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Tesla Superchargers were over 10 times as reliable as these rivals
Tesla and Rivian topped this charger reliability study, outperforming competitors by a wide margin.
A new study shows that many electric vehicle (EV) charging networks were substantially less reliable than Tesla’s Superchargers or Rivian’s Adventure Network (RAN), while hardware problems accounted for the most common issue experienced
In a Consumer Reports study shared last week, Tesla and Rivian’s charging networks were found to be significantly more reliable than those of other companies, though EV owners reported a problem with about one out of every five charging sessions initiated overall. Respondents said they had issues with just 4 percent of charging sessions at Tesla’s Superchargers, making them the most reliable, while issues with Rivian’s network were reported for just 5 percent of sessions.
Comparatively, Shell Recharge users faced the most issues, with respondents detailing problems in 48 percent of charging sessions. The next least reliable networks were EVgo and Blink, which followed with 43 percent and 41 percent problems reported, respectively. DC fast-chargers had a reported issue rate of 34 percent, while owners faced problems with Level 2 chargers in 25 percent of sessions.
“The findings show that the public charging experience can vary widely based on the vehicle and the charging networks operating in one’s community and along frequent trips,” writes Drew Toher, Consumer Reports’ Campaign Manager for Sustainable Transportation projects. “This is an important consideration for those without access to home charging. With these findings, CR is encouraging all charging networks to take ownership of their performance and implement measures to improve reliability.”
The survey included responses from 1,230 owners of BEVs and plug-in hybrid EVs (PHEVs), detailing experiences from roughly 5,700 individual charging sessions. The majority of issues customers faced were related to hardware, while they also reported problems with payment, charging power, and other factors.
Out of those who said they had issues directly with the chargers, 76 percent said they encountered broken or unresponsive screens, or those with error messages.
Credit: Consumer Reports (graphic by Sharon Seidl)
Credit: Consumer Reports (graphic by Sharon Seidl)
Credit: Consumer Reports (graphic by Sharon Seidl)
Credit: Consumer Reports (graphic by Sharon Seidl)
Teslas constant push for improvements in action.💪
Superchargers are already among the best in the industry, but Tesla is still improving the system.⚡️ https://t.co/wD9D2Z1CJe
— TESLARATI (@Teslarati) February 21, 2025
READ MORE ON EV CHARGING: Tesla Superchargers dominate J.D. Power EV Charging Study
“By calling out broken screens, payment issues, and slow charging power, community members are crowdsourcing data that will hold charging networks accountable and improve drivers’ experience with public charging,” Toher adds. “This will help tackle the biggest impediment for consumers looking to purchase a more efficient vehicle.”
The release also notes that EV owners planning to charge beyond their home can take a few steps to help ensure the best experiences possible, including making accounts for several different charging networks, getting apps like A Better Route Planner, Plugshare, and CR partner Chargeway, and performing battery preconditioning, among others.
Tesla’s Superchargers have repeatedly been found to be the most reliable in markets around the world, and in surveys from Consumer Reports, JD Power, and other auto industry research firms. Rivian has also followed Tesla in taking routine measures to keep owners informed about the reliability of chargers. One such example includes the automaker’s deployment last April of “charging scores” for the RAN network, to help improve customer experiences by directing them to working stations.
Tesla exec highlights advantages of prefabricated Superchargers
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
