News
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.
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.
Don’t hesitate to contact us with news tips. Just send a message to simon@teslarati.com to give us a heads up.
News
Tesla reliability rankings skyrocket significantly in latest assessment
“They definitely have their struggles, but by continuing to refine and not make huge changes in their models, they’re able to make more reliable vehicles, and they’ve moved up our rankings.”
Tesla ranked in the Top 10 of the most reliable car companies for 2026, as Consumer Reports’ latest index showed significant jumps from the past two years.
In 2022, Tesla ranked 27th out of 28 brands. Last year, it came in 17th.
🚨🚨 Tesla entered the Top 10 in Consumer Reports’ list of reliable carmakers for the first time
In the past two years, Tesla has ranked 17th in 2024 and 27th out of 28 brands in 2022.
Subaru, BMW, Porsche, Honda, and Toyota were the Top 5 OEMs in the rankings. pic.twitter.com/z216bccVoH
— TESLARATI (@Teslarati) December 4, 2025
However, 2026’s rankings were different. CR‘s rankings officially included Tesla in the Top 10, its best performance to date.
Finishing tenth, the full Top 10 is:
- Subaru
- BMW
- Porsche
- Honda
- Toyota
- Lexus
- Lincoln
- Hyundai
- Acura
- Tesla
Tesla has had steady improvements in its build quality, and its recent refinements of the Model 3 and Model Y have not gone unnoticed.
The publication’s Senior Director of Auto Testing, Jake Fisher, said about Tesla that the company’s ability to work through the rough patches has resulted in better performance (via CNBC):
“They definitely have their struggles, but by continuing to refine and not make huge changes in their models, they’re able to make more reliable vehicles, and they’ve moved up our rankings.”
He continued to say that Tesla’s vehicles have become more reliable over time, and its decision to avoid making any significant changes to its bread-and-butter vehicles has benefited its performance in these rankings.
Legacy automakers tend to go overboard with changes, sometimes keeping a model name but recognizing a change in its “generation.” This leads to constant growing pains, as the changes in design require intense adjustments on the production side of things.
Instead, Tesla’s changes mostly come from a software standpoint, which are delivered through Over-the-Air updates, which improve the vehicle’s functionality or add new features.
Only one Tesla vehicle scored below average in Consumer Reports’ rankings for 2026 was the Cybertruck. Fisher’s belief that Tesla improves its other models over time might prove to be true with Cybertruck in a few years.
He continued:
“They’re definitely improving by keeping with things and refining, but if you look at their 5- to 10-year-old models that are out there, when it comes to reliability, they’re dead last of all the brands. They’re able to improve the reliability if they don’t make major changes.”
Regarding Subaru’s gold medal placing on the podium, Fisher said:
“While Subaru models provide good performance and comfort, they also excel in areas that may not be immediately apparent during a test drive.”
Other notable brands to improve are Rivian, which bumped itself slightly from 31 to 26. Chevrolet finished 24th, GMC ended up 29th, and Ford saw itself in 18th.
Elon Musk
Tesla Full Self-Driving v14.2.1 texting and driving: we tested it
We decided to test it, and our main objective was to try to determine a more definitive label for when it would allow you to grab your phone and look at it without any nudge from the in-car driver monitoring system.
On Thursday, Tesla CEO Elon Musk said that Full Self-Driving v14.2.1 would enable texting and driving “depending on [the] context of surrounding traffic.”
Tesla CEO Elon Musk announces major update with texting and driving on FSD
We decided to test it, and our main objective was to try to determine a more definitive label for when it would allow you to grab your phone and look at it without any nudge from the in-car driver monitoring system.
I’d also like to add that, while Tesla had said back in early November that it hoped to allow this capability within one to two months, I still would not recommend you do it. Even if Tesla or Musk says it will allow you to do so, you should take into account the fact that many laws do not allow you to look at your phone. Be sure to refer to your local regulations surrounding texting and driving, and stay attentive to the road and its surroundings.
The Process
Based on Musk’s post on X, which said the ability to text and drive would be totally dependent on the “context of surrounding traffic,” I decided to try and find three levels of congestion: low, medium, and high.
I also tried as best as I could to always glance up at the road, a natural reaction, but I spent most of my time, during the spans of when it was in my hand, looking at my phone screen. I limited my time looking at the phone screen to a few seconds, five to seven at most. On local roads, I didn’t go over five seconds; once I got to the highway, I ensured the vehicle had no other cars directly in front of me.
Also, at any time I saw a pedestrian, I put my phone down and was fully attentive to the road. I also made sure there were no law enforcement officers around; I am still very aware of the law, which is why I would never do this myself if I were not testing it.
I also limited the testing to no more than one minute per attempt.
I am fully aware that this test might ruffle some feathers. I’m not one to text and drive, and I tried to keep this test as abbreviated as possible while still getting some insight on how often it would require me to look at the road once again.
