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.
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Tesla has added the 15th automaker to the growing list of companies whose EVs can utilize the Supercharger Network this year, as BMW is the latest company to gain access to the largest charging infrastructure in the world.
BMW became the 15th company in 2025 to gain Tesla Supercharger access, after the company confirmed to its EV owners that they could use any of the more than 25,000 Supercharging stalls in North America.
Welcome @BMW owners.
Download the Tesla app to charge → https://t.co/vnu0NHA7Ab
— Tesla Charging (@TeslaCharging) December 10, 2025
Newer BMW all-electric cars, like the i4, i5, i7, and iX, are able to utilize Tesla’s V3 and V4 Superchargers. These are the exact model years, via the BMW Blog:
- i4: 2022-2026 model years
- i5: 2024-2025 model years
- 2026 i5 (eDrive40 and xDrive40) after software update in Spring 2026
- i7: 2023-2026 model years
- iX: 2022-2025 model years
- 2026 iX (all versions) after software update in Spring 2026
With the expansion of the companies that gained access in 2025 to the Tesla Supercharger Network, a vast majority of non-Tesla EVs are able to use the charging stalls to gain range in their cars.
So far in 2025, Tesla has enabled Supercharger access to:
- Audi
- BMW
- Genesis
- Honda
- Hyundai
- Jaguar Land Rover
- Kia
- Lucid
- Mercedes-Benz
- Nissan
- Polestar
- Subaru
- Toyota
- Volkswagen
- Volvo
Drivers with BMW EVs who wish to charge at Tesla Superchargers must use an NACS-to-CCS1 adapter. In Q2 2026, BMW plans to release its official adapter, but there are third-party options available in the meantime.
They will also have to use the Tesla App to enable Supercharging access to determine rates and availability. It is a relatively seamless process.
News
Tesla adds new feature that will be great for crowded parking situations
This is the most recent iteration of the app and was priming owners for the slowly-released Holiday Update.
Tesla has added a new feature that will be great for crowded parking lots, congested parking garages, or other confusing times when you cannot seem to pinpoint where your car went.
Tesla has added a new Vehicle Locator feature to the Tesla App with App Update v4.51.5.
This is the most recent iteration of the app and was priming owners for the slowly-released Holiday Update.
While there are several new features, which we will reveal later in this article, perhaps one of the coolest is that of the Vehicle Locator, which will now point you in the direction of your car using a directional arrow on the home screen. This is similar to what Apple uses to find devices:
Interesting. The location arrow in the Tesla app now points to your car when you’re nearby. pic.twitter.com/b0yjmwwzxN
— Whole Mars Catalog (@wholemars) December 7, 2025
In real time, the arrow gives an accurate depiction of which direction you should walk in to find your car. This seems extremely helpful in large parking lots or unfamiliar shopping centers.
Getting to your car after a sporting event is an event all in itself; this feature will undoubtedly help with it:
The nice little touch that Tesla have put in the app – continuous tracking of your vehicle location relative to you.
There’s people reporting dizziness testing this.
To those I say… try spinning your phone instead. 😉 pic.twitter.com/BAYmJ3mzzD
— Some UK Tesla Guy (UnSupervised…) (@SomeUKTeslaGuy) December 8, 2025
Tesla’s previous app versions revealed the address at which you could locate your car, which was great if you parked on the street in a city setting. It was also possible to use the map within the app to locate your car.
However, this new feature gives a more definitive location for your car and helps with the navigation to it, instead of potentially walking randomly.
It also reveals the distance you are from your car, which is a big plus.
Along with this new addition, Tesla added Photobooth features, Dog Mode Live Activity, Custom Wraps and Tints for Colorizer, and Dashcam Clip details.
🚨 Tesla App v4.51.5 looks to be preparing for the Holiday Update pic.twitter.com/ztts8poV82
— TESLARATI (@Teslarati) December 8, 2025
All in all, this App update was pretty robust.
Tesla CEO Elon Musk shaded Waymo in a post on X on Wednesday, stating the company “never really had a chance” and that it “will be obvious in hindsight.”
Tesla and Waymo are the two primary contributors to the self-driving efforts in the United States, with both operating driverless ride-hailing services in the country. Tesla does have a Safety Monitor present in its vehicles in Austin, Texas, and someone in the driver’s seat in its Bay Area operation.
Musk says the Austin operation will be completely void of any Safety Monitors by the end of the year.
🚨 Tesla vs. Waymo Geofence in Austin https://t.co/A6ffPtp5xv pic.twitter.com/mrnL0YNSn4
— TESLARATI (@Teslarati) December 10, 2025
With the two companies being the main members of the driverless movement in the U.S., there is certainly a rivalry. The two have sparred back and forth with their geofences, or service areas, in both Austin and the Bay Area.
While that is a metric for comparison now, ultimately, it will not matter in the coming years, as the two companies will likely operate in a similar fashion.
Waymo has geared its business toward larger cities, and Tesla has said that its self-driving efforts will expand to every single one of its vehicles in any location globally. This is where the true difference between the two lies, along with the fact that Tesla uses its own vehicles, while Waymo has several models in its lineup from different manufacturers.
The two also have different ideas on how to solve self-driving, as Tesla uses a vision-only approach. Waymo relies on several things, including LiDAR, which Musk once called “a fool’s errand.”
This is where Tesla sets itself apart from the competition, and Musk highlighted the company’s position against Waymo.
Jeff Dean, the Chief Scientist for Google DeepMind, said on X:
“I don’t think Tesla has anywhere near the volume of rider-only autonomous miles that Waymo has (96M for Waymo, as of today). The safety data is quite compelling for Waymo, as well.”
Musk replied:
“Waymo never really had a chance against Tesla. This will be obvious in hindsight.”
Waymo never really had a chance against Tesla. This will be obvious in hindsight.
— Elon Musk (@elonmusk) December 10, 2025
Tesla stands to have a much larger fleet of vehicles in the coming years if it chooses to activate Robotaxi services with all passenger vehicles. A simple Over-the-Air update will activate this capability, while Waymo would likely be confined to the vehicles it commissions as Robotaxis.
Tesla adds 15th automaker to Supercharger access in 2025
Tesla adds new feature that will be great for crowded parking situations
