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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.
Don’t hesitate to contact us with news tips. Just send a message to simon@teslarati.com to give us a heads up.
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Tesla hits FSD hackers with surprise move
In recent weeks, the company has begun remotely disabling FSD capabilities on affected vehicles, and in some instances, permanently revoking access even for owners who paid thousands of dollars for the feature.
Tesla is cracking down on hackers who have figured out a way to utilize third-party programs to activate Full Self-Driving (FSD) in their vehicles — despite the suite not being approved for use in their country.
Tesla has launched a sweeping enforcement campaign against owners using third-party hardware hacks to activate FSD software in countries where the advanced driver-assistance system remains unregulated or unapproved.
In recent weeks, the company has begun remotely disabling FSD capabilities on affected vehicles, and in some instances, permanently revoking access even for owners who paid thousands of dollars for the feature.
Tesla has started remotely disabling Full Self-Driving on cars fitted with third-party CAN bus hacks in countries where the software is not yet approved.
This crackdown began after the hacks started spreading widely last month. 👇 pic.twitter.com/wL8VqZuTlK
— PiunikaWeb – helpful, and breaking tech news (@PiunikaWeb) April 9, 2026
Reports of the crackdown have surfaced across Europe, China, Japan, South Korea, and the UK, marking a significant escalation in Tesla’s efforts to enforce regional software restrictions.
FSD is Tesla’s flagship supervised autonomy package, which is available in several countries across the world. Currently limited by regulatory hurdles, it has not received full approval in most markets outside of the United States due to various things, such as safety standards, data privacy, and local traffic laws.
However, the company is working to expand its availability globally. Nevertheless, Tesla has installed the necessary hardware on vehicles globally, but locks the features based on geographic location.
Some owners have taken accessing FSD into their own hands, using jailbreak or bypass devices.
These “jailbreak” tools, typically €500 USB-style modules that plug into the vehicle’s Controller Area Network (CAN) bus, intercept signals to spoof approvals and unlock FSD, including advanced navigation, Autopark, and Summon features.
Hackers in Poland, Ukraine, and elsewhere have distributed the devices, with some claiming they work on HW3 and HW4 vehicles and can be unplugged to restore stock settings. In China alone, over 100,000 owners reportedly installed such modifications.
Tesla’s response has been swift and uncompromising. Recently, the company began sending in-car notifications and emails warning owners that unauthorized modifications violate terms of service, compromise vehicle safety systems, and expose cars to cybersecurity risks.
The email communication read:
“Your vehicle has detected an unauthorized third-party device. As a precaution, some driver assistance functions have been disabled for safety reasons. A software update will be available soon. Once you install the update, some features may be enabled again.”
Vehicles detected using the hacks have had FSD capabilities remotely disabled without refund. In some cases, owners report permanent bans, even if they had legitimately purchased the software package.
Tesla’s hardline stance underscores its commitment to regulatory compliance and safety.
Tesla has long argued that unsupervised FSD requires rigorous validation, and premature activation could endanger drivers and bystanders.
The crackdown sends a clear-cut message to those who are bypassing the FSD safeguards, but there are greater implications for Tesla if something were to go wrong. This is an understandable way to protect the company’s reputation for its FSD suite.
News
Tesla developing small, affordable SUV, report claims
This latest rumor deserves heavy scrutiny. Tesla has already walked away from a mass-market $25,000 EV once before.
Tesla is developing a small, affordable SUV, a new report claims, speculating that the automaker is planning to add yet another vehicle to its lineup at a price point similar to the Model 3 and Model Y, but smaller and more compact.
But it does not make a whole lot of sense, especially considering a handful of things CEO Elon Musk said and the overall plan for Tesla’s future.
Reuters reported that Tesla is in the early stages of developing an all-new, smaller, cheaper electric SUV. Citing four sources familiar with the matter, the story claims the vehicle would be shorter than the Model Y, built in China, and represent a fresh platform rather than a variant of the Model 3 or Y.
Suppliers have reportedly been contacted to discuss details, though Tesla has not commented. The move appears aimed at broadening affordability amid slowing EV demand and intensifying competition, particularly from Chinese rivals.
This latest rumor deserves heavy scrutiny. Tesla has already walked away from a mass-market $25,000 EV once before.
In 2024, the company scrapped its long-teased “Redwood” project for a budget-friendly car. Elon Musk explained the decision bluntly during an earnings call: a conventional low-cost model would be “pointless” and “completely at odds with what we believe.”
It’s sort of hard to believe this report: 3/Y are already relatively affordable, Elon said a $25k wouldn’t make sense, consumers want something larger than the Y with X going away, and Musk said what’s coming is “cooler than a minivan.”
Have to think the car is at least an SUV. https://t.co/4CQUV9ZNA5
— TESLARATI (@Teslarati) April 9, 2026
In other words, chasing a bare-bones cheap EV runs counter to Tesla’s core mission of accelerating sustainable energy through cutting-edge technology and autonomy rather than volume-driven price wars.
Musk’s own recent statements reinforce skepticism about a compact SUV pivot. Just two weeks ago, on March 25, he responded to fan requests for a minivan by posting on X: “Something way cooler than a minivan is coming.”
