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.
Here are the V11.3 release notes again if you haven't seen them. Very happy to see improvements in rain reflections as that was rare, but could give some insane errors #FSDBeta @elonmusk pic.twitter.com/ZIOcIhmUMd
— Dirty Tesla (@DirtyTesLa) February 20, 2023
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.
News
Tesla Robotaxi app update now tells riders if Cybercab is the better choice
Tesla’s Robotaxi app now shows ETAs, wait times and availability for Cybercab and Model Y.
Tesla has rolled out a new vehicle selection screen in its Robotaxi app, and it puts the numbers riders care about most in front of them before they book.
Version 26.11.0 of the app shows the estimated arrival time, the expected wait and current availability for each vehicle option on a single screen, according to a video shared by @gheeunit on X on November 7. Riders deciding between a Cybercab and a Model Y Robotaxi can now compare those figures side by side instead of picking a car first and learning how long it will take afterward.
Tesla first gave riders that choice on September 3, the day paid Cybercab rides began in Austin. The original version of the screen listed the Cybercab, which seats two, next to the Model Y, which seats four. A later build, 26.8.2, added a seating capacity indicator so groups knew which car would fit them. What it did not show was whether choosing the Cybercab meant standing on the curb a few extra minutes.
Newest version of @robotaxi app has a new vehicle selector UI for choosing between Cybercab and Model Y and shows you the fare for both simultaneously! https://t.co/7qoDQ0vACX — mantequilla 🧈 (@gheeunit) November 7, 2026
That question matters more now than it did two months ago. Tesla had 45 Cybercabs on the Texas DMV roster when rides started. By late October the state listed 573, alongside 631 Model Ys, and community trackers logged a record 1,576 Cybercab sightings across Austin on Halloween alone. With two large fleets sharing one service area, the closest car and the quickest pickup are not always the same vehicle.
Inline availability also changes what happens when demand spikes. If no Cybercab is free nearby, the rider sees that on the selection screen rather than after trying to book one.
For now the comparison is mostly an Austin feature. Riders in Dallas, Houston, Fort Worth and the Florida markets are still matched with Model Y vehicles, though Tesla said on its third quarter earnings call that Cybercab rides would launch in Dallas this month.
The update follows a steady run of smaller changes to the rider experience. Late last month Tesla brought a quiet mode that blacks out the cabin screen to Model Y Robotaxis after first testing it in the Cybercab, and it has stretched Austin service to run from 6 a.m. to 2 a.m.
The Cybercab side of that selection screen is about to get much busier. Elon Musk said this week that Tesla will wind down Cybertruck production at Gigafactory Texas around the middle of 2027 to make room for more Cybercab output, and Tesla has said it is aiming to get Cybercabs to customers by the end of this year.
Tesla has not published official release notes for version 26.11.0.
Tesla is ending Cybertruck production sometime in mid-2027, according to CEO Elon Musk.
Musk made the announcement on X last night, which came as a shock to many. He said that the Cybertruck will end production “to make room for increased Cybercab production” at Gigafactory Texas.
It is a huge blow to the fans of Tesla who have come to love the Cybertruck and identify with it as a symbol of their fandom. It has been the best-selling electric pickup, but it has had an underwhelming sales performance in terms of what was expected. This is mostly due to Tesla not meeting the prices it planned to offer the Cybertruck, as its unveiling and actual release were four years apart.
Tesla will be winding down production of the Cybertruck at Gigafactory Texas around the middle of next year to make room for increased Cybercab production
— Elon Musk (@elonmusk) November 6, 2026
Overall, the responses were mixed. Some fans understood the move toward Cybercab production, especially as Tesla is truly pushing the autonomous future through its Robotaxi platform. However, others did not understand it.
“Damn, how many Cybercabs do you guys need?” one response read. Another said it was “Sad but understandable.”Even analyst Gary Black had responded to the news, stating he hoped Tesla planned to replace it with a traditional pickup design.
It doesn’t seem like that will be the case.
Tesla is so hell-bent on delivering autonomy and eventually providing a driverless service that owning a car seems like an arbitrary idea, according to their thesis. Instead, Cybercabs will be available to pick you up and drop you off on demand, safely, without any human help.
As a result, Tesla has thinned its lineup considerably, and one can only ask where the vehicle lineup goes from here. Eventually, it seems like Cybercab could be the only vehicle that Tesla will sell.
Elon Musk
SpaceX’s next Starship flight set to make history on Friday the 13th
SpaceX is targeting Friday, November 13 for Starship Flight 15 and its first ship catch.
SpaceX is targeting Friday, November 13 for Starship Flight 15, the mission the company plans to use for its first attempt at catching the ship itself with the launch tower.
SpaceX Vice President of Launch Kiko Dontchev shared the date on stage at the UP.Summit on Thursday, according to Ars Technica’s Eric Berger, who was in attendance. It is the first launch target to come directly from a SpaceX executive. Until now, the public schedule had relied on FAA air traffic planning slides, which listed Flight 15 for no earlier than November 8 and later November 12. SpaceX has not posted an official mission page yet, and no launch time has been shared.
The date lands inside the window Elon Musk sketched out last month. Speaking at Giga Texas on October 10, Musk said the flight would “probably launch a little bit before Thanksgiving,” as Teslarati reported. On SpaceX’s third quarter earnings call ten days later, he confirmed that Flight 15 would try to catch both the Super Heavy booster and the ship, and put the odds of a successful ship catch at “more likely than not.” SpaceX also aired an animation of the maneuver during that webcast, showing the ship swinging vertical over Starbase before dropping into the tower’s chopsticks.
The hardware is ready. Booster 22 fired all 33 of its Raptor engines for a full duration static fire at Pad 2 on October 25. Ship 42 followed with a single engine burn simulating a deorbit maneuver on October 26 and a 60 second firing of all six engines the next day, according to NASASpaceflight. Ship 42 had already rehearsed the catch in September, when the Pad 2 arms lifted it into position and crews connected the quick disconnect arm while the vehicle hung from the tower.
The remaining hurdle is regulatory. The FAA’s Starship page does not yet list a Flight 15 license. SpaceX President Gwynne Shotwell said in October that, after “significant constructive engagement with the FAA,” she expects the license to cover a return to the launch site and a tower catch for both stages. Bringing the ship home means a reentry path that heads toward land, rather than ending over open ocean as every Starship flight so far has.
SpaceX has caught Super Heavy three times, on Flights 5, 7 and 8, but the ship comes back from orbital velocity and has never been caught. Flight 14 on September 28 was the first Starship to reach orbit, deploying 26 Starlink V3 satellites before splashing down despite an early engine shutdown that Musk blamed on engine computer software.
Musk has called a successful ship catch “the first time that there’s been full recovery of an orbital class rocket,” and he has already named the step after it: a Flight 16 where both the booster and the ship fly again. NASASpaceflight reports that Ship 43, the next vehicle in line, is set for static fire testing in December.
Tesla Robotaxi app update now tells riders if Cybercab is the better choice
Tesla is ending Cybertruck production
