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Tesla FSD Beta 10.69.2.2 extending to 160k owners in US and Canada: Elon Musk
It appears that after several iterations and adjustments, FSD Beta 10.69 is ready to roll out to the greater FSD Beta program. Elon Musk mentioned the update on Twitter, with the CEO stating that v10.69.2.2. should extend to 160,000 owners in the United States and Canada.
Similar to his other announcements about the FSD Beta program, Musk’s comments were posted on Twitter. “FSD Beta 10.69.2.1 looks good, extending to 160k owners in US & Canada,” Musk wrote before correcting himself and clarifying that he was talking about FSD Beta 10.69.2.2, not v10.69.2.1.
While Elon Musk has a known tendency to be extremely optimistic about FSD Beta-related statements, his comments about v10.69.2.2 do reflect observations from some of the program’s longtime members. Veteran FSD Beta tester @WholeMarsBlog, who does not shy away from criticizing the system if it does not work well, noted that his takeovers with v10.69.2.2 have been marginal. Fellow FSD Beta tester @GailAlfarATX reported similar observations.
Tesla definitely seems to be pushing to release FSD to its fleet. Recent comments from Tesla’s Senior Director of Investor Relations Martin Viecha during an invite-only Goldman Sachs tech conference have hinted that the electric vehicle maker is on track to release “supervised” FSD around the end of the year. That’s around the same time as Elon Musk’s estimate for FSD’s wide release.
It should be noted, of course, that even if Tesla manages to release “supervised” FSD to consumers by the end of the year, the version of the advanced driver-assist system would still require drivers to pay attention to the road and follow proper driving practices. With a feature-complete “supervised” FSD, however, Teslas would be able to navigate on their own regardless of whether they are in the highway or in inner-city streets. And that, ultimately, is a feature that will be extremely hard to beat.Â
Following are the release notes of FSD Beta v10.69.2.2, as retrieved by NotaTeslaApp:
– 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 connectivities. 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.
– 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 maneuvers.
– 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 optimisable 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.
– 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.
– 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.
– 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.
– 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.
– Made speed profile more comfortable when creeping for visibility, to allow for smoother stops when protecting for potentially occluded objects.
– Improved recall of animals by 34% by doubling the size of the auto-labeled training set.
– 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.
– 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.
– Improved speed when entering highway by better handling of upcoming map speed changes, which increases the confidence of merging onto the highway.
– Reduced latency when starting from a stop by accounting for lead vehicle jerk.
– Enabled faster identification of red light runners by evaluating their current kinematic state against their expected braking profile.
Press the “Video Record” button on the top bar UI to share your feedback. When pressed, your vehicle’s external cameras will share a short VIN-associated Autopilot Snapshot with the Tesla engineering team to help make improvements to FSD. You will not be able to view the clip.
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Tesla Supercharging is getting yet another layer of gamification, as the company is rolling out a new competition that could win Free Supercharging miles.
Tesla is ramping up its efforts to make vehicle ownership more engaging through gamification. In June 2026, the company announced the 2026 Free Supercharging Competition, building on the Charging Passport feature introduced the previous year. This initiative turns Supercharging into a competitive, collectible adventure while offering substantial real-world incentives.
🚨 Tesla is taking its gamification of Supercharging a step further with the launch of the 2026 Free Supercharging Contest:
“In January 2027, Tesla will celebrate nine outstanding Supercharger users from 2026 by awarding them free Supercharging for their Tesla vehicle for as… pic.twitter.com/CPPYJLJwFD
— TESLARATI (@Teslarati) June 23, 2026
The Charging Passport, rolled out late last year, functions like a digital travel log or a year-in-review for Tesla owners. These types of things are used by many platforms, including Spotify and Apple Music, which show listeners what type of taste they had for the year.
Accessed in the Tesla App under the ‘Charging’ section, it displays a map of visited Superchargers, key stats, such as total energy charged (kWh), number of unique sites, total charging sessions, top charging day, and miles added. Owners earn collectible Charging Badges in categories, which include:
- Charging Milestones – for total energy, consecutive weeks of Supercharging, or unique sites visited
- Iconic Chargers – for Flagship Locations or stations near famous landmarks
- Special Events – limited-time badges for specific experiences. These badges appear within 24 hours of qualifying activity and provide a fun, shareable recap of an owner’s Supercharging journeys. Milestone progress resets annually, allowing fresh challenges each year
The 2026 contest elevates this gamification by rewarding top performers with lifetime free Supercharging. All Supercharging sessions from January 1 to December 31, 2026, count toward the competition. To participate, owners must enable “Share Charging Data with Tesla App” in vehicle settings and open the 2026 Charging Passport in the app at least once before January 1, 2027.
Nine winners will be selected — three per region (Americas, Asia-Pacific, and EMEA, with some countries excluded for regulatory reasons) — one in each of three categories:
- Longest Trip: Longest continuous streak of unique Supercharger locations where each new site is visited within 24 hours of the previous session’s start time
- Most Unique Supercharger Sites Visited: Highest number of distinct locations
- Most Energy Supercharged: Highest total in kWh charged at Superchargers
A unique site is defined as shown in the Tesla app or vehicle navigation. Repeat visits during a streak are allowed but do not extend the count. Ties are broken by total energy charged. Ineligible participants include vehicles already receiving free Supercharging, commercial-use vehicles (taxi, rideshare, delivery), Tesla employees and their immediate families, and residents of certain excluded countries.
