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 tipped its hand at where Robotaxi is heading next
In the world of autonomous ride-hailing, there are only a handful of names. Among those few companies lies a strategy play by each to keep the opposition on their toes. Tesla, on the other hand, already tipped its hand at where it is headed next.
Tesla has signaled its next major push in the autonomous ride-hailing market by filing for an Autonomous Vehicle Network Company permit in Nevada (Docket 26-05015). Through Tesla Robotaxi, LLC, the company seeks approval to operate up to 5,000 robotaxis in Clark County, including high-traffic areas like Las Vegas and Henderson airports, within the first 12 months of launch.
This filing builds on Tesla’s earlier testing approvals from the Nevada DMV in September 2025 and preparations such as maintenance hubs in the Las Vegas area. Nevada represents a strategic expansion into a major tourist destination, where high visitor volumes could drive strong utilization and showcase the reliability of unsupervised autonomy to a broad audience.
We’d have to assume this means Tesla is targeting Las Vegas, and it’s a great move from a business perspective.
Vegas is such a melting pot of people from all around the country and the world. It will expose people from all corners of the globe to Tesla’s autonomy capabilities https://t.co/Qz3fQmhULF pic.twitter.com/Du5pj2RyWC
— TESLARATI (@Teslarati) June 6, 2026
Approval would mark a significant step toward commercial operations in a new state, following progress in Texas.
Tesla’s shareholder decks and earnings calls have clearly outlined these ambitions. In the Q4 2025 shareholder deck, the company listed planned Robotaxi coverage for the first half of 2026, explicitly naming Las Vegas alongside Phoenix, Miami, Orlando, and Tampa, with Dallas and Houston already advancing. Austin was noted as “ramping unsupervised,” while the Bay Area remained in safety-driver mode.
By Q1 2026, the deck updated statuses to reflect launches in Dallas and Houston, with “preparations underway” for the remaining cities, including Las Vegas. Paid Robotaxi miles nearly doubled sequentially in Q1, underscoring momentum even as broader timelines adjusted slightly for regulatory and operational readiness.
On earnings calls, CEO Elon Musk and executives have emphasized a phased rollout prioritizing safety. Unsupervised operations in Texas have shown strong results with no reported accidents or injuries in the program. Tesla continues groundwork in additional major U.S. metros through testing and permitting, positioning it to scale quickly once approvals clear.
This Nevada move aligns with Tesla’s vision of transforming from an EV maker into an AI and robotics leader. The forthcoming Cybercab, which started production at Giga Texas in April, is expected to eventually dominate the fleet, replacing many Model Y vehicles and driving down costs to enable affordable rides.
For investors and the industry, this signals Tesla’s intent to dominate key Sun Belt and tourist markets where weather, regulations, and demand favor rapid scaling. Success in Las Vegas could validate the model for denser urban and high-tourism environments, accelerating the shift toward a future where robotaxis generate meaningful revenue.
Las Vegas will also expand knowledge among the general public at Tesla’s capabilities, helping people experience driverless ride-hailing from several companies during their time on The Strip.
News
Tesla Model 3’s cheapest trim just got a major accolade
The Tesla Model 3’s cheapest trim level just got a major accolade, as Edmunds just revealed the Rear-Wheel-Drive trim of the all-electric sedan is the most efficient EV that is currently in production.
The 2026 Tesla Model 3 Rear-Wheel-Drive not only beat its EPA-estimated range by 30 miles, but it also bested its efficiency mark by 13.2 percent. The Model 3 tested by Edmunds traveled 393 miles, beating its EPA rating by 8.3 percent, while it returned 21.7 kWh per 100 miles, or 4.61 mi/kWh.
Beating those two metrics is especially pertinent when it comes to EV ownership and driving down the cost of ownership from ICE counterparts across the board. The real money savings come from driving down the cost of driving per mile, especially when it comes to high-mileage driving.
Edmunds stated in its report and review that the process it uses to test EV efficiency is aimed at giving “the most accurate representation of a car’s real-world range.” The assessment uses a strict route that features 60 percent city and 40 percent highway driving, and an average speed of 40 MPH across the trip.
It also drives each car within 5 MPH of all posted speed limits, and the climate control is set on Auto at 72 degrees to ensure even testing. In other words, Edmunds does not use methods to maximize efficiency, and instead tries to make it reasonable to achieve the same ratings yourself.
