Tesla has launched an online calculator for its Supercharger for Business program, giving property owners their first transparent look at what it really costs to install Superchargers on site and what kind of return they can expect.

The program itself launched in September 2025, allowing businesses to purchase and operate Supercharger hardware on their own property while Tesla handles installation, maintenance, software, and 24/7 driver support. As Teslarati reported at launch, hosts also get their logo placed on the chargers and their location integrated into Tesla’s in-car navigation, meaning drivers are actively routed there. The stalls are open to all EVs, not just Teslas.

We launched Supercharger for Business in 2025 to help companies get charging right. We found simplicity and transparency to be a problem in this industry.

We’re now sharing pricing and a financial calculator to help make informed decisions. The goal is to accelerate investments,…

— Tesla Charging (@TeslaCharging) April 8, 2026

The new online calculator, announced by Tesla on Wednesday with the note that “simplicity and transparency” have been a problem in the industry, lets any business enter a U.S. address and get a real cost and revenue model. A standard 8-stall V4 Supercharger site runs approximately $500,000 in hardware and $55,000 per post for installation, bringing an all-in price just shy of $1 million. Tesla charges a flat $0.10 per kWh fee to cover software, billing, and network operations. Businesses set their own retail price and keep the margin above that fee.

Tesla expands its branded ‘For Business’ Superchargers

Taking a look at Tesla’s Supercharger for Business online calculator, we can see that ROI is not uniform, and the gap between a strong location and a poor one can stretch the breakeven point by several years.

The biggest driver is foot traffic and how long people stay. A busy rest station, hotel, or outlet mall brings in repeat visitors who need to charge while they’re already stopped, pushing utilization numbers higher and shortening payback time.

Tesla Supercharger for Business ROI calculator

Local electricity rates matter just as much on the cost side. Markets like California carry some of the highest commercial electricity rates in the country, which eats into the margin between what a host pays per kWh and what they charge drivers. At the same time, dense urban areas with high EV adoption tend to support higher retail charging prices, which can offset that cost if demand is strong enough. Weather also plays a role. Cold climates reduce battery efficiency and increase charging frequency, but they can also suppress utilization in winter months if drivers avoid stopping in exposed outdoor locations. Suburban and rural sites face a different problem: lower baseline EV traffic, which means a site with cheaper power and lower operating costs can still take longer to pay back simply because the stalls sit idle more often. Tesla’s calculator uses real fleet data to pre-fill utilization estimates by ZIP code, so businesses can run their specific address against these variables rather than relying on averages.

The program has seen real adoption. Wawa, already the largest host of Tesla Superchargers with over 2,100 stalls across 223 locations, opened its first fully owned and branded site in Alachua, Florida earlier this year. Francis Energy of Oklahoma and the city of Alpharetta, Georgia have also deployed branded stations through the program, as Teslarati covered in January.

Tesla now exceeds 80,000 Supercharger stalls worldwide, and the calculator makes the economic case for accelerating that number through private investment rather than company-owned sites alone.

Tesla’s Full Self-Driving suite is one of the most significant technological developments in terms of passenger travel in decades, but it is not all sunshine and rainbows, even with major strides in safety, CEO Elon Musk revealed.

In a candid reply to a dramatic video of Tesla’s Full Self-Driving (FSD) system averting disaster, Elon Musk laid bare a harsh reality facing autonomous vehicle technology.

The clip shows a Model 3 traveling at over 65 mph on a foggy, rain-soaked highway when a pedestrian suddenly steps into traffic.

Full Self-Driving instantly detects the threat and swerves safely, preventing what could have been a fatal collision for both the pedestrian and the driver’s cousin.

Musk’s response was unequivocal:

“Tesla self-driving saves a lot of lives – the statistics are unequivocal. That doesn’t mean it’s perfect, of course.” Even with a projected 10x safety improvement over human drivers, FSD would still prevent roughly 90% of the world’s approximately one million annual auto fatalities. The remaining 10%—roughly 100,000 deaths—would expose Tesla to relentless lawsuits. Meanwhile, the vast majority of lives saved would go unnoticed. “The 90% who are still alive mostly won’t even know that Tesla saved them. Nonetheless, it is the right thing to do.”

This “unfortunate truth,” as Musk implicitly framed it, highlights a fundamental asymmetry in how society perceives safety technology. Human drivers cause the overwhelming majority of crashes through distraction, fatigue, or error.

Tesla self-driving saves a lot of lives – the statistics are unequivocal.

That doesn’t mean it’s perfect, of course.

