News
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.
Elon Musk
Tesla needs to come through on this one Robotaxi metric, analyst says
“We think the key focus from here will be how fast Tesla can scale driverless operations (including if Tesla’s approach to software/hardware allows it to scale significantly faster than competitors, as the company has argued), and on profitability.”
Tesla needs to come through on this one Robotaxi metric, Mark Delaney of Goldman Sachs says.
Tesla is in the process of rolling out its Robotaxi platform to areas outside of Austin and the California Bay Area. It has plans to launch in five additional cities, including Houston, Dallas, Miami, Las Vegas, and Phoenix.
However, the company’s expansion is not what the focus needs to be, according to Delaney. It’s the speed of deployment.
The analyst said:
“We think the key focus from here will be how fast Tesla can scale driverless operations (including if Tesla’s approach to software/hardware allows it to scale significantly faster than competitors, as the company has argued), and on profitability.”
Profitability will come as the Robotaxi fleet expands. Making that money will be dependent on when Tesla can initiate rides in more areas, giving more customers access to the program.
There are some additional things that the company needs to make happen ahead of the major Robotaxi expansion, one of those things is launching driverless rides in Austin, the first city in which it launched the program.
This week, Tesla started testing driverless Robotaxi rides in Austin, as two different Model Y units were spotted with no occupants, a huge step in the company’s plans for the ride-sharing platform.
Tesla Robotaxi goes driverless as Musk confirms Safety Monitor removal testing
CEO Elon Musk has been hoping to remove Safety Monitors from Robotaxis in Austin for several months, first mentioning the plan to have them out by the end of 2025 in September. He confirmed on Sunday that Tesla had officially removed vehicle occupants and started testing truly unsupervised rides.
Although Safety Monitors in Austin have been sitting in the passenger’s seat, they have still had the ability to override things in case of an emergency. After all, the ultimate goal was safety and avoiding any accidents or injuries.
Goldman Sachs reiterated its ‘Neutral’ rating and its $400 price target. Delaney said, “Tesla is making progress with its autonomous technology,” and recent developments make it evident that this is true.
Investor's Corner
Tesla gets bold Robotaxi prediction from Wall Street firm
Last week, Andrew Percoco took over Tesla analysis for Morgan Stanley from Adam Jonas, who covered the stock for years. Percoco seems to be less optimistic and bullish on Tesla shares, while still being fair and balanced in his analysis.
Tesla (NASDAQ: TSLA) received a bold Robotaxi prediction from Morgan Stanley, which anticipates a dramatic increase in the size of the company’s autonomous ride-hailing suite in the coming years.
Last week, Andrew Percoco took over Tesla analysis for Morgan Stanley from Adam Jonas, who covered the stock for years. Percoco seems to be less optimistic and bullish on Tesla shares, while still being fair and balanced in his analysis.
Percoco dug into the Robotaxi fleet and its expansion in the coming years in his latest note, released on Tuesday. The firm expects Tesla to increase the Robotaxi fleet size to 1,000 vehicles in 2026. However, that’s small-scale compared to what they expect from Tesla in a decade.
Tesla expands Robotaxi app access once again, this time on a global scale
By 2035, Morgan Stanley believes there will be one million Robotaxis on the road across multiple cities, a major jump and a considerable fleet size. We assume this means the fleet of vehicles Tesla will operate internally, and not including passenger-owned vehicles that could be added through software updates.
He also listed three specific catalysts that investors should pay attention to, as these will represent the company being on track to achieve its Robotaxi dreams:
- Opening Robotaxi to the public without a Safety Monitor. Timing is unclear, but it appears that Tesla is getting closer by the day.
- Improvement in safety metrics without the Safety Monitor. Tesla’s ability to improve its safety metrics as it scales miles driven without the Safety Monitor is imperative as it looks to scale in new states and cities in 2026.
- Cybercab start of production, targeted for April 2026. Tesla’s Cybercab is a purpose-built vehicle (no steering wheel or pedals, only two seats) that is expected to be produced through its state-of-the-art unboxed manufacturing process, offering further cost reductions and thus accelerating adoption over time.
Robotaxi stands to be one of Tesla’s most significant revenue contributors, especially as the company plans to continue expanding its ride-hailing service across the world in the coming years.
Its current deployment strategy is controlled and conservative to avoid any drastic and potentially program-ruining incidents.
So far, the program, which is active in Austin and the California Bay Area, has been widely successful.
News
Tesla Model Y L is gaining momentum in China’s premium segment
This suggests that the addition of the Model Y L to Tesla China’s lineup will not result in a case of cannibalization, but a possible case of “premiumization” instead.
Tesla’s domestic sales in China held steady in November with around 73,000 units delivered, but a closer look at the Model Y L’s numbers hints at an emerging shift towards pricier variants that could very well be boosting average selling prices and margins.
This suggests that the addition of the Model Y L to Tesla China’s lineup will not result in a case of cannibalization, but a possible case of “premiumization” instead.
Tesla China’s November domestic numbers
Data from the a Passenger Car Association (CPCA) indicated that Tesla China saw domestic deliveries of about 73,000 vehicles in November 2025. This number included 34,000 standard Model Y units, 26,000 Model 3 units, and 13,000 Model Y L units, as per industry watchers.
This means that the Model Y L accounted for roughly 27% of Tesla China’s total Model Y sales, despite the variant carrying a ~28% premium over the base RWD Model Y that is estimated to have dominated last year’s mix.
As per industry watcher @TSLAFanMtl, this suggests that Tesla China’s sales have moved towards more premium variants this year. Thus, direct year-over-year sales comparisons might miss the bigger picture. This is true even for the regular Model Y, as another premium trim, the Long Range RWD variant, was also added to the lineup this 2025.
November 2025 momentum
While Tesla China’s overall sales this year have seen challenges, the Model Y and Model 3 have remained strong sellers in the country. This is especially impressive as the Model Y and Model 3 are premium-priced vehicles, and they compete in the world’s most competitive electric vehicle market. Tesla China is also yet to roll out the latest capabilities of FSD in China, which means that its vehicles in the country could not tap into their latest capabilities yet.
Aggregated results from November suggest that the Tesla Model Y took the crown as China’s #1 best-selling SUV during the month, with roughly 34,000 deliveries. With the Model Y L, this number is even higher. The Tesla Model 3 also had a stellar month, seeing 25,700 deliveries during November 2025.
Tesla needs to come through on this one Robotaxi metric, analyst says
Tesla gets bold Robotaxi prediction from Wall Street firm