The Results
Low Congestion Area
I picked a local road close to where I live at a time when I knew there would be very little traffic. I grabbed my phone and looked at it for no more than five seconds before I would glance up at the road to ensure everything was okay:
In full: the Low Congestion Area pic.twitter.com/6DqlBnekPn
— TESLARATI (@Teslarati) December 4, 2025
Looking up at the road was still regular in frequency; I would glance up at the road after hitting that five-second threshold. Then I would look back down.
I had no nudges during this portion of the test. Traffic was far from even a light volume, and other vehicles around were very infrequently seen.
Medium Congestion Area
This area had significantly more traffic and included a stop at a traffic light. I still kept the consecutive time of looking at my phone to about five seconds.
I would quickly glance at the road to ensure everything was okay, then look back down at my phone, spending enough time looking at a post on Instagram, X, or Facebook to determine what it was about, before then peeking at the road again.
There was once again no alert to look at the road, and I started to question whether I was even looking at my phone long enough to get an alert:
In full: the Medium Congestion Area pic.twitter.com/gnhIfBVe6Q
— TESLARATI (@Teslarati) December 4, 2025
Based on past versions of Full Self-Driving, especially dating back to v13, even looking out the window for too long would get me a nudge, and it was about the same amount of time, sometimes more, sometimes less, I would look out of a window to look at a house or a view.
High Congestion Area
I decided to use the highway as a High Congestion Area, and it finally gave me an alert to look at the road.
As strange as it is, I felt more comfortable looking down at my phone for a longer amount of time on the highway, especially considering there is a lower chance of a sudden stop or a dangerous maneuver by another car, especially as I was traveling just 5 MPH over in the left lane.
This is where I finally got an alert from the driver monitoring system, and I immediately put my phone down and returned to looking at the road:
In full: the High Congestion Area pic.twitter.com/K9rIn4ROvm
— TESLARATI (@Teslarati) December 4, 2025
Once I was able to trigger an alert, I considered the testing over with. I think in the future I’d like to try this again with someone else in the car to keep their eyes on the road, but I’m more than aware that we can’t always have company while driving.
My True Thoughts
Although this is apparently enabled based on what was said, I still do not feel totally comfortable with it. I would not ever consider shooting a text or responding to messages because Full Self-Driving is enabled, and there are two reasons for that.
The first is the fact that if an accident were to happen, it would be my fault. Although it would be my fault, people would take it as Tesla’s fault, just based on what media headlines usually are with accidents involving these cars.
Secondly, I am still well aware that it’s against the law to use your phone while driving. In Pennsylvania, we have the Paul Miller Law, which prohibits people from even holding their phones, even at stop lights.
I’d feel much more comfortable using my phone if liability were taken off of me in case of an accident. I trust FSD, but I am still erring on the side of caution, especially considering Tesla’s website still indicates vehicle operators have to remain attentive while using either FSD or Autopilot.
Check out our full test below:
Elon Musk
Tesla CEO Elon Musk announces major update with texting and driving on FSD
“Depending on context of surrounding traffic, yes,” Musk said in regards to FSD v14.2.1 allowing texting and driving.
Tesla CEO Elon Musk has announced a major update with texting and driving capabilities on Full Self-Driving v14.2.1, the company’s latest version of the FSD suite.
Tesla Full Self-Driving, even in its most mature and capable versions, is still a Level 2 autonomous driving suite, meaning it requires attention from the vehicle operator.
You cannot sleep, and you should not take attention away from driving; ultimately, you are still solely responsible for what happens with the car.
The vehicles utilize a cabin-facing camera to enable attention monitoring, and if you take your eyes off the road for too long, you will be admonished and advised to pay attention. After five strikes, FSD and Autopilot will be disabled.
However, Musk announced at the Annual Shareholder Meeting in early November that the company would look at the statistics, but it aimed to allow people to text and drive “within the next month or two.”
He said:
“I am confident that, within the next month or two, we’re gonna look at the safety statistics, but we will allow you to text and drive.”
“I am confident that, within the next month or two, we’re gonna look at the safety statistics, but we will allow you to text and drive.”
Does anyone think v14.3 will enable this? pic.twitter.com/N2yn0SK70M
— TESLARATI (@Teslarati) November 23, 2025
Today, Musk confirmed that the current version of Full Self-Driving, which is FSD v14.2.1, does allow for texting and driving “depending on context of surrounding traffic.”
Depending on context of surrounding traffic, yes
— Elon Musk (@elonmusk) December 4, 2025
There are some legitimate questions with this capability, especially as laws in all 50 U.S. states specifically prohibit texting and driving. It will be interesting to see the legality of it, because if a police officer sees you texting, they won’t know that you’re on Full Self-Driving, and you’ll likely be pulled over.
Some states prohibit drivers from even holding a phone when the car is in motion.
It is certainly a move toward unsupervised Full Self-Driving operation, but it is worth noting that Musk’s words state it will only allow the vehicle operator to do it depending on the context of surrounding traffic.
He did not outline any specific conditions that FSD would allow a driver to text and drive.
Tesla reliability rankings skyrocket significantly in latest assessment
Tesla Full Self-Driving v14.2.1 texting and driving: we tested it
