Doubts may still linger about the potential of battery electric vehicles for mainstream transportation, but EVs are getting progressively better. And if the data from the Tesla Model 3 and Model Y fleet is any indication, it appears that these improvements could result, at least to some degree, in an all-electric crossover being more efficient than the early production versions of an all-electric sedan.
In a recent conversation with Teslarati, David Hodge, the founder and CEO of Embark — a transportation app company that was sold to Apple in 2013 — explained that his work on a little passion project has shown something incredibly interesting about the Model 3 and Model Y’s efficiency. Hodge is currently working on the Nikola app, a service that he hopes will eventually grow to be the CarFax for EVs. So far, users of the app have driven about 7,000,000 miles, and over 2,000 Model 3s are registered in the fleet.
These Model 3s are comprised of vehicles that were produced from the beginning of Elon Musk’s first “alien dreadnought” attempt to cars that rolled off the line this quarter. Based on data that the Nikola app proprietor shared, it is evident that the Model 3 has gotten significantly more efficient over the years. Users of the app with vehicles produced in 2018, for example, showed a real-world average MPGe of 90.3, while cars that were produced in 2019 had a real-world average of 100.4.
These efficiency improvements continued in the first half of 2020, when Nikola app users who owned Model 3s showed a real-world average MPGe of 105.2. Interestingly enough, Tesla appears to have rolled out a major improvement to the Model 3’s efficiency in the second half of the year, as vehicles produced after June 2020 have shown a real-world average MPGe of 125.7. That’s the biggest improvement in the Model 3’s efficiency yet, at least as reflected in data from the Nikola app’s users.
Inasmuch as the improvements in the Model 3’s MPGe are notable, the efficiency of the Model Y appears to be even more noteworthy. The Model Y is the newest vehicle in Tesla’s lineup today, having started deliveries earlier this year. But even with its early ramp, it is becoming quite evident that Tesla did something special with the all-electric crossover.
Nikola app users who owned Model Ys that were produced in the first half of 2020 showed a real-world average MPGe of 103.2, which was very close to the MPGe of Model 3s that were manufactured in the same period. And just like the Model 3s, Model Ys that were produced after June 2020 exhibited a significant improvement in efficiency, with the vehicles having a real-world average MPGe of 118.7. That’s higher than the MPGe of Model 3s that were produced just last year.
As noted by Hodge, such efficiency figures from the Model Y are extremely impressive, especially considering that it is larger and significantly heftier than the Model 3. This is also a pretty unique situation considering that the company’s flagship sedan, the Model S, has always been significantly more efficient than its SUV counterpart, the Model X.
“This is pretty impressive considering the obvious aerodynamic differences in the Y and the fact that the S has always outperformed the X by about 15. If you just look at cars made since June, the Model Y MPGe climbed to 119 on average, but it looks like some of the tech improvements made it over to the 3, which is seeing 125.6 MPGe average in that period,” Hodge noted.
Tesla has a habit of rolling out improvements to its vehicles as soon as they are available. The latest Teslas are therefore expected to have the best tech that the company has to offer at the time of their production. With this in mind, and as per the findings of auto teardown expert Sandy Munro, the Model Y is indeed equipped with Tesla’s best, both in tech and in design. And considering that the all-electric crossover is expected to share components with its sedan sibling, it is not very surprising to see the Model 3 experience efficiency gains as soon as the Model Y started ramping up. Such is simply the nature of Tesla.
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
