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Tesla’s vehicles led U.S. EV sales again last quarter: report

Tesla, Ford, and Chevrolet’s models led the pack in Q1, while more new EVs hit the road than ever.

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Credit: Joe Tegtmeyer

Recent data has shown that Tesla’s Model Y and Model 3 remained the top-selling electric vehicle (EV) models in the U.S. in the first quarter, despite a decline in overall sales in the market.

As detailed in the latest Kelley Blue Book EV sales report, shared by Cox Automotive on Thursday, Tesla’s Model Y and Model 3 outsold the next several models combined during the first quarter, while the Cybertruck was the tenth best-selling EV overall.

Tesla sold 64,051 Model Y units, representing a 33.8 percent drop year over year, along with selling 52,520 Model 3 units, marking a 70.3 percent increase year over year, to outpace the next several models combined. The Tesla Cybertruck sold 6,406 units, while the Model S and X sold 1,280 and 3,843 units, respectively.

Tesla also launched a new version of the Model Y in the first quarter, likely explaining at least a part of the decline, though the brand also faces continued pressure from the public, as many have targeted stores and vehicles in protesting Elon Musk and the Trump administration.

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Meanwhile, the Ford Mustang Mach-E, the Chevy Equinox EV, and the Honda Prologue followed and made up the rest of the top five, with 11,607, 10,329, and 9,561 units sold, respectively. A number of models were also introduced to the market last year, such as the Porsche Macan, the VW ID.Buzz, and Volvo’s EX30 and EX90 models. Honda and Acura also added over 14,000 EVs to U.S. roads, marking an increase from having no products in Q1 2024.

Additionally, many models such as the Chevy Equinox EV, the Honda Prologue, and the VW ID.4 all climbed in the rankings from the full-year 2024 EV sales list, and it will be interesting to see how these and other emerging models hold as the year rolls on.

Cox also points out that Tesla’s overall sales were down 8.6 percent from last year’s first quarter, while General Motors (GM) sold over 30,000 EVs across its brands to lead the sector in sales growth.

See the full list of BEVs sold below, as ranked by volume. You can also check out the full Q1 EV sales data from Cox Automotive here, or read the firm’s press release on the report here.

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READ MORE ON U.S. EV SALES: Tesla average transaction prices (ATP) rise in March 2025: Cox Automotive

EV models sold in the U.S. in Q1 2025, ranked by volume

  1. Tesla Model Y: 64,051
  2. Tesla Model 3: 52,520
  3. Ford Mustang Mach-E: 11,607
  4. Chevrolet Equinox EV: 10,329
  5. Honda Prologue: 9,561
  6. Hyundai Ioniq 5: 8,611
  7. VW ID.4: 7,663
  8. Ford F-150 Lightning: 7,187
  9. BMW i4: 7,125
  10. Tesla Cybertruck: 6,406
  11. Chevrolet Blazer EV: 6,187
  12. Toyota BZ4X: 5,610
  13. Rivian R1S: 5,357
  14. Cadillac Lyriq: 4,300
  15. Acura ZDX: 4,813
  16. Nissan Ariya: 4,148
  17. Tesla Model X: 3,843
  18. Ford E-Transit and Kia EV9 (tied): 3,756
  19. Kia EV6: 3,738
  20. BMW iX: 3,626
  21. GMC Hummer Truck/SUV: 3,479
  22. Porsche Macan: 3,339
  23. Hyundai Ioniq 6: 3,318
  24. Audi Q6 e-tron: 3,246
  25. Subaru Solterra: 3,131
  26. Chevrolet Silverado: 2,383
  27. Jeep Wagoneer EV: 2,595
  28. Nissan Leaf: 2,323
  29. Dodge Charger EV: 1,947
  30. Rivian R1T: 1,727
  31. Cadillac Escalade EV: 1,956
  32. VW ID.Buzz: 1,901
  33. BMW i5: 1,899
  34. Audi Q4 e-tron: 1,874
  35. Mercedes EQB: 1,622
  36. Cadillac Optiq: 1,716
  37. Rivian EDV500/700: 1,469
  38. Lexus RZ: 1,453
  39. Tesla Model S: 1,280
  40. GMC Sierra EV: 1,249
  41. Volvo EX30: 1,185
  42. Kia Niro: 1,162
  43. Porsche Taycan: 1,019
  44. Volvo EX90: 1,000
  45. Hyundai Kona EV: 914
  46. BMW i7: 888
  47. Mercedes EQE: 742
  48. Genesis GV60: 733
  49. Genesis GV70: 712
  50. Mini Countryman: 693
  51. Mercedes EQE: 742
  52. Audi Q8 e-tron: 535
  53. Mercedes G-Class and EQS (tied): 509
  54. Jaguar I-Pace: 381
  55. Volvo C40: 315
  56. Chevrolet Brightdrop 400/600: 274
  57. Audi e-tron: 250
  58. Volvo XC40: 218
  59. Mercedes E-Sprinter: 90
  60. Genesis G80: 51
  61. Chevrolet Bolt: 13
  62. Mini Cooper: 3

*Additional EV Models: 5,930

*The additional EV models category is likely made up of low-volume, luxury, and niche EV makers, such as those from Lucid and Polestar. However, at the time of writing, Cox Automotive has not yet responded to Teslarati’s request for comment on which vehicles were excluded.

Top 10 EV sellers by brand in the U.S. in Q1 2025

  1. Tesla: 128,100
  2. Ford: 22,500
  3. Chevrolet: 19,186
  4. BMW:13,538
  5. Hyundai: 12,843
  6. VW: 9,564
  7. Honda: 9,561
  8. Kia: 8,656
  9. Rivian: 8,553
  10. Cadillac: 7,972

These were the best-selling EV brands in the U.S. in Q1

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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.

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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.

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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

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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.

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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.

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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.

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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.

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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:

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“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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