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Tesla FSD Beta 10.69 release notes highlight better left turns, smoother driving
Tesla released FSD Beta 10.69 to the first round of testers over the weekend. Read v.10.69’s release notes below to check out the latest improvements.
Stay in your Lanes
- Added a new “deep lane guidance” module to the Vector Lanes neural network which fuses features extracted from the video streams with coarse map data, i.e. lane counts and lane connectivites. This architecture achieves a 44% lower error rate on lane topology compared to the previous model, enabling smoother control before lanes and their connectivities becomes visually apparent. This provides a way to make every Autopilot drive as good as someone driving their own commute, yet in a sufficiently general way that adapts for road changes.
Nothing Like Smooth Driving
- Improved overall driving smoothness, without sacrificing latency, through better modeling of system and actuation latency in trajectory planning. Trajectory planner now independently accounts for latency from steering commands to actual steering actuation, as well as acceleration and brake commands to actuation. This results in a trajectory that is a more accurate model of how the vehicle would drive. This allows better downstream controller tracking and smoothness while also allowing a more accurate response during harsh manevuers.
- Increased smoothness for protected right turns by improving the association of traffic lights with slip lanes vs yield signs with slip lanes. This reduces false slowdowns when there are no relevant objects present and also improves yielding position when they are present.
- Reduced false slowdowns near crosswalks. This was done with improved understanding of pedestrian and bicyclist intent based on their motion.
- Enabled creeping for visibility at any intersection where objects might cross ego’s path, regardless of presence of traffic controls.
- Improved accuracy of stopping position in critical scenarios with crossing objects, by allowing dynamic resolution in trajectory optimization to focus more on areas where finer control is essential.
- Reduced latency when starting from a stop by accounting for lead vehicle jerk.
Chuck’s Left Turn
- Improved unprotected left turns with more appropriate speed profile when approaching and exiting median crossover regions, in the presence of high speed cross traffic (“Chuck Cook style” unprotected left turns). This was done by allowing optimizable initial jerk, to mimic the harsh pedal press by a human, when required to go in front of high speed objects. Also improved lateral profile approaching such safety regions to allow for better pose that aligns well for exiting the region. Finally, improved interaction with objects that are entering or waiting inside the median crossover region with better modeling of their future intent.
Safety is Number 1
- Added control for arbitrary low-speed moving volumes from Occupancy Network. This also enables finer control for more precise object shapes that cannot be easily represented by a cuboid primitive. This required predicting velocity at every 3D voxel. We may now control for slow-moving UFOs.
- Made speed profile more comfortable when creeping for visibility, to allow for smoother stops when protecting for potentially occluded objects.
- Improved speed when entering highway by better handling of upcoming map speed changes, which increases the confidence of merging onto the highway.
- Enabled faster identification of red light runners by evaluating their current kinematic state against their expected braking profile.
Tesla FSD “Brain” Improvements
- Upgraded Occupancy Network to use video instead of images from single time step. This temporal context allows the network to be robust to temporary occlusions and enables prediction of occupancy flow. Also, improved ground truth with semantics-driven outlier rejection, hard example mining, and increasing the dataset size by 2.4x.
- Upgraded to a new two-stage architecture to produce object kinematics (e.g. velocity, acceleration, yaw rate) where network compute is allocated O(objects) instead of O(space). This improved velocity estimates for far away crossing vehicles by 20%, while using one tenth of the compute.
- Improved geometry error of ego-relevant lanes by 34% and crossing lanes by 21% with a full Vector Lanes neural network update. Information bottlenecks in the network architecture were eliminated by increasing the size of the per-camera feature extractors, video modules, internals of the autoregressive decoder, and by adding a hard attention mechanism which greatly improved the fine position of lanes.
- Improved recall of animals by 34% by doubling the size of the auto-labeled training set.
- Increased recall of forking lanes by 36% by having topological tokens participate in the attention operations of the autoregressive decoder and by increasing the loss applied to fork tokens during training.
- Improved velocity error for pedestrians and bicyclists by 17%, especially when ego is making a turn, by improving the onboard trajectory estimation used as input to the neural network.
- Improved recall of object detection, eliminating 26% of missing detections for far away crossing vehicles by tuning the loss function used during training and improving label quality.
- Improved object future path prediction in scenarios with high yaw rate by incorporating yaw rate and lateral motion into the likelihood estimation. This helps with objects turning into or away from ego’s lane, especially in intersections or cut-in scenarios.
Tesla is rolling out FSD Beta v.10.69 in phases, starting with ~1,000 testers over the weekend. Once the update is rolled out for wide release, the price of FSD Beta will increase.
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Tesla has expanded the footprint of a massive safety feature worldwide with a recent Software Update labeled as 2026.20.6. The expansion of the “Blind Spot Warning While Parked” feature represents the more widespread availability of the feature, which aims to prevent “dooring.”
Dooring is when a driver or passenger opens a car door into the path of an oncoming road user, usually a cyclist or motorcyclist. It is among the most common types of cycling accidents, the League of American Bicyclists says.
For this reason, Tesla created a feature that warns occupants not to open the door because an object is approaching. The feature will sound a chime, and it will also delay the opening of the door to prevent an incident.
The release notes state (via Not a Tesla App):
“If you attempt to open a door while an approaching object is detected in your blind spot (for example, a bicyclist approaching from behind) a chime sounds, and your door will not open upon initial button press. Wait a short time and press the button a second time to override the warning.”
