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Tesla FSD Beta V11.3 starts shipping to employees (Release Notes)

Credit: Drive in EV/Twitter

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The release notes for Tesla FSD Beta V11.3 have been shared online. Observers from the electric vehicle community suggest that Tesla Full Self-Driving Beta 11.3 is rolling out to the company’s employee FSD Beta testers, at least for now. 

The following are Tesla’s FSD Beta V11.3 release notes

  • Enabled FSD Beta on highway. This unifies the vision and planning stack on and off-highway and replaces the legacy highway stack, which is over four years old. The legacy highway stack still relies on several single-camera and single-frame networks, and was setup to handle simple lane-specific maneuvers. FSD Beta’s multi-camera video networks and next-gen planner, that allows for more complex agent interactions with less reliance on lanes, make way for adding more intelligent behaviors, smoother control and better decision making.
  • Added voice drive-notes. After an intervention, you can now send Tesla an anonymous voice message describing your experience to help improve Autopilot.
  • Expanded Automatic Emergency Braking (AEB) to handle vehicles that cross ego’s path. This includes cases where other vehicles run their red light or turn across ego’s path, stealing the right-of-way.
  • Replay of previous collisions of this type suggests that 49% of the events would be mitigated by the new behavior. This improvement is now active in both manual driving and autopilot operation.
  • Improved autopilot reaction time to red light runners and stop sign runners by 500ms, by increased reliance on object’s instantaneous kinematics along with trajectory estimates.
  • Added a long-range highway lanes network to enable earlier response to blocked lanes and high curvature.
  • Reduced goal pose prediction error for candidate trajectory neural network by 40% and reduced runtime by 3X. This was achieved by improving the dataset using heavier and more robust offline optimization, increasing the size of this improved dataset by 4X, and implementing a better architecture and feature space.
  • Improved occupancy network detections by oversampling on 180K challenging videos including rain reflections, road debris, and high curvature.
  • Improved recall for close-by cut-in cases by 20% by adding 40k autolabeled fleet clips of this scenario to the dataset. Also improved handling of cut-in cases by improved modeling of their motion into ego’s lane, leveraging the same for smoother lateral and longitudinal control for cut-in objects.
  • Added “lane guidance module and perceptual loss to the Road Edges and Lines network, improving the absolute recall of lines by 6% and the absolute recall of road edges by 7%.
  • Improved overall geometry and stability of lane predictions by updating the “lane guidance” module representation with information relevant to predicting crossing and oncoming lanes.
  • Improved handling through high speed and high curvature scenarios by offsetting towards inner lane lines. 
  • Improved lane changes, including: earlier detection and handling for simultaneous lane changes, better gap selection when approaching deadlines, better integration between speed-based and nav-based lane change decisions and more differentiation between the FSD driving profiles with respect to speed lane changes.
  • Improved longitudinal control response smoothness when following lead vehicles by better modeling the possible effect of lead vehicles’ brake lights on their future speed profiles.
  • Improved detection of rare objects by 18% and reduced the depth error to large trucks by 9%, primarily from migrating to more densely supervised autolabeled datasets.
  • Improved semantic detections for school busses by 12% and vehicles transitioning from stationary-to-driving by 15%. This was achieved by improving dataset label accuracy and increasing dataset size by 5%.
  • Improved decision making at crosswalks by leveraging neural network based ego trajectory estimation in place of approximated kinematic models.
  • Improved reliability and smoothness of merge control, by deprecating legacy merge region tasks in favor of merge topologies derived from vector lanes.
  • Unlocked longer fleet telemetry clips (by up to 26%) by balancing compressed IPC buffers and optimized write scheduling across twin SOCs.

Several longtime FSD Beta testers have pointed out some key improvements that would likely be very appreciated by users in V11.3. These include the systems’ improved handling through high speed and high curvature scenarios, as well as improvements to Automatic Emergency Braking (AEB). With the improvements in place, FSD Beta V11.3 would behave closer to a proper human driver. 

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Comments from longtime Tesla FSD Beta testers also suggest that V11.3 is still only being released for company employees for now. Considering Tesla’s past updates, it would not be surprising if the greater FSD Beta fleet gets the V11.3 update in the coming week or so. This is, of course, unless V11.3 ends up going the way of FSD Beta V11, which was released to employees in November but not to the greater fleet of FSD Beta testers. 

The Teslarati team would appreciate hearing from you. If you have any tips, contact me at maria@teslarati.com or via Twitter @Writer_01001101.

Maria--aka "M"-- is an experienced writer and book editor. She's written about several topics including health, tech, and politics. As a book editor, she's worked with authors who write Sci-Fi, Romance, and Dark Fantasy. M loves hearing from TESLARATI readers. If you have any tips or article ideas, contact her at maria@teslarati.com or via X, @Writer_01001101.

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Tesla Model 3 named New Zealand’s best passenger car of 2025

Tesla flipped the switch on Full Self-Driving (Supervised) in September, turning every Model 3 and Model Y into New Zealand’s most advanced production car overnight.

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Credit: Tesla Asia/X

The refreshed Tesla Model 3 has won the DRIVEN Car Guide AA Insurance NZ Car of the Year 2025 award in the Passenger Car category, beating all traditional and electric rivals. 

Judges praised the all-electric sedan’s driving dynamics, value-packed EV tech, and the game-changing addition of Full Self-Driving (Supervised) that went live in New Zealand this September.

