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Tesla FSD Beta 10.69 release notes highlight better left turns, smoother driving

(Credit: Tesla)

Published

3 years ago

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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.

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Maria--aka "M"-- is an experienced writer and book editor. She's written about several topics including health, tech, and politics. As a book editor, she's worked with authors who write Sci-Fi, Romance, and Dark Fantasy. M loves hearing from TESLARATI readers. If you have any tips or article ideas, contact her at maria@teslarati.com or via X, @Writer_01001101.

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Investor's Corner

Tesla analyst realizes one big thing about the stock: deliveries are losing importance

Published

55 minutes ago

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December 15, 2025

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Credit: Joe Tegtmeyer | YouTube

Tesla analyst Dan Levy of Barclays realized one big thing about the stock moving into 2026: vehicle deliveries are losing importance.

As a new era of Tesla seems to be on the horizon, the concern about vehicle deliveries and annual growth seems to be fading, at least according to many investors.

Even CEO Elon Musk has implied at times that the automotive side, as a whole, will only make up a small percentage of Tesla’s total valuation, as Optimus and AI begin to shine with importance.

He said in April:

“The future of the company is fundamentally based on large-scale autonomous cars and large-scale and large volume, vast numbers of autonomous humanoid robots.”

Levy wrote in a note to investors that Tesla’s Q4 delivery figures “likely won’t matter for the stock.” Barclays said in the note that it expects deliveries to be “soft” for the quarter.

In years past, Tesla analysts, investors, and fans were focused on automotive growth.

Cars were truly the biggest thing the stock had to offer: Tesla was a growing automotive company with a lot of prowess in AI and software, but deliveries held the most impact, along with vehicle pricing. These types of things had huge impacts on the stock years ago.

In fact, several large swings occurred because of Tesla either beating or missing delivery estimates:

  • January 3, 2022: +13.53%, record deliveries at the time
  • January 3, 2023: -12.24%, missed deliveries
  • July 2, 2024: +10.20%, beat delivery expectations
  • October 3, 2022: -8.61%, sharp miss due to Shanghai factory shutdown
  • July 2, 2020: +7.95%, topped low COVID-era expectations with sizeable beat on deliveries

It has become more apparent over the past few quarters that delivery estimates have significantly less focus from investors, who are instead looking for progress in AI, Optimus, Cybercab, and other projects.

These things are the future of the company, and although Tesla will always sell cars, the stock is more impacted by the software the vehicle is running, and not necessarily the vehicle itself.

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News

Tesla removes Safety Monitors, begins fully autonomous Robotaxi testing

This development, in terms of the Robotaxi program, is massive. Tesla has been working incredibly hard to expand its fleet of Robotaxi vehicles to accommodate the considerable demand it has experienced for the platform.

Published

13 hours ago

on

December 14, 2025

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Credit: @Mandablorian | X

Tesla has started Robotaxi testing in Austin, Texas, without any vehicle occupants, the company’s CEO Elon Musk confirmed on Sunday. Two Tesla Model Y Robotaxi units were spotted in Austin traveling on public roads with nobody in the car.

The testing phase begins just a week after Musk confirmed that Tesla would be removing Safety Monitors from its vehicles “within the next three weeks.” Tesla has been working to initiate driverless rides by the end of the year since the Robotaxi fleet was launched back in June.

Two units were spotted, with the first being seen from the side and clearly showing no human beings inside the cabin of the Model Y Robotaxi:

Another unit, which is the same color but was confirmed as a different vehicle, was spotted just a few moments later:

The two units are traveling in the general vicinity of the South Congress and Dawson neighborhoods of downtown Austin. These are located on the southside of the city.

This development, in terms of the Robotaxi program, is massive. Tesla has been working incredibly hard to expand its fleet of Robotaxi vehicles to accommodate the considerable demand it has experienced for the platform.

However, the main focus of the Robotaxi program since its launch in the Summer was to remove Safety Monitors and initiate completely driverless rides. This effort is close to becoming a reality, and the efforts of the company are coming to fruition.

