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Tesla vs. competition: How many BEVs did OEMs sell in the U.S. in 2024?

Credit: Tesla

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Tesla remained the dominant seller of battery-electric vehicles (BEVs) in the U.S. last year, with early estimates showing that the company sold more than most of its competitors combined. While data isn’t yet available for every automaker selling BEVs in the U.S., we took the time to compile some of the earliest estimates available for 2024 BEV sales, giving us an idea of where Tesla’s competitors landed in the year’s sales.

According to Cox Automotive, automakers sold 1.3 million BEVs in the U.S. in 2024, making up 8 percent of the total market share of nearly 16 million vehicles sold across powertrain types. EV sales also jumped in Q4 to 356,000 vehicles, marking a 12 percent jump year over year.

Cox also expects EV deliveries to surpass 1.5 million in the U.S. in 2025, while 2023 deliveries topped out at 1.2 million.

General Motors (GM) and Ford took up the second and third spots in U.S. BEV sales in 2024, both following Tesla, which held first place decisively. GM’s BEV sales were made up of the Chevy Equinox EV, the Chevy Blazer EV, the Chevy Silverado EV, the Cadillac Lyriq, the GMC Hummer EV, the GMC Sierra EV, and the BrightDrop EV600 commercial van. Ford’s BEV sales were comprised of the Mustang Mach-E, the F-150 Lightning, and the E-Transit.

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Toyota was one of the few other manufacturers to release specific U.S. and BEV data, with the latter being made up of those from the BZ4X and Lexus RZ. The vast majority of Toyota’s “electrified” vehicles is comprised of hybrid and plugin hybrid powertrains, along with the Mirai which sports a fuel cell powertrain. All of these electrified vehicle types are excluded from the figure below.

Hyundai’s BEV figure was made up of Ioniq 5, Ioniq 6, and Kona BEV sales, the latter of which is also offered in a hybrid version. The company’s subsidiary Kia had BEV sales including the battery-electric EV6 and EV9, and while the automaker also sells a BEV version of the Niro, it did not separate the vehicle’s hybrid and BEV versions in its report released last week.

It’s worth noting that Tesla doesn’t share figures for individual market sales, though the maker was estimated by Cox Automotive to have sold about 633,000 units to remain the clear leader in the market. Others, such as Lucid and Rivian, deliver the vast majority of their vehicles in the U.S., though they do not break out region-specific figures. Meanwhile, similar estimates for the brands have not yet been shared publicly.

READ MORE ABOUT U.S. BEV SALES: Colorado becomes the #1 state for EV sales, beating California

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Audi had 23,152 BEVs sold in the U.S. made up of its e-tron Q4, Q6, Q8, and GT lineups, while its parent company, Volkswagen, sold blank units comprised of the ID.4 and newly launched ID.Buzz, which was only sold in the market in the fourth quarter. BMW sold its battery-electric i4, i5, i7, and iX models in the U.S. last year.

Nissan’s BEVs included the Leaf and the Ariya, which saw year-to-date sales increases of 57 and 47 percent, respectively.

Cox Automotive is also expected to unveil its 2024 EV Sales report in the coming weeks, which should shed light on many of the automakers that have not shared market-specific figures.

You can see the recent estimates from Cox Automotive on the top EV makers in the U.S. in 2024 below, along with some figures directly from each automaker. Additionally, the source of the figures are linked near the bottom of the page.

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How many BEVs did automakers sell in the U.S. in 2024?

  1. Tesla: 633,762
  2. GM: 114,432
  3. Ford: 97,865
  4. Hyundai: 61,797
  5. Kia: 56,099
  6. Rivian: 51,442
  7. BMW: 50,981
  8. Nissan: 31,024
  9. Toyota: 28,267
  10. Mercedes-Benz: 21,154
  11. Audi: 23,152
  12. Volkswagen: 18,183

Top 10 EV models sold in the U.S., according to Cox Auto estimates

  1. Tesla Model Y
  2. Tesla Model 3
  3. Ford Mustang Mach-E
  4. Hyundai Ioniq 5
  5. Tesla Cybertruck
  6. Ford F-150 Lightning
  7. Honda Prologue
  8. Chevy Equinox EV
  9. Cadillac Lyriq
  10. Rivian R1S

You can see detailed estimates from Cox Automotive, which were released on January 13.

Audi | BMW | Ford | GM | Hyundai | Lucid | Nissan | Rivian | Tesla | Toyota | Volkswagen

Updated 1/19: Added the latest figures from Cox Automotive estimates.

What are your thoughts? Did I miss any automakers or U.S. sales figures? Let me know at zach@teslarati.com, find me on X at @zacharyvisconti, or send us tips at tips@teslarati.com.