Tesla initially rolled out this feature back in 2024 with the Model 3 “Highland.” However, it remained with the Model 3 exclusively for over a year; that was until Tesla added it to the Cybertruck this past Spring.
Now, it is making its way to the new Model Y, 2021 and newer Model S, and 2021 or newer Model X.
The prevention of dooring incidents could eliminate many injuries to cyclists, especially in an urban setting. Dooring accounts for 10-20 percent of bike-related crashes in major cities, and over 17,000 dooring-related incidents were treated in the U.S. over the course of a decade. These usually involve fractures, contusions, and head trauma.
Tesla confirmed this morning that it has sent the first production units, manufactured with no steering wheel or pedals, to on-road testing in Austin, sharing video of the first rides with no human controls.
The lack of steering wheels and pedals in the Cybercab aligns with Tesla’s self-certification of Robotaxi as Level 4 SAE, a platform it plans to make widespread through internal vehicles and customer-owned cars that will operate and generate revenue for individuals.
The start of these engineering tests is a major signal for Tesla, which plans to bring driverless, wheel-less, and pedal-less Cybercabs to market in the coming months. With production already well underway at Gigafactory Texas, where the Cybercab is built, there is some inclination to believe the first public rides could happen sooner rather than later.
Engineering tests of the first production Cybercab have begun in Austin pic.twitter.com/fk3KQvcE8a
— Tesla (@Tesla) June 30, 2026
Tesla’s engineering tests will put the Cybercab in real-world scenarios, testing not only the hardware, but more importantly, the software that drives the car around Austin with nobody supervising it within the car.
This is perhaps the biggest part of the internal testing process, especially prior to allowing regular, everyday people to hail the Cybercab for an autonomous ride. These early rides serve as a true benchmark for Tesla: How many rides can it achieve safely? How many miles did it travel consecutively without needing an intervention? What scenarios challenge the Full Self-Driving suite the most?
The proper precautions have already been put into place as well, as Tesla released the First Responders Guide to Cybercab over the weekend, ensuring that emergency services have 24/7 access to Robotaxi Assistance, as well as other boundaries, such as Geofencing features that can be used to redirect autonomous vehicle traffic due to accidents, road closures, construction, or maintenance.
Cybercab seems genuinely close to being added to the Robotaxi fleet in Austin, but Tesla has prioritized safety throughout this entire process. Therefore, we think it could be months before it truly starts giving rides to the public. People have been frustrated with this, but Robotaxi in Austin has a tremendous safety record so far, so the slow rollout has kept people safe and accidents to a minimum.
The most important thing is that Tesla continues to show consistent progress in the Cybercab’s ramp-up toward fleet addition. A few weeks back, we saw the EPA reward the Cybercab a Certificate of Conformity, allowing it to enter the stream of commerce. Then, we saw Tesla add decals, signaling that it was likely about to start testing it publicly. That has now happened.
The next big move will be the announcement of the first rides, so this Summer should be filled with anticipation.
For years, there have been images and videos across social media platforms that have reminded me of when I was a 15-year-old kid teased by “Xbox 720” videos on YouTube. These videos are of the supposed “Tesla Phone” that Elon Musk was secretly developing in between leading Tesla with its electric cars and SpaceX with its reusable rockets.
Would you buy a Tesla phone ? pic.twitter.com/aaTwvvIJit
— Tesla Owners Silicon Valley (@teslaownersSV) October 6, 2023
Although Musk has put those rumors to bed several times, it was never completely out of the realm that he could get involved in cell phones in some capacity. Think outside the box and more macro-level, though. Instead of reinventing the computer, Musk reinvented connectivity by developing Starlink with SpaceX.
It could be something similar, TD Cowen analyst Gregory Williams said in a note last week, where he hinted SpaceX could be gathering some steam to acquire T-Mobile.
Williams said it would be the “clear choice” for SpaceX if it decided to go through with a network acquisition. He also suggested AT&T.
The move would be possible through selling more of its own stock, which would help SpaceX raise the money to purchase T-Mobile, which would cost roughly $300 billion. It could be one of the moves SpaceX makes post-IPO in terms of an acquisition: it already acquired Cursor AI for $60 billion.
Other analysts, like Dan Ives of Wedbush, believe SpaceX and Tesla will eventually merge into one anyway, and that conglomeration could come as soon as this year, some have said.
The implications of SpaceX purchasing T-Mobile are massive. A combined entity would create a truly ubiquitous network: T-Mobile’s terrestrial 5G towers and Starlink’s growing constellation of Direct-to-Cell satellites. This would essentially eliminate dead zones across the U.S. and potentially globally.
SpaceX would instantly become a full-scale facilities-based carrier with satellite differentiation; a huge advantage. This would pressure AT&T and Verizon heavily.
There are also concerns like a potential reduction in long-term competition, and of course, a deal of that size would face intense scrutiny from government agencies.
The strategic fit is compelling due to the existing Starlink–T-Mobile partnership and complementary technologies (space + terrestrial). It could create a dominant integrated communications player. However, the regulatory, financial, and execution hurdles are enormous — this remains highly speculative with no indication SpaceX is actively pursuing it right now.
Tesla expands massive safety feature worldwide in latest update
Tesla sends production Cybercab with no steering wheel, pedals to on-road testing
