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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.
Elon Musk
Tesla Semi finally has an FSD timeline and it’s waiting on the Cybercab
Elon Musk told investors Semi self-driving should start working by early 2027, per today’s earnings.
During Wednesday’s’ Tesla Q2 earnings call, an analyst asked Elon Musk when Tesla would look at autonomy for the Semi. His answer set a real timeline for the first time, noting that self-driving on the Tesla Semi is expected to start working “around the end of this year or early next year”.
Musk framed the delay as a matter of priority, not capability. Tesla’s self-driving team is currently focused on Model 3, Model Y, and Cybercab, the vehicles that make up the overwhelming majority of Tesla’s fleet. Since Semi trucks on the road remain a small fraction of that total even after the recent Nevada factory ramp, Musk said it made more sense to keep the software team’s attention on what he called “the march of nines of safety” for the higher volume vehicles first. Autonomous Semi development is “taking a bit of a backseat for the next six months or so,” he said, before adding that it “will definitely be working next year and in time for the scale-up to high production of the Tesla Semi.”
Tesla Semi’s official battery capacity leaked by California regulators
The timeline lines up with what’s already been showing up on public roads. In June, a Tesla Semi was spotted in Sunnyvale wearing a full validation rig, the same rooftop sensor array Tesla mounts on vehicles ahead of an FSD milestone.
A second unit was seen near Fremont days later with a matching camera suite and lens washers. Separately, Tesla analyst Nic Cruz Patane posted video this month of the production Semi’s exterior camera array, ten AI4 based units built directly into the truck rather than added later.
Tesla Semi AI4 cameras. The production version has 10 cameras on its exterior.
These trucks are designed to be autonomous. pic.twitter.com/GH3BamxIBQ
— Nic Cruz Patane (@niccruzpatane) April 14, 2026
Musk also gave the reason autonomy on the Semi matters in the first place, a persistent shortage of qualified truck drivers. “There is a really serious shortage of truckers,” he said on the call, framing a self-driving Semi as important both for addressing that shortage and for improving safety and comfort for the drivers running the truck today.
The timing also tracks with the Semi’s production reality. Tesla’s Q2 shareholder letter, dropped language promising the Semi would reach volume production this year. Musk pointed to 4680 battery cell output as the near-term constraint on Semi and Cybercab production. A software timeline landing in early 2027 gives Tesla’s autonomy team room to work while the hardware ramp catches up behind it.
It’s worth nothing that this isn’t necessarily a promise the Semi ships driverless next year. Musk’s own language, self-driving “working” by early 2027, describes internal validation catching up to hardware already riding on every production truck, not a public unsupervised rollout.
Tesla (NASDAQ: TSLA) reported its earnings for the first quarter of 2026 on Wednesday afternoon. Here’s what the company reported compared to what Wall Street analysts expected.
The earnings results come after Tesla reported a massive beat on vehicle deliveries for the second quarter, delivering 489,126 vehicles and building 451,758 cars during the three-month span.
This was a major shock for those on Wall Street as they anticipated somewhere around 400,000 deliveries for the quarter, and showed Tesla still has plenty of demand for its vehicles around the world and in the U.S. despite losing the $7,500 EV Tax Credit last year.
Tesla Q2 2026 Earnings Results
- Non-GAAP EPS – $0.33 reported vs. $0.53 expected
- Revenues – $28.236 billion reported vs. $26.4 billion expected
- Free Cash Flow- -$1.092B
- Profit -$ 4.751B
Tesla (beat/missed) analyst expectations, so the market response to the company’s quarter is what we will look for next.
Tesla shares closed today down just over 1 percent, trading at $374.01.
In the past, it has been anyone’s guess with what Tesla shares will do after they report earnings. Strong quarters have resulted in sharp drops, while lackluster quarters have seen the stock shoot up considerably.
Tesla will hold its Q2 2026 Earnings Call in about 90 minutes at 5:30 p.m. on the East Coast. Remarks will be made by CEO Elon Musk and other executives, who will shed some light on the investor questions that we covered earlier this week.
You can stream it below. Additionally, we will be doing our Live Blog on X and Facebook.
Q2 2026 Earnings Call https://t.co/zZS6ii2TWK
— Tesla (@Tesla) July 22, 2026
Tesla is about to make parking in busy parking lots at businesses and other points of interest less stressful than ever by allowing drivers more control over where they park and how, CEO Elon Musk confirmed on X.
Tesla has been working to improve the parking performance of vehicles utilizing the Full Self-Driving suite, but now it is looking to add more customization, allowing drivers to choose the specific space they park in, but also potentially the orientation the car pulls into the spot:
It’s coming soon
— Elon Musk (@elonmusk) July 21, 2026
Musk has reiterated on X twice over the past several weeks that Tesla is working to make things with the FSD suite based more on the driver’s specific preferences and behaviors that were seen in past drives.
Essentially, it sounds like if you tend to park away from a business to avoid other vehicles, Tesla FSD will soon recognize that preference of yours and start parking further away as well. Additionally, the prospect of assigned parking spaces has been something many owners have voiced concerns about.
Living in a community with assigned parking spaces makes using FSD incredibly difficult as it will rarely park in the correct spot when there are so many to choose from. This is also pertinent in work settings where there are sometimes assigned parking spaces.
The updates to Tesla’s Full Self-Driving suite in terms of listening to driver preferences with parking are also extending to routing. Tesla announced yesterday that with the release of its 2026 Summer Update, it was adding Automatic Navigation and Preferred Routes:
Tesla reveals 2026 Summer Update with crazy fixes to Nav and more
Tesla has always maintained the idea that any human input is bad input, and that, ideally, Tesla Full Self-Driving will always make the right decision. Of course, this is all in theory, but the issue is that so many of Tesla’s interventions have come because it does something that is not necessarily wrong, but perhaps not what the driver would prefer.
Taking these preferences into account will help Tesla alleviate some of the potentially unnecessary interventions that drivers perform.
Tesla Semi finally has an FSD timeline and it’s waiting on the Cybercab
Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue
