Tesla was found to be one of the most unreliable brands in America, according to Consumer Reports’ annual reliability report.
Consumer Reports‘ annual reliability rankings have been released, and with data from 24 brands and over 300,000 vehicles, Tesla fell near the bottom (19/24) along with Mercedes-Benz, Jeep, Volkswagen, GMC, and Chevrolet. Electric vehicles overall also placed poorly, being the second least reliable category of vehicles. Hybrids/plugin hybrids, especially those from Toyota, were found to be the most reliable.
Before diving deeper into the rankings, it is crucial to understand how Consumer Reports creates its yearly reliability rankings in the first place. This year, the company surveyed over 300,000 vehicles (sold between 2000-2022), and over the past year, owners were asked to report issues they had with their vehicles. Issues were categorized into 17 categories; engine issues, transmission issues, interior electronics issues, etc. From this accumulation of data, Consumer Reports then gives each brand a grade out of 100 regarding their overall reliability.
Consumer Reports also stipulates that they will only rank brands that they have “sufficient survey data for two or more models.” Hence the absence of brands such as Rivian, Alfa Romeo, and Lucid.
Tesla scored a reliability score of 40/100, while electric vehicles overall scored 36/100. It isn’t all bad news for Tesla; its score matches the average for domestic automakers, the company was able to improve its ranking by four places compared to last year, and none of its vehicles made it to the list of 10 least reliable vehicles in America. A list that notably included the popular Hyundai Kona EV scoring 5/100.
Conversely, hybrid and PHEV vehicles crushed the competition with an average score of 78/100. And unsurprisingly, the brand with the most extensive representation within that segment, Toyota, achieved the number 1 spot with an overall reliability score of 72/100. Toyota was joined by Lexus, BMW, Mazda, and Honda in the top 5 (descending order).
Consumer Reports’ results lead to one central question, what influenced Tesla (and electric vehicles generally) in scoring so low compared to the competition? This question becomes especially confounding when the prevailing narrative is that “electric vehicles are generally more reliable than their gas counterparts.”
Consumer Reports’ analysis only addresses this question once, noting that “As more EVs hit the marketplace and automakers build each model in greater numbers, we are seeing that some of them have problems with the battery packs, charging systems, and the motors in their drive systems. Owners of the Chevrolet Bolt, Ford Mustang Mach-E, Hyundai Kona Electric, and Volkswagen ID.4 all reported some of these issues.”
Another couple of issues that may be plaguing Tesla include build quality and software problems. Tesla has notoriously had quality control issues, which will certainly not aid its reliability score. At the same time, as Tesla attempts to offer the bleeding edge of software innovation, they undoubtedly encounter more software issues than have been typically seen in the automotive space. And while these problems are typically fixed through updates and technical support quickly, they could easily contribute to Tesla’s poor performance.
Looking to the future, it is clear that Tesla needs to continue to dedicate itself to improving QC and general reliability. It is easy to say, “Tesla needs to increase production,” but consumers will pay the price if this production expansion comes at the cost of reliability.
What do you think of the article? Do you have any comments, questions, or concerns? Shoot me an email at william@teslarati.com. You can also reach me on Twitter @WilliamWritin. If you have news tips, email us at tips@teslarati.com!
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.”
News
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
