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NVIDIA says Tesla raised the bar for self-driving tech, car makers must deliver
NVIDIA, a prominent and highly successful leader in computer chip design, says that Tesla has raised the bar in autonomous driving software, and other car makers will have to deliver similar performance if they want to compete in the long-term future of the auto industry, according to a recent NVIDIA company blog.
“It’s financially insane to buy anything other than a Tesla,” CEO Elon Musk stated during the company’s Autonomy Day event. He then compared the purchase of any other car as equivalent to buying a horse for one’s transportation purposes. NVIDIA, for its part, agrees with Musk and Tesla’s sentiments about the future of self-driving and the need for powerful computers to push its progress.
“Self-driving cars—which are key to new levels of safety, efficiency, and convenience—are the future of the industry. And they require massive amounts of computing performance… This is the way forward. Every other automaker will need to deliver this level of performance,” the chip maker wrote.
The type of autonomous driving technology Tesla is pushing is predicted to be the inevitable standard, and the company’s lead in the arena will likely increase even further as more of their vehicles take to the road. “By end of this quarter, about half a million Teslas will have full self-driving hardware (pending computer swap) & we will make another half million FSD cars by mid next year,” Musk tweeted, emphasizing this point and echoing what he’d explained the day prior.
Exactly. By end of this quarter, about half a million Teslas will have full self-driving hardware (pending computer swap) & we will make another half million FSD cars by mid next year.
— Elon Musk (@elonmusk) April 23, 2019
Tesla’s recent Autonomy Day presentation drew comparisons between the all-electric car maker’s Full Self-Driving (FSD) computer chip and those produced by NVIDIA, the only computer processing unit maker delivering performance in line with Tesla’s. NVIDIA currently has two self-driving chips in the works: the Xavier SoC (system on a chip) for assisted driving AutoPilot features, and the DRIVE AGX Pegasus computer for full self-driving. The comparisons in Tesla’s presentation were directed at the Xavier in a single-chip configuration.
The technical performance specifications required to run powerful artificial intelligence (AI) neural networks (NN) for autonomous driving require operations performed per second to be measured in the trillions – abbreviated as TOPS (tera operations per second). Tesla’s FSD computer chip can perform at a rate of 72 TOPS (x2 chips in the computer for 144 TOPS total), and the Xavier does 30 TOPS (mistakenly claimed to be 21 TOPS at Tesla’s event, per NVIDIA’s blog).
NVIDIA also expressed in the blog piece its opinion that the match between FSD and Xavier wasn’t quite an apples-to-apples comparison, given the purposes of the two chips. The chip designer prefers its DRIVE AGX Pegasus for the line-up, a computer intended for fully autonomous driving and capable of 320 TOPS. Tesla is assumingly aware of this product and obviously acknowledges the high level of technology developed by NVIDIA given that Hardware 2.5, the computer currently running Tesla’s Autopilot features, was made by the company.
A Tesla with driver features “deleted” under the Tesla Network. | Image: Tesla
There are additional specifications such as power consumption that further differentiate FSD from NVIDIA’s products with a more similar purpose to Tesla’s latest computer. Thus, a different product match may not have mattered towards the overall point being made in the presentation. Either way, a more important distinction between the two companies is the current status of their technologies.
Tesla’s chip was crowned as “objectively the best in the world” by Musk, and this looks to be true, given the fact that all Tesla Model S, 3, and X vehicles being produced now have the hardware installed and will add to the already accruing real world self-driving data the company’s cars provide. NVIDIA has partnered with other car manufacturers to develop its products, but they are not incorporated in production vehicles the way Tesla’s FSD has been yet.
The performance Tesla has achieved in its FSD computer is impressive, and that was and continues to be the point. “[Autonomy] is basically our entire expense structure,” Musk told an investor inquiring about where the California-based company was incurring the most cost. Tesla is hedging its fiscal future on the success of autonomous driving in the marketplace, and the company is doing so with bullish energy driven by its famous top executive.
Musk expects Tesla’s Full Self-Driving software to be complete by the end of this year and fully operational by the second quarter of next year.
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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.