Why the Model 3 clinched the crown

DRIVEN admitted they were late to the “Highland” party because the updated sedan arrived in New Zealand as a 2024 model, just before the new Model Y stole the headlines. Yet two things forced a re-evaluation this year.

First, experiencing the new Model Y reminded testers how many big upgrades originated in the Model 3, such as the smoother ride, quieter cabin, ventilated seats, rear touchscreen, and stalk-less minimalist interior. Second, and far more importantly, Tesla flipped the switch on Full Self-Driving (Supervised) in September, turning every Model 3 and Model Y into New Zealand’s most advanced production car overnight.

FSD changes everything for Kiwi buyers

The publication called the entry-level rear-wheel-drive version “good to drive and represents a lot of EV technology for the money,” but highlighted that FSD elevates it into another league. “Make no mistake, despite the ‘Supervised’ bit in the name that requires you to remain ready to take control, it’s autonomous and very capable in some surprisingly tricky scenarios,” the review stated.

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At NZ$11,400, FSD is far from cheap, but Tesla also offers FSD (Supervised) on a $159 monthly subscription, making the tech accessible without the full upfront investment. That’s a game-changer, as it allows users to access the company’s most advanced system without forking over a huge amount of money.

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Tesla starts rolling out FSD V14.2.1 to AI4 vehicles including Cybertruck

FSD V14.2.1 was released just about a week after the initial FSD V14.2 update was rolled out.

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Credit: Grok Imagine

It appears that the Tesla AI team burned the midnight oil, allowing them to release FSD V14.2.1 on Thanksgiving. The update has been reported by Tesla owners with AI4 vehicles, as well as Cybertruck owners. 

For the Tesla AI team, at least, it appears that work really does not stop.

FSD V14.2.1

Initial posts about FSD V14.2.1 were shared by Tesla owners on social media platform X. As per the Tesla owners, V14.2.1 appears to be a point update that’s designed to polish the features and capacities that have been available in FSD V14. A look at the release notes for FSD V14.2.1, however, shows that an extra line has been added. 

“Camera visibility can lead to increased attention monitoring sensitivity.”

Whether this could lead to more drivers being alerted to pay attention to the roads more remains to be seen. This would likely become evident as soon as the first batch of videos from Tesla owners who received V14.21 start sharing their first drive impressions of the update. Despite the update being released on Thanksgiving, it would not be surprising if first impressions videos of FSD V14.2.1 are shared today, just the same.

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Rapid FSD releases

What is rather interesting and impressive is the fact that FSD V14.2.1 was released just about a week after the initial FSD V14.2 update was rolled out. This bodes well for Tesla’s FSD users, especially since CEO Elon Musk has stated in the past that the V14.2 series will be for “widespread use.” 

FSD V14 has so far received numerous positive reviews from Tesla owners, with numerous drivers noting that the system now drives better than most human drivers because it is cautious, confident, and considerate at the same time. The only question now, really, is if the V14.2 series does make it to the company’s wide FSD fleet, which is still populated by numerous HW3 vehicles. 

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Waymo rider data hints that Tesla’s Cybercab strategy might be the smartest, after all

These observations all but validate Tesla’s controversial two-seat Cybercab strategy, which has caught a lot of criticism since it was unveiled last year.

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Credit: wudapig/Reddit

Toyota Connected Europe designer Karim Dia Toubajie has highlighted a particular trend that became evident in Waymo’s Q3 2025 occupancy stats. As it turned out, 90% of the trips taken by the driverless taxis carried two or fewer passengers. 

These observations all but validate Tesla’s controversial two-seat Cybercab strategy, which has caught a lot of criticism since it was unveiled last year.

Toyota designer observes a trend

Karim Dia Toubajie, Lead Product Designer (Sustainable Mobility) at Toyota Connected Europe, analyzed Waymo’s latest California Public Utilities Commission filings and posted the results on LinkedIn this week.

“90% of robotaxi trips have 2 or less passengers, so why are we using 5-seater vehicles?” Toubajie asked. He continued: “90% of trips have 2 or less people, 75% of trips have 1 or less people.” He accompanied his comments with a graphic showing Waymo’s occupancy rates, which showed 71% of trips having one passenger, 15% of trips having two passengers, 6% of trips having three passengers, 5% of trips having zero passengers, and only 3% of trips having four passengers.

The data excludes operational trips like depot runs or charging, though Toubajie pointed out that most of the time, Waymo’s massive self-driving taxis are really just transporting 1 or 2 people, at times even no passengers at all. “This means that most of the time, the vehicle being used significantly outweighs the needs of the trip,” the Toyota designer wrote in his post.

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Cybercab suddenly looks perfectly sized

Toubajie gave a nod to Tesla’s approach. “The Tesla Cybercab announced in 2024, is a 2-seater robotaxi with a 50kWh battery but I still believe this is on the larger side of what’s required for most trips,” he wrote.

With Waymo’s own numbers now proving 90% of demand fits two seats or fewer, the wheel-less, lidar-free Cybercab now looks like the smartest play in the room. The Cybercab is designed to be easy to produce, with CEO Elon Musk commenting that its product line would resemble a consumer electronics factory more than an automotive plant. This means that the Cybercab could saturate the roads quickly once it is deployed.

While the Cybercab will likely take the lion’s share of Tesla’s ride-hailing passengers, the Model 3 sedan and Model Y crossover would be perfect for the remaining  9% of riders who require larger vehicles. This should be easy to implement for Tesla, as the Model Y and Model 3 are both mass-market vehicles. 

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