Study reveals less than 1% of EV owners wish to switch back to ICE

 

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Zach is a renewable energy reporter who has been covering electric vehicles since 2020. He grew up in Fremont, California, and he currently lives in Colorado. His work has appeared in the Chicago Tribune, KRON4 San Francisco, FOX31 Denver, InsideEVs, CleanTechnica, and many other publications. When he isn't covering Tesla or other EV companies, you can find him writing and performing music, drinking a good cup of coffee, or hanging out with his cats, Banks and Freddie. Reach out at zach@teslarati.com, find him on X at @zacharyvisconti, or send us tips at tips@teslarati.com.

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Tesla urges New Jersey owners to oppose new bill that could block Robotaxi

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Credit: Grok

Tesla has launched a direct campaign targeting its customers in New Jersey, sending emails that warn of pending legislation that could effectively block true driverless technology in the state.

The email focuses on Senate Bill S.1677 and Assembly Bill A.3968, measures intended to create a three-year autonomous vehicle pilot program but laden with requirements that Tesla argues make unsupervised Robotaxis impossible.

According to the email, the bills impose “restrictions so severe that true driverless deployment would remain illegal.” Specific hurdles include mandates for human safety drivers during operations, multimillion-dollar insurance minimums, reportedly $5 million, and thresholds like 100,000 miles of demonstrated safe autonomous driving before any driverless approval.

Tesla contends these are arbitrary barriers that ignore real-world performance data and favor entrenched competitors over innovative technologies like its Full Self-Driving (FSD) system.

The push comes as Tesla has started expanding Robotaxi operations in states like Texas, where unsupervised vehicles are already providing rides in several cities. New Jersey, by contrast, risks falling behind. The company highlights in the email communication that more than 94 percent of serious crashes result from human error, meaning impairment, distraction, or fatigue. These are all problems that Robotaxis eliminate entirely.

In 2025, New Jersey recorded 582 traffic deaths, underscoring the human cost of delayed adoption.

Tesla’s outreach stresses the transformative potential of robotaxis. For families, they could offer safer school runs without drowsy or distracted drivers. For seniors and people with disabilities, robotaxis promise independence and reliable mobility.

In areas with limited public transit, they could deliver affordable, on-demand transportation, reducing congestion, emissions, and overall transportation costs. Economically, the company warns that restrictive rules could cost New Jersey jobs, innovation investment, and billions in potential growth as autonomous ride-hailing scales elsewhere.

Supporters of the legislation, including Sen. Andrew Zwicker, describe the pilot as a cautious framework with strong safety oversight, including incident reporting, expert task forces, and restrictions in sensitive zones like school areas. They view it as balancing innovation with public protection.

Tesla and pro-AV advocates counter that the bill lacks technology neutrality, creates insurmountable entry barriers for commercial deployment, and prioritizes process over outcomes — effectively functioning as a de facto ban on services like Robotaxi.

This latest clash echoes Tesla’s past battles in New Jersey over direct vehicle sales. The email directs owners to Tesla’s advocacy platform, where they can send customized messages to legislators calling for amendments: outcome-based safety standards, open competition, and clear pathways for fully driverless commercial operations.

As hearings approach, Tesla’s campaign frames the issue as a choice between protecting the status quo and embracing life-saving progress. With robotaxi technology already proving itself in permissive states, New Jersey owners are being asked to ensure their state doesn’t lock out the future of transportation.

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Tesla’s Navigation Nightmare: Why the easiest part of FSD might be the hardest

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Credit: TESLARATI

Turn-by-turn navigation is not new technology.

For over two decades, drivers have relied on Garmin, TomTom, and later smartphone apps like Google Maps and Waze to receive precise, reliable directions. These systems have guided millions safely through unfamiliar cities, highways, and backroads with remarkable effectiveness. They handle real-time traffic, construction detours, and complex intersections with minimal fuss.

Yet Tesla, the company that promised revolutionary Full Self-Driving (FSD), continues to struggle with this foundational capability. As FSD (Supervised) v14.3.4 has started rolling out to cars this week, navigation remains its glaring Achilles’ heel, undermining the entire autonomous vision.

Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much

Tesla’s FSD excels in many driving behaviors—smooth acceleration, confident lane changes in ideal conditions, and responsive handling of visible obstacles. However, when it comes to following a route accurately, the system falters repeatedly.

Owners report wrong turns, missed exits, inefficient routing through local roads instead of highways, phantom speed limit errors, and even directing vehicles to building rear entrances. Interventions for navigation issues often outnumber those for core driving maneuvers. Tesla has begun surveying owners specifically about these errors, acknowledging the problem after years of complaints.

Navigation is perhaps my biggest complaint when it comes to FSD, because sometimes, we do know better. Some of us have been living in our areas for our entire lives, but even those who have not have years or even decades of experience driving on local roads. We might know a little better about routing.