Winners receive free Supercharging on the winning vehicle for as long as they own or lease it.
This contest is part of Tesla’s broader gamification strategy. The Safety Score has long rewarded safe driving habits with a numerical rating that can influence insurance rates or feature access. The referral program incentivizes owners with credits or free Supercharging months for successful referrals.
In-app statistics, streaks, and community features further encourage engagement. Older third-party apps even awarded “mayor” titles for frequenting specific Superchargers.
By combining digital badges, competitive leaderboards, and high-value rewards, Tesla boosts network utilization, gathers usage data, and fosters deeper owner loyalty. The 2026 Free Supercharging Competition invites enthusiasts to plan epic road trips while turning everyday charging into a rewarding pursuit. With the Passport already proving popular, expect heightened activity across the Supercharger network throughout the year.
Tesla is atop the American-Made Index from Cars.com for the sixth-straight year, as the Model 3 and Model Y took the top two spots, respectively.
Last year, the Model 3, Model Y, Model S, and Model X took the top four spots, respectively. The company has routinely performed well in the Index. However, Tesla discontinued its flagship Model S and Model X earlier this year, which took the two cars out of the ranking.
Cybertruck is not considered due to its curb weight being above the 8,500-pound threshold, which eliminates it from being required to have more detailed assembly information.
Cars.com uses five main categories to develop its rankings:
- Location(s) of final assembly
- Percentage of U.S. and Canadian parts
- Countries of origin for all available engines
- Countries of origin for all available transmissions
- U.S. manufacturing workforce
These five major factors are then put into a 100-point scale. The vehicles with the highest scores sit atop the list. The Model 3 edged out the Model Y.
🇺🇸 The Tesla Model 3 and Tesla Model Y have been put atop the American-Made Index from https://t.co/PXZ0g1pPb6, meaning they are the most American vehicles you can possibly buy.
This is the SIXTH-STRAIGHT year a Tesla has been listed as the most American-made vehicle: pic.twitter.com/HyraOmaxSL
— TESLARATI (@Teslarati) June 23, 2026
Tesla uses a strong domestic strategy to build its cars and parts domestically. It relies on intense vertical integration that reduces its dependence on global suppliers, keeping more value and jobs in the United States.
This strategy has helped Tesla gain a strong reputation for domestically produced vehicles and parts. However, it helps it with more than just awards like this one. Keeping a supply chain local has also helped insulate Tesla more than others from tariffs and supply chain disruptions.
This year’s American-Made Index from Cars.com studied nearly 400 vehicles from the 2026 model year. Tesla was the only manufacturer to have an EV inside the Top 10. The Kia EV9 was the next EV to make the list, scoring the 17th position.
The Hyundai IONIQ 5 was 21st, and the final EV to make the list was the Cadillac LYRIQ in 77th.
Tesla has finally clarified the situation regarding the viral crash in Texas where a Model 3 slammed into a home.
CEO Elon Musk replied to reports on Monday that stated the crash was due to the company’s Full Self-Driving or Autopilot suite, which seemed unlikely to those who are familiar with it. Video showed the car slamming into a house at an excessive rate of speed, making it highly unlikely the crash was due to the suite’s operation, as it does not travel at those speeds in residential areas.
Musk said:
“This makes no sense. FSD drives slowly through neighborhood streets, and this was a high-speed crash!”
Tesla’s Head of AI, Ashok Elluswamy, added context, revealing that the company’s data shows the driver “manually overrode self-driving by pressing the accelerator all the way to 100%.”
He revealed the speed reached by the car was 73 MPH, and the accelerator was still pressed “even after the crash.”
Yup. In this case, the driver manually overrode self-driving by pressing the accelerator all the way to 100% of the accel pedal in this residential area. They reached a speed of 73 mph during the crash, and had the accelerator pressed even after the crash.
— Ashok Elluswamy (@aelluswamy) June 22, 2026
Authorities are reportedly investigating “whether Tesla’s Autopilot system played a role after a Model 3 left the roadway…slammed through a brick house at high speed and fatally struck Matha Avila as she sat inside,” the New York Post reported.
The National Highway Traffic Safety Administration (NHTSA) is now investigating the crash. Tesla will work with the agency to provide them with whatever information they need in order to clarify the cause of the crash.
Similarly, Tesla had claims of a fatal accident in Harris County, Texas, a few years ago. Early reports indicated that Full Self-Driving was the cause of the crash. After the National Transportation Safety Board (NTSB) worked with Tesla, the agency proved there was “no use of the Autopilot system at any time during this ownership period of the vehicle, including the time frame up to the last transmitted timestamp on April 17, 2021.”
Tesla alleged “driverless” crash in Texas: What is known so far
“Application of the accelerator pedal was found to be as high as 98.8 percent,” the NTSB said in their findings. The highest recorded speed in the five seconds leading up to the impact was 67 miles per hour. The area where the crash occurred is residential, and Texas State laws have default speed limits of 30 MPH in residential streets.
This appears to be a similar situation. However, an investigation will prove what happened for sure.
Tesla gets another layer of gamification with Free Supercharging on the line
Tesla tops American-Made Index for sixth-consecutive year
