Considering the pedigree of the German-made performance sedan as well as the tendency of Tesla’s previous vehicles to throttle their performance on a track, Musk’s claims were met with a notable degree of skepticism from both avid car enthusiasts and critics alike. That said, initial reviews of the feature were notably positive.
Tesla conquered the drag strip with Ludicrous Mode. It remains to be seen if the company can do the same on the closed circuit with Track Mode. Considering the deliberate design of the feature, though, there is a pretty good chance that the Model 3 Performance would soon be just as formidable on the track as the Model S P100D is on the drag strip.
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.”
News
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