Elon Musk says Tesla is developing a new vehicle: ‘Way cooler than a minivan’
The remark came in the context of family-hauling needs, with Musk highlighting the Cybertruck’s ability to seat multiple child seats. It signals Tesla’s focus is shifting toward more spacious, innovative people-movers—not shrinking its lineup.
U.S. demand data echoes this logic.
The long-wheelbase Model Y L—a six-seat, stretched variant offering extra room for families—has generated massive interest wherever offered. Fans in the U.S. have basically begged for the Model Y L to make its way to the States, or for the company to develop a full-size SUV.
The Model Y L is selling well in China, where it is manufactured.
Delivery wait times for the Model Y L stretched into February 2026 as orders poured in. Tesla recently expanded the trim to eight new Asian markets, yet it remains unavailable in the United States, where consumer appetite for a larger, more practical SUV is reportedly strong.
American buyers have consistently favored bigger vehicles; the Model Y already outsells most competitors precisely because it delivers crossover utility without compromise. A compact model shorter than today’s bestseller would likely miss this mark entirely.
Tesla’s product strategy has long emphasized differentiation through autonomy, range, and desirability rather than racing to the bottom on price. Stripped-down variants of the Model 3 and Y have already struggled to ignite broad demand.
A new compact SUV built in China might sound logical on paper for cost-sensitive buyers, but it risks repeating past missteps—diluting brand cachet while ignoring clear signals from Musk and the market.
History suggests Tesla talks about affordable cars more often than it delivers them. Whether this Reuters scoop evolves into metal or joins the $25k project on the scrap heap remains to be seen.
For now, the smart money is on Tesla doubling down on “way cooler” vehicles that actually fit American families—and Tesla’s ambitious vision—rather than a smaller SUV that feels like yesterday’s news.
News
Tesla CEO Elon Musk says next FSD release is the one we’ve been waiting for
On Thursday, Musk teased the capabilities and next steps for Tesla’s Full Self-Driving software, focusing squarely on the incremental improvements of the current v14.3 suite, as well as the looming arrival of v15.
Tesla CEO Elon Musk teased the capabilities of a future Full Self-Driving release, but it seems like we are getting what Yogi Berra once called “DĂ©jĂ vu all over again.”
On Thursday, Musk teased the capabilities and next steps for Tesla’s Full Self-Driving software, focusing squarely on the incremental improvements of the current v14.3 suite, as well as the looming arrival of v15.
He confirmed that upcoming point releases of v14.3 will deliver additional polish to the current build, smoothing out remaining edges in an already capable system. These iterative updates, Musk noted, are designed to refine performance without requiring a full version overhaul.
Yet the real headline was Musk’s forecast for v15.
“V15 will far exceed human levels of safety, even in completely unsupervised and complex situations,” he wrote.
Tesla V14.3 self-driving review. The point releases will bring polish.
V15 will far exceed human levels of safety, even in completely unsupervised and complex situations. https://t.co/s4UK9RWw9f— Elon Musk (@elonmusk) April 9, 2026
He clarified that v15 will be powered by Tesla’s long-awaited large model, an AI architecture with roughly 10x the parameters of the smaller model currently in widespread use. The leap, Musk explained, stems from the unusually rapid progress of the compact model, which has advanced so quickly that the larger counterpart has yet to catch up in real-world deployment.
However, it is becoming a pattern that is, by now, familiar to anyone following Tesla’s autonomous driving roadmap.
There’s no debating you on that 🤷
— TESLARATI (@Teslarati) April 9, 2026
Musk has consistently and repeatedly framed each successive major release as the one poised to deliver game-changing autonomy. Earlier versions were similarly positioned as a movement toward the final piece of the puzzle, only for attention to pivot to the next milestone once they arrived.
The refrain has become a recurring feature of FSD communication: current software is impressive, the point releases will sharpen it further, but the true breakthrough lies one major iteration ahead.
Musk’s latest comments fit squarely into that cadence. While v14.3 point releases are expected to tighten supervised driving behaviors in the coming weeks, v15 is cast as the version that finally crosses the threshold into unsupervised operation at human-or-better safety levels across demanding scenarios.
Our rate of advancement with the small model has been so fast that the large model has not yet caught up.
V15 will be the large model.— Elon Musk (@elonmusk) April 9, 2026
The 10x parameter scale of the underlying large model is presented as the key technical enabler, promising richer reasoning and more robust decision-making than anything deployed to date.
Whether v15 ultimately fulfills that promise remains to be seen. Tesla’s history shows that each new target generates fresh excitement—and occasional skepticism—about timelines.
Fans realize Musk’s timelines for FSD are exciting, but rarely met:
You can see a rift happening in the Tesla bull community between a large group of reasonable people who aren’t afraid to acknowledge the elephants in the room, and those who are essentially bull bots whose entire identities are destroyed if they have to acknowledge any bump in…
— Mike P (@mikepat711) April 9, 2026
For now, Musk’s message is familiar: the immediate focus is polishing v14.3 through targeted point releases, while the 10x-parameter large model in v15 represents the next decisive step toward fully unsupervised, superhuman safety.
Hopefully, Tesla can come through, but we can only believe that once v15 gets here, v16 will be the next big step toward autonomy.
Drivers can expect continued refinement in the short term and a significantly more ambitious leap once the large model is ready. The cycle continues, but the stakes, Musk insists, keep rising.
Tesla hits FSD hackers with surprise move
Tesla developing small, affordable SUV, report claims