It is a drastic step in the company’s trek for self-driving technology, as it plans to expand it to passenger vehicles in the coming years. Tesla owners have plenty of experience with the Full Self-Driving suite, which is not fully autonomous, but is consistently ranked among the best-performing platforms in the world.

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Tesla refines Full Self-Driving, latest update impresses where it last came up short

We were able to go out and test it pretty extensively on Saturday, and the changes Tesla made from the previous version were incredibly impressive, especially considering it seemed to excel where it last came up short.

Published

1 day ago

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December 14, 2025

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Credit: TESLARATI

Tesla released Full Self-Driving v14.2.1.25 on Friday night to Early Access Program (EAP) members. It came as a surprise, as it was paired with the release of the Holiday Update.

We were able to go out and test it pretty extensively on Saturday, and the changes Tesla made from the previous version were incredibly impressive, especially considering it seemed to excel where it last came up short.

Tesla supplements Holiday Update by sneaking in new Full Self-Driving version

With Tesla Full Self-Driving v14.2.1, there were some serious regressions. Speed Profiles were overtinkered with, causing some modes to behave in a strange manner. Hurry Mode was the most evident, as it refused to go more than 10 MPH over the speed limit on freeways.

It would routinely hold up traffic at this speed, and flipping it into Mad Max mode was sort of over the top. Hurry is what I use most frequently, and it had become somewhat unusable with v14.2.1.

It seemed as if Speed Profiles should be more associated with both passing and lane-changing frequency. Capping speeds does not help as it can impede the flow of traffic. When FSD travels at the speed of other traffic, it is much more effective and less disruptive.

With v14.2.1.25, there were three noticeable changes that improved its performance significantly: Speed Profile refinements, lane change confidence, and Speed Limit recognition.

Speed Profile Refinement

Speed Profiles have been significantly improved. Hurry Mode is no longer capped at 10 MPH over the speed limit and now travels with the flow of traffic. This is much more comfortable during highway operation, and I was not required to intervene at any point.

With v14.2.1, I was sometimes assisting it with lane changes, and felt it was in the wrong place at the wrong time more frequently than ever before.

However, this was one of the best-performing FSD versions in recent memory, and I really did not have any complaints on the highway. Speed, maneuvering, lane switching, routing, and aggressiveness were all perfect.

Lane Changes

v14.2.1 had a tendency to be a little more timid when changing lanes, which was sort of frustrating at times. When the car decides to change lanes and turn on its signal, it needs to pull the trigger and change lanes.

It also changed lanes at extremely unnecessary times, which was a real frustration.

There were no issues today on v14.2.1.25; lane changes were super confident, executed at the correct time, and in the correct fashion. It made good decisions on when to get into the right lane when proceeding toward its exit.

It was one of the first times in a while that I did not feel as if I needed to nudge it to change lanes. I was very impressed.

Speed Limit Recognition

So, this is a complex issue. With v14.2.1, there were many times when it would see a Speed Limit sign that was not meant for the car (one catered for tractor trailers, for example) or even a route sign, and it would incorrectly adjust the speed. It did this on the highway several times, mistaking a Route 30 sign for a 30 MPH sign, then beginning to decelerate from 55 MPH to 30 MPH on the highway.

This required an intervention. I also had an issue leaving a drive-thru Christmas lights display, where the owners of the private property had a 15 MPH sign posted nearly every 200 yards for about a mile and a half.

The car identified it as a 55 MPH sign and sped up significantly. This caused an intervention, and I had to drive manually.

It seems like FSD v14.2.1.25 is now less reliant on the signage (maybe because it was incorrectly labeling it) and more reliant on map data or the behavior of nearby traffic.

A good example was on the highway today: despite the car reading that Route 30 sign and the Speed Limit sign on the center screen reading 30 MPH, the car did not decelerate. It continued at the same speed, but I’m not sure if that’s because of traffic or map data:

A Lone Complaint

Tesla has said future updates will include parking improvements, and I’m really anxious for them, because parking is not great. I’ve had some real issues with it over the past couple of months.

Today was no different:

Full Self-Driving v14.2.1.25 is really a massive improvement over past versions, and it seems apparent that Tesla took its time with fixing the bugs, especially with highway operation on v14.2.1.

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