But the navigation mistakes are more than just FSD potentially taking a slightly different route that may or may not save you a few minutes. Sometimes, they’re genuinely mind-boggling.

This isn’t just annoying; it cascades into broader failures. A flawed route plan confuses the AI’s decision-making, leading to hesitant behavior, unnecessary disengagements, or dangerous maneuvers like attempting impossible U-turns or ignoring clear ramps. In a system meant to operate with minimal supervision, unreliable navigation erodes trust.

More often than not, false or plain incorrect navigation is what causes me to interrupt FSD operation. Unfortunately, I believe the latest FSD version is the worst example of it, and it leads me to believe that Tesla might be making some changes; they’ve just made them in the wrong direction.

It makes you wonder: Why is a company that has done so much with the progress of FSD and autonomy struggling so much with navigation, something that is not new and has been around a long time?

Multiple Data Sources

First, Tesla’s navigation relies on a fragile patchwork of multiple data sources—Google Maps, TomTom, OpenStreetMap, Valhalla, and its own fleet-derived data—stitched together rather than a single authoritative map. When these conflict on lane geometry, road status, or turn details, the system hesitates or chooses incorrectly.

Traditional GPS providers maintain centralized, regularly validated databases with professional curation and rapid updates. Tesla’s hybrid approach, while innovative in crowdsourcing, introduces inconsistencies that a purely vision-based or end-to-end AI approach may not easily reconcile in real time.

Persistent Learning

FSD seems to struggle with persistent learning from driver interventions.

Unlike consumer apps that quickly adapt to repeated corrections or user preferences (e.g., avoiding certain routes or remembering habitual detours), Tesla’s FSD often fails to internalize fixes on the same trip or across similar scenarios. Owners note making the same manual override multiple times without the routing engine updating its behavior meaningfully.

This stems from the neural architecture prioritizing real-time perception and control over long-term route memory and personalization, making navigation feel rigid and “opinionated” compared to the adaptive logic in Waze or Google Maps.

I noticed that when I asked Grok to try and get me home a certain way (a way that FSD routinely took in the past because it was the most efficient), it had to place a waypoint between my location at the time and my house. When I went to edit the waypoint out, as Grok had placed it for a way to get FSD to get off the highway at the right exit, it was stumped again, rerouted, and took a longer way home.

Reasoning, Scaling, and Intuition

Third, scaling navigation for unsupervised or robotaxi ambitions requires not just accuracy but adaptability and user-like reasoning. Current FSD often defaults to single routes that ignore driver preferences or real-world nuances like time-of-day traffic patterns. It fails to match the intuitive, context-aware planning that traditional systems have refined over the years.

Resolving navigation is critical for several reasons. Practically, it is the backbone of any autonomous journey: without trustworthy routing, the car cannot reliably reach destinations, rendering FSD useless for robotaxis or hands-free commutes. Safety depends on it—mismatched plans create hesitation in merges or intersections, increasing accident risk.

Economically, Tesla’s valuation and future hinge on FSD delivering unsupervised driving; persistent navigation flaws delay regulatory approval and erode consumer confidence. For owners who paid premiums for FSD, these issues represent unfulfilled promises. While it is unlikely Tesla will lose too many customers due to bad navigation, some will be frustrated with the constant need for human input.

Tesla has achieved miracles in electric vehicles and battery tech. Mastering turn-by-turn—technology Garmin nailed in the early 2000s—should not be this hard. By investing in tighter data integration, faster learning loops from interventions, and more intuitive routing algorithms, Tesla could close this gap.

Until then, FSD’s navigation struggles highlight a humbling truth: even the most ambitious innovator must sometimes master the basics before conquering the future.

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Tesla Cybertruck driver gets pickup seized for ‘legitimate concerns’ in UK

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A Tesla Cybertruck driver in the United Kingdom had their all-electric pickup seized by local police in the Greater Manchester area after the department cited “legitimate concerns.”

Last Thursday, police saw the pickup on the roads and decided to pull the driver over. Greater Manchester Police said:

“Whilst this may seem trivial to some, legitimate concerns exist around the safety of other road users or pedestrians if they were involved in a collision with the Cybertruck.”

The Cybertruck in question was, according to the BBC, registered and insured abroad and was confiscated. The driver, who is a UK resident, was reported.

The Greater Manchester Police Department then added:

“The Tesla Cybertruck is not road-legal in the UK and does not hold a certificate of conformity.”

The Cybertruck cannot be legally driven in the UK because it has no UK Type Approval for operation in the country. This is due to some safety concerns, which are related to its angular shape and design. The stainless steel exoskeleton has sharp edges and projections that violate UK/EU rules on pedestrian protection.

Tesla has considered creating what it referred to as an “international version” that would be approved for operation in Europe. However, there has been no real movement on that front by the company, as it has been focused on the Robotaxi rollout primarily.

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