In comparison to other EVs, it beat the 2026 Mercedes-Benz CLA 350, which went 385 miles, as well as the 2026 Audi A6 Sportback E-tron Prestige AWD, which traveled 392 miles. Only the Mercedes-Benz CLA 250+ traveled farther, making it an impressive 434 miles on a charge.
However, the Tesla Model 3 RWD’s efficiency is “unmatched” because of its incredibly low energy usage per mile.
🚨 Tesla Model 3 RWD:
-At $36,990, it is $9,000 cheaper than the average transaction price for a new car ($46,023 via KBB)
-Was 13.2% more efficient than its EPA estimate
-Traveled 393 miles on a charge despite its 363-mile EPA range https://t.co/Grov2hXqpa pic.twitter.com/Zl8rnZZLIB
— TESLARATI (@Teslarati) June 8, 2026
The Model 3 Rear-Wheel-Drive might be the best bang-for-your-buck EV if you’re looking to buy new and want access to features like Full Self-Driving, while also being aware of efficiency. This trim of the Model 3 is also priced over $9,000 cheaper than what Kelley Blue Book says the average transactional price for a new car was in May 2026, which sits at $46,023.
If you’re looking for something with more speed, an All-Wheel-Drive drivetrain, or more premium features, the Premium trims of the Model 3 currently come with one year of Free Supercharging.
Investor's Corner
SpaceX IPO set to provide massive $11.6B windfall for teacher pension plan
The Ontario Teachers’ Pension Plan (OTPP) stands to reap one of the most extraordinary returns in pension fund history thanks to a bold 2019 investment in SpaceX.
According to a recent report from The Globe and Mail, the Toronto-based fund invested roughly $300 million CAD (~$220 million USD at the time) in Elon Musk’s space company as its inaugural deal through the Teachers’ Innovation Platform.
At SpaceX’s anticipated $1.75 trillion IPO valuation, set for a mid-June debut on Nasdaq under ticker $SPCX, that stake could now be worth up to $11.6 billion USD. This would represent a roughly 50x return and easily become OTPP’s most successful single investment ever.
The fund manages $279 billion in assets for approximately 346,000 working and retired teachers in Ontario, potentially delivering an average boost of around $33,500 per member if fully realized.
SpaceX has filed its S-1 and plans to price shares at $135 each, aiming to raise a record $75 billion in what would be the largest IPO in history, surpassing Saudi Aramco. The company reported $18.67 billion in revenue for 2025, driven primarily by Starlink satellite internet growth and NASA contracts, though it continues to post significant losses tied to ambitious R&D in Starship and AI initiatives.
Important pieces moving forward include:
- Starlink Expansion: The satellite broadband service is scaling rapidly, targeting global connectivity, especially in underserved rural and remote areas. This segment offers massive recurring revenue potential as numbers climb.
- Starship and Reusability Leadership: SpaceX’s fully reusable Starship aims to slash launch costs dramatically, enabling frequent missions, Mars ambitions, and lucrative government/defense contracts. Success here could unlock exponential growth.
- AI and Diversification: Recent moves, including ties to xAI, position SpaceX in high-growth AI infrastructure, broadening beyond traditional aerospace.
- Validation Scrutiny: While the $1.75 trillion target excites investors, analysts like Morningstar value the company closer to $780 billion, citing high multiples (around 90x trailing revenue) and execution risks. A 180-day lockup period will prevent early investors like OTPP from selling immediately post-IPO.
The irony has not been lost on observers. Ontario’s government previously canceled a Starlink rural internet contract amid political tensions involving Musk, yet the pension fund’s savvy investment, made when SpaceX was valued around $33-36 billion, and Starlink was nascent, delivers outsized gains independent of politics.
For OTPP, this windfall strengthens its already solid 111 percent funding ratio and underscores the value of patient, innovation-focused capital allocation.
For SpaceX, the IPO marks a new chapter: greater transparency, access to public markets for talent retention and growth capital, and heightened pressure to deliver on its multi-planetary vision.
All eyes are fixed on whether SpaceX can justify its lofty valuation through sustained execution. For Ontario teachers, the returns are already stellar, but SpaceX, like other Musk companies in the past, has plenty of things to prove. Perhaps the most ideal person for the job is at the helm, hoping to bring the company to a massive valuation.