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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.

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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. 

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.

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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 launches solution to end Supercharger fights once and for all

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Credit: Tesla

Tesla is launching its solution to end Supercharger fights once and for all, eliminating any confusion on who is to charge next at a congested location.

Last year, a notable incident at a Tesla Supercharger led to a fight, and it all stemmed from a disagreement over who arrived at the location first.

Congestion at Tesla Superchargers is a pretty infrequent occurrence for most of us, but there are more congested and popular areas where wait times can be extensive. An unfortunate growing pain of EV ownership is the plain fact that chargers are not as available as gas pumps, and there are, at times, lines to charge.

This can cause tensions to flare and people to get entitled when visiting Superchargers. Nobody wants to spend hours at a Supercharger, but now, there will be no more confusion when there is a queue, and that’s thanks to Tesla’s new Virtual Queue for Superchargers.

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Tesla is finally starting to build out the Virtual Supercharger Queue, according to Not a Tesla App, but it still relies on drivers to make it work.

When a driver is near a Supercharger that is full, a message will pop up on the Tesla App, using the driver’s location to determine their eligibility to join the virtual queue.

The app states:

“While the app is closed, Tesla uses your location to notify you of accurate wait times at Superchargers when you arrive.”

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Another message within the app states:

“There is a waitlist to charge. Are you sure you want to start a charging session now?”

This sounds as if it will require drivers to act appropriately and only plug in when the app prompts them to do so, by letting them know it is their turn.

The app will notify the driver of their position in the queue, as well as how many vehicles are ahead of them.

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Tesla launches first ‘true’ East Coast V4 Supercharger: here’s what that means

The company announced a while back that it would be working on a solution for this issue. Personally, I’ve only had to wait at a Supercharger for a charge on one occasion, and there was a line of between 3 and 10 cars during this singular occurrence.

There were no conflicts or arguments about who had arrived first, but there was some discussion between several drivers during my time there about who was to charge first. Throw a non-Tesla EV into the mix, one that can only charge at a pull-in spot, and that causes even more of a complication.

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Tesla offers awesome Free Supercharging incentive on an unexpected vehicle

In the past, Tesla has used Free Supercharging to incentivize the purchase of its expensive vehicles, like the Model S and Model X. However, those vehicles are leaving the company lineup, and Tesla saw a benefit from applying the incentive to another car.

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Credit: Tesla Charging | X

Tesla is offering an awesome new Free Supercharging incentive on a vehicle that is sort of unexpected.

In the past, Tesla has used Free Supercharging to incentivize the purchase of its expensive vehicles, like the Model S and Model X. However, those vehicles are leaving the company lineup, and Tesla saw a benefit from applying the incentive to another car.

Tesla North America has introduced a compelling new incentive aimed at boosting Model 3 sales. Starting with orders placed on or after April 24, buyers of the Model 3 Premium (Long Range) and Performance variants in the United States will receive one full year of complimentary Supercharging.

The offer applies exclusively to new vehicle orders and does not extend to existing owners or other trims like the base Rear-Wheel Drive model.

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The announcement underscores Tesla’s continued dominance in EV charging infrastructure.

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While the incentive provides 12 months of zero-cost access to the Supercharger network, Tesla also reiterated its pricing structure: all Tesla vehicles receive the lowest Supercharging rates.

Non-Tesla EVs, by contrast, pay approximately 40 percent more per kWh or must purchase a subscription to access the network at standard rates. This tiered approach highlights the strategic value of owning a Tesla, where seamless integration with the world’s largest and most reliable fast-charging network remains a key differentiator.

For prospective buyers, the savings can be substantial. Depending on driving habits, a typical Model 3 owner might log 12,000–15,000 miles annually.

With average Supercharging costs around $0.40–$0.50 per kWh, one year of free sessions could translate to $800–$1,200 in avoided expenses.

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That effectively lowers the total cost of ownership and makes long-distance travel more affordable from day one. Early delivery customers have already noted similar past incentives, with one Cybertruck owner reporting over $2,400 saved in just six months under similar offers that Tesla has deployed in the past.

The timing of the offer appears strategic. Tesla faces growing competition from other automakers expanding their own charging networks and offering aggressive EV incentives.

By bundling free Supercharging rather than discounting the vehicle’s MSRP, Tesla preserves perceived value while directly addressing one of the biggest barriers for new EV adopters: charging costs and convenience.

The move also encourages higher-mileage use of the network, generating valuable real-world data for Tesla’s autonomous driving development.

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Why Tesla would apply this incentive to the Model 3 is pretty interesting. It usually is a pretty good incentive to move units out the door, so there’s some speculation whether Tesla is planning to launch new upgrades to the mass-market sedan in the coming months, and the company wants to move what will be outdated units from its inventory.

However, there is also just the idea that Tesla could be attempting to stimulate some early quarter demand for the Model 3, especially as the Model Y continues to sell very well. Tesla’s loss of the $7,500 EV tax credit last year had an impact on sales, and Tesla might be testing some formidable options to see if it can add some demand once again.

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Tesla Cybercab gets crazy change as mass production begins

Tesla has officially kicked off mass production of its groundbreaking Cybercab robotaxi at Giga Texas, and the first units rolling off the line feature a striking transformation that’s turning heads across the EV community.

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Credit: TechOperator | X

Tesla Cybercab has evidently received a pretty crazy change from an aesthetic standpoint, as the company has made the decision to offer an additional finish on the vehicle as mass production is starting.

Tesla has officially kicked off mass production of its groundbreaking Cybercab robotaxi at Giga Texas, and the first units rolling off the line feature a striking transformation that’s turning heads across the EV community.

VIN Zero—the very first production Cybercab—showcases a vibrant champagne gold exterior with a high-gloss finish, a dramatic departure from the flat, matte-wrapped prototypes that debuted at the 2024 “We, Robot” event.

This glossy sheen is a pretty big pivot from what was initially shown by Tesla. The company has maintained a pretty flat tone in terms of anything related to custom colors or finishes.

A specialized clear coat or process delivers the deep, reflective gloss without conventional painting. The result is a premium, mirror-like shine, and it looks pretty good, and gives the compact two-seater a more luxurious and futuristic presence than the subdued matte prototypes.

Photos shared by Tesla community members reveal VIN Zero in a showroom-like setting at Giga Texas, highlighting refined panel gaps, large aero wheel covers, and the signature no-steering-wheel, no-pedals interior optimized for full autonomy.

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The open frunk in some images offers a glimpse of practical storage, while the overall build quality appears more polished than that of test mules.

This glossy evolution aligns with Tesla’s broader production ramp. After the first unit in February 2026, the company has shifted to volume manufacturing, with dozens of units already spotted in outbound lots. CEO Elon Musk and the team aim for hundreds per week, paving the way for unsupervised FSD robotaxi networks that could slash ride costs to pennies per mile.

The Cybercab holds Tesla’s grand ambitions of operating a full-service ride-hailing service without any drivers in its grasp. Tesla has yet to solve autonomy, but is well on its way, and although its timelines are usually a bit off, improvements often come through the Over-the-Air updates to the Full Self-Driving suite.

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