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.
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Tesla crosses major Unsupervised Self-Driving milestone
Tesla has reached a notable benchmark in its autonomous driving program after its Robotaxi fleet surpassed one million miles of unsupervised operation. The company made the announcement during its Cybercab event in Austin on September 3.
Tesla Vice President of AI Ashok Elluswamy told attendees he was happy to report the fleet had achieved one million miles of unsupervised Robotaxi operation as a testament to safety.
The new total marked a sharp increase from the 380,000 unsupervised miles Tesla disclosed during its second-quarter 2026 earnings update in late July.
In roughly six weeks, the company added about 620,000 miles. That acceleration followed Tesla’s decision to remove in-vehicle safety monitors from most of its operations outside the San Francisco Bay Area.

Credit: Tesla
Tesla first launched Robotaxi service in Austin in June 2025 with safety drivers present. It later began fully unsupervised rides and expanded into Dallas, Houston, Miami, Orlando, and Tampa. The San Francisco Bay Area remains the exception, where a safety monitor still rides in the vehicle under California permitting rules.
The company has not released a city-by-city breakdown of the one million unsupervised miles.
The milestone arrived as Tesla began offering public Cybercab rides in Austin. The purpose-built vehicle has no steering wheel or pedals and is designed only for autonomous ride-hailing. Production versions joined the existing fleet of modified Tesla vehicles already operating in the service.
Tesla’s unsupervised mileage is growing at a double-digit weekly rate according to earlier company comments, yet its fleet size remains modest compared with established competitors. Waymo has accumulated more than 200 million fully autonomous rider-only miles. Tesla has described its own unsupervised operations as having recorded zero notable incidents in the period leading up to the July update.
The one-million-mile figure reflects Tesla’s shift from supervised testing to broader driverless service in multiple states. It also highlights the company’s strategy of using both existing Model Y vehicles and the new Cybercab to scale its network.

Credit: Tesla
Whether the rapid recent growth continues will depend on further city expansions, regulatory approvals, and the performance of the purpose-built Cybercab in everyday paid rides. Tesla has not specified how many of the latest miles involved the new vehicle versus the rest of the fleet.
The announcement underscores Tesla’s progress toward a larger robotaxi network while illustrating the remaining gap in total autonomous experience relative to longer-operating rivals.
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Tesla Robotaxi will be a 24/7 service: here’s when
Tesla AI lead Ashok Elluswamy said this week that 24-hour Robotaxi service is close. Replying on X to a rider who wanted Cybercab trips all night, he wrote that the capability would arrive “next month or so” once “the next tech to merge on the v15 plan” is ready.
The comment landed on September 4, one day after Tesla opened public Cybercab rides in Austin. It is the clearest near-term timeline yet for overnight unsupervised operation. Tesla’s paid Robotaxi network currently runs from 6 a.m. to 10 p.m. seven days a week across Austin, Dallas, Houston, Miami, Orlando, and Tampa.
next month or so. the next tech to merge on the v15 plan will enable it.
— Ashok Elluswamy (@aelluswamy) September 4, 2026
That 16-hour window is shorter than the 6 a.m. to 2 a.m. schedule the company used for much of the prior year.
Elluswamy did not name the specific feature or say whether the change would apply first to purpose-built Cybercabs, the existing Model Y fleet, or both. He also offered no city-by-city rollout list. The link to Full Self-Driving v15 is nevertheless significant.
Tesla has described v15 as a step-change architecture with seven parallel improvement tracks and roughly ten times more parameters than earlier builds. Early versions of that software already operate on the Robotaxi fleet and contain about 40 percent of the planned gains.
By July 2026, the unsupervised fleet had logged more than 380,000 miles across six cities in two states with what the company called an impeccable safety record and no notable incidents caused by the vehicles themselves. Tesla has repeatedly argued that camera-based end-to-end neural networks, rather than extra sensors, are the core of the solution.
Overnight service would test that claim in lower-light conditions and would also raise vehicle utilization, a key variable for Robotaxi unit economics. The company has already begun using public Superchargers at night and is building dedicated Robotaxi charging sites.
Riders have asked why software must change if the cars already drive in the dark. The practical answer appears to be reliability and scale: Tesla has held back mass expansion until more of the v15 stack is merged, citing the need for higher confidence before putting thousands of unoccupied vehicles on streets around the clock.
If the next module arrives on the timetable Elluswamy sketched, 24-hour service could begin in October 2026 in at least some markets.
That would mark a shift from a daytime-bounded pilot to a service that can run whenever demand exists, including the late-night hours that have so far remained out of reach.
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Tesla Full Self-Driving will now overtake manual driving to avoid disaster
Tesla is beginning to roll out Full Self-Driving Supervised v14.3.9 with a new active safety layer that can take control even when the driver is operating the car manually.
Tesla AI said the software can activate FSD on the driver’s behalf when an imminent collision is detected and Automatic Emergency Braking may not be enough. It may also engage if the system detects heavy distraction or an accidental FSD disengagement.
FSD Supervised v14.3.9 starting to roll out shortly
This release includes a new active safety feature set: FSD Supervised can now activate on your behalf when an imminent collision is detected and Automatic Emergency Braking (AEB) may not be enough.
It may also engage if we…
— Tesla AI (@Tesla_AI) September 4, 2026
The capability is essentially Automatic Collision Evasion. However, unlike conventional AEB, which mainly applies the brakes in a straight line, this feature can use steering, braking, and acceleration together if the car calculates that stopping alone will not prevent impact and a safer path exists. The system may change lanes or move toward a shoulder when conditions allow, then continue driving after the immediate threat is handled rather than simply coming to a stop.
The intervention is meant as a last-resort safety net, not a replacement for attentive driving.
Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident
Tesla’s own description still frames FSD as supervised assistance. Secondary reports on internal release notes say the feature can fire while the car is being driven manually if cabin-camera monitoring suggests the driver is not sufficiently attentive, such as reaching toward the back seat, or if FSD appears to have been turned off unintentionally.
After the emergency maneuver, the car is expected to alert the driver and request a return to manual control.
The safety case is straightforward. Many collisions happen in the last second because a driver is looking away, fumbles a control, or faces an obstacle that braking cannot fully solve. A system that can both recognize that AEB is insufficient and execute a coordinated evasive path can reduce those remaining high-severity events.
Re-engaging after accidental disengagement also addresses a practical failure mode: a small steering nudge that drops FSD at the worst moment. The advantage is a background safety net that uses the same vision stack already running in v14, instead of leaving the car solely to emergency braking once the driver is no longer in command.
The feature still depends on FSD being enabled and, according to reports, an active FSD purchase or subscription. It does not make the vehicle unsupervised. Drivers remain responsible, and Tesla has not published how often the system is expected to intervene or how it will handle false positives.
If the rollout is conservative and the false-alarm rate stays low, the update is a meaningful step: FSD is no longer only a feature the driver turns on. In the rare moments when disaster is already forming, it can step in.