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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.
The Teslarati team would appreciate hearing from you. If you have any tips, contact me at maria@teslarati.com or via Twitter @Writer_01001101.
Tesla revealed plans to develop its own maps internally to fix Navigation issues and give owners more control over their routing.
On the company’s Q3 2026 Earnings Call, a question was asked about FSD Navigation issues, particularly speed limit recognition, parking, and routing. These are issues that surface from version to version and seem to be seriously challenging for Tesla’s AI team to resolve.
Tesla’s Head of AI, Ashok Elluswamy, said in response to the question:
“You’re totally right that we shouldn’t be depending on external people’s maps. So we are building our own maps, but not like the same way as OneMoreMap. We are building an entirely new architecture with essentially AI-based mapping and navigation.”
He continued:
“It’s going to be super awesome. It’s going to be integrated with voice. You can talk to it, ask for different routes. It’s going to learn your personalized preferences, plus the fleet preferences. The collective intelligence of all the cars is going to flow into making the maps and navigation super cool.”
Elluswamy said this issue should be confronted, and the mapping should be available for people by the time the v15 release starts deploying to customers.
“And over the next several months,” he added, “it’s just going to take over all of the navigation functions, parking, destination handling. And it will know you better than you know yourself in some regard for the driving task, and then handle it fully.”
Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much
Navigation is perhaps the most notable complaint with FSD, and although it has gotten better, it is still flawed. Much of the time, FSD will take people on routes that are not preferred by the driver, but Tesla tried to combat this with a routing feature in the Summer 2026 Update.
Tesla currently relies on Google for map data, but it is sort of counterintuitive to believe the company would rely on a third party for this. These improvements will be welcome, as routing and navigation have been such a pain point for so many owners for so long.
Quotes via Motley Fool
Tesla Full Self-Driving (Supervised) showed a record attach rate at delivery for new vehicles in the third quarter of 2026.
75 percent of new vehicle deliveries in North America included a subscription to FSD software, up from 55 percent in the prior quarter, a 20-percentage-point sequential gain in the company’s most mature market.
Tesla Q3 2026 Earnings results: in-line revenues, slight beat on EPS
Tesla shed light on the Q3 Shareholder Deck that 75 percent of new deliveries came with an FSD subscription:
“FSD (Supervised)⁴ attach rate continued to grow, reaching over 75% of new vehicle deliveries in North America – our most mature market – a nearly twenty percentage point sequential increase. We believe that FSD is driving demand in markets where it is available, and we continue to work with regulators to get it approved in other markets. “
The higher attach rate accompanied strong growth in the overall FSD consumer base, as active subscriptions rose to 1.75 million, a 67 percent year-over-year increase. For the first time, more than half of paid customers are on the monthly subscription, which is priced at $99 per month in the U.S.
People are buying FSD with a car attached, not the other way around
— Elon Musk (@elonmusk) October 21, 2026
The transition to subscriptions has accelerated since Tesla discontinued the one-time purchase option in most markets earlier this year. The recurring model improves revenue visibility and margins compared with large upfront payments. With three-quarters of North American deliveries now including FSD, the software is now an evidently large contributor to Tesla’s economics and ancillary revenue.
Geographic expansion remains important for further gains. FSD is now available in nine countries in the EU, and more than 100,000 customers have driven over 160 million kilometers. Tesla is pursuing broader EU-wide approval, with a related vote expected in December. Similar progress in additional markets could support higher attach rates beyond North America.
These results came as Tesla had a strong quarterly delivery performance of 486,532 vehicles in the quarter, which came with its largest passenger-vehicle backlog in four years. Battery supply continued to limit volume, but the company has pointed to FSD as a clear difference-maker that is helping sustain demand. As supervised capabilities improve, the attach rate will likely continue to improve.
At face value, it is a key measure of how Tesla is converting sales into autonomy progress.
Update: 10/22 10:51a – Para 1 consumers changed to “customers” for accuracy.
Tesla Cybercab units finally got a definitive date for when they will be able to be purchased by customers, ending speculation regarding whether the fully autonomous vehicle would be available in the near term.
During Tesla’s third-quarter 2026 earnings call on October 21, Vice President of Engineering Lars Moravy said the company is aiming to begin delivering its purpose-built Cybercab robotaxi to customers before year-end.
🚨 In short, Cybercabs are slated to go to customers by end of the year. All units are going into Robotaxi fleet currently, per @larsmoravy
Cybercab will be “transport-as-a-service,” but vast majority of Cybercab will be “Tesla-owned,” @elonmusk says https://t.co/R8Qu8QWdmp
— TESLARATI (@Teslarati) October 21, 2026
“We’re trying to get Cybercabs to customers by the end of this year, 2026,” Moravy said. He added that production is underway on the line at Gigafactory Texas, but “all of those are currently going to our own internal Robotaxi fleet.”
Moravy explained that as operations scale, Tesla will “mainly deliver fully designed autonomous vehicles to our customers,” with the Cybercab as the first such vehicle. Initial customer deliveries will start small while the company gains experience with delivery logistics, ownership models, fleet management, and operating autonomous vehicles outside its direct control.
CEO Elon Musk reinforced the limited nature of private sales, describing the Cybercab primarily as a “transport-as-a-service” offering rather than a personal ownership vehicle like the Model 3, Model Y, or upcoming Roadster. “The vast majority of the Cybercab stuff will be Tesla-owned and transport-as-a-service,” Musk said.
The Cybercab is a two-seater vehicle developed by Tesla without a steering wheel or pedals. It relies completely on Tesla’s Full Self-Driving suite and has been in production since February. Early units have been put in Tesla’s Robotaxi service as of early September, when the company launched rides to the public. Tesla previously indicated it would aim to sell Cybercabs for about $30,000.
Unsupervised Full Self-Driving is expected to ship to consumer cars during Q2 2027, Ashok Elluswamy, Tesla’s Head of AI, indicated during the call. Early buyers or fleet operators may receive vehicles whose autonomous operation remains geographically restricted due to lagging regulatory agencies. There are some hurdles that remain ahead of Cybercab deliveries.
Tesla is building its own maps to fix Navigation issues
Tesla buyers are buying for Full Self-Driving and not for the car, data shows