Even when we improve safety 10X, saving 90% of the million lives lost in auto accidents every year, Tesla will still get sued for the 10% who did die. The 90%… https://t.co/OrNB1mO5eF

— Elon Musk (@elonmusk) April 6, 2026

Yet when FSD errs, the incident becomes headline news and a courtroom target. Prevented tragedies, by contrast, leave no trace.

Survivors simply continue their journeys, unaware of the split-second intervention that kept them alive. The result is a distorted public narrative that amplifies failures while rendering successes invisible.

We have seen this through various headlines throughout the years, including the mainstream media’s obsession with only mentioning the manufacturer’s name in the instance of an accident when it is “Tesla.”

Opinion: Tesla Autopilot NHTSA investigation headlines are out of control

The video’s real-world example underscores FSD’s current capabilities. In near-zero visibility, the system’s cameras and neural network reacted faster than any human could, demonstrating the life-saving potential Musk cites.

Tesla’s latest safety data already shows FSD (Supervised) performing significantly better than the U.S. average, with crashes occurring far less frequently per mile driven.

Still, regulatory scrutiny, liability concerns, and media focus on edge-case failures continue to slow widespread adoption. Musk’s frank admission suggests Tesla is prepared to push forward despite the legal and perceptual headwinds.

As FSD edges closer to unsupervised autonomy, Musk’s post serves as both a progress report and a reality check. The technology is already saving lives today.

The unfortunate truth is that proving it and scaling it responsibly will require society to value statistical lives saved as much as dramatic stories of those lost. In the race toward safer roads, perception may prove as formidable an obstacle as the fog and rain in that viral video.

Tesla has officially started rolling out Full Self-Driving v14.3 to Early Access Program (EAP) members, and there are a lot of new improvements.

We are in EAP and will be on the road with v14.3 in the coming hours, so we’ll have a lot of things to discuss over the next few days, especially coming from v14.2.2.5, which I called the most “confusing” FSD release of all time.

🚨 Tesla Full Self-Driving v14.3 is here and it is coming with so many new features

Looks like there will be some MAJOR improvements to the general performance.

Truly seems like it will be significantly different than v14.2 pic.twitter.com/mhdfBLuDup

— TESLARATI (@Teslarati) April 7, 2026

Tesla brought out a lot of improvements, according to the v14.3 release notes, which list a vast number of fixes, new features, and new capabilities.

Here’s what Tesla’s release notes for the v14.3 release state:

• Improved parking location pin prediction, now shown on a map with a P icon.
•  Increased decisiveness of parking spot selection and maneuvering.
• Rewrote the Al compiler and runtime from the ground up with MLIR, resulting in 20% faster reaction time and improving model iteration speed.
• Enhanced response to emergency vehicles, school buses, right-of-way violators, and other rare vehicles.
• Mitigated unnecessary lane biasing and minor tailgating behaviors.
• Improved handling of small animals by focusing RL training on harder examples and adding rewards for better proactive safety.
• Improved traffic light handling at complex intersections with compound lights, curved roads, and yellow light stopping – driven by training on hard RL examples sourced from the Tesla fleet.
• Upgraded the Reinforcement Learning (RL) stage of training the FSD neural network, resulting in improvements in a wide variety of driving scenarios.
• Upgraded the neural network vision encoder, improving understanding in rare and low-visibility scenarios, strengthening 3D geometry understanding, and expanding traffic sign understanding.
• Improved handling for rare and unusual objects extending, hanging, or leaning into the vehicle path by sourcing infrequent events from the fleet.
• Improved handling of temporary system degradations by maintaining control and automatically recovering without driver intervention, reducing unnecessary disengagements.

Tesla also listed a handful of future improvements as well:

• Expand reasoning to all behaviors beyond destination handling
• Add pothole avoidance
• Improve driver monitoring system sensitivity with better eye gaze tracking, eye wear handling, and higher accuracy in variable lighting situations

CEO Elon Musk has said that v14.3 could be “where the last big piece of the puzzle finally lands.” We have high expectations for this release because, in a lot of ways, v14.2’s final version was extremely disappointing and seemed to be a regression more than anything.

Nevertheless, Full Self-Driving v14.3 is going to be quite an interesting test, considering this is also the first time Musk has stated it will feel like the car will be “sentient.”

Reasoning will be a bigger piece of the puzzle with this release, although there were some elements of it in v14.2.

Tesla AI Head says future FSD feature has already partially shipped

We plan to travel plenty of miles with it over the next few days, so we’ll keep you posted on what our thoughts are.