The release notes for Tesla FSD Beta V11.3 have been shared online. Observers from the electric vehicle community suggest that Tesla Full Self-Driving Beta 11.3 is rolling out to the company’s employee FSD Beta testers, at least for now.
The following are Tesla’s FSD Beta V11.3 release notes:
- Enabled FSD Beta on highway. This unifies the vision and planning stack on and off-highway and replaces the legacy highway stack, which is over four years old. The legacy highway stack still relies on several single-camera and single-frame networks, and was setup to handle simple lane-specific maneuvers. FSD Beta’s multi-camera video networks and next-gen planner, that allows for more complex agent interactions with less reliance on lanes, make way for adding more intelligent behaviors, smoother control and better decision making.
- Added voice drive-notes. After an intervention, you can now send Tesla an anonymous voice message describing your experience to help improve Autopilot.
- Expanded Automatic Emergency Braking (AEB) to handle vehicles that cross ego’s path. This includes cases where other vehicles run their red light or turn across ego’s path, stealing the right-of-way.
- Replay of previous collisions of this type suggests that 49% of the events would be mitigated by the new behavior. This improvement is now active in both manual driving and autopilot operation.
- Improved autopilot reaction time to red light runners and stop sign runners by 500ms, by increased reliance on object’s instantaneous kinematics along with trajectory estimates.
- Added a long-range highway lanes network to enable earlier response to blocked lanes and high curvature.
- Reduced goal pose prediction error for candidate trajectory neural network by 40% and reduced runtime by 3X. This was achieved by improving the dataset using heavier and more robust offline optimization, increasing the size of this improved dataset by 4X, and implementing a better architecture and feature space.
- Improved occupancy network detections by oversampling on 180K challenging videos including rain reflections, road debris, and high curvature.
- Improved recall for close-by cut-in cases by 20% by adding 40k autolabeled fleet clips of this scenario to the dataset. Also improved handling of cut-in cases by improved modeling of their motion into ego’s lane, leveraging the same for smoother lateral and longitudinal control for cut-in objects.
- Added “lane guidance module and perceptual loss to the Road Edges and Lines network, improving the absolute recall of lines by 6% and the absolute recall of road edges by 7%.
- Improved overall geometry and stability of lane predictions by updating the “lane guidance” module representation with information relevant to predicting crossing and oncoming lanes.
- Improved handling through high speed and high curvature scenarios by offsetting towards inner lane lines.
- Improved lane changes, including: earlier detection and handling for simultaneous lane changes, better gap selection when approaching deadlines, better integration between speed-based and nav-based lane change decisions and more differentiation between the FSD driving profiles with respect to speed lane changes.
- Improved longitudinal control response smoothness when following lead vehicles by better modeling the possible effect of lead vehicles’ brake lights on their future speed profiles.
- Improved detection of rare objects by 18% and reduced the depth error to large trucks by 9%, primarily from migrating to more densely supervised autolabeled datasets.
- Improved semantic detections for school busses by 12% and vehicles transitioning from stationary-to-driving by 15%. This was achieved by improving dataset label accuracy and increasing dataset size by 5%.
- Improved decision making at crosswalks by leveraging neural network based ego trajectory estimation in place of approximated kinematic models.
- Improved reliability and smoothness of merge control, by deprecating legacy merge region tasks in favor of merge topologies derived from vector lanes.
- Unlocked longer fleet telemetry clips (by up to 26%) by balancing compressed IPC buffers and optimized write scheduling across twin SOCs.
Here are the V11.3 release notes again if you haven't seen them. Very happy to see improvements in rain reflections as that was rare, but could give some insane errors #FSDBeta @elonmusk pic.twitter.com/ZIOcIhmUMd
— Dirty Tesla (@DirtyTesLa) February 20, 2023
Several longtime FSD Beta testers have pointed out some key improvements that would likely be very appreciated by users in V11.3. These include the systems’ improved handling through high speed and high curvature scenarios, as well as improvements to Automatic Emergency Braking (AEB). With the improvements in place, FSD Beta V11.3 would behave closer to a proper human driver.
Comments from longtime Tesla FSD Beta testers also suggest that V11.3 is still only being released for company employees for now. Considering Tesla’s past updates, it would not be surprising if the greater FSD Beta fleet gets the V11.3 update in the coming week or so. This is, of course, unless V11.3 ends up going the way of FSD Beta V11, which was released to employees in November but not to the greater fleet of FSD Beta testers.
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Tesla (TSLA) receives “Buy” rating and $551 PT from Canaccord Genuity
He also maintained a “Buy” rating for TSLA stock over the company’s improving long-term outlook, which is driven by autonomy and robotics.
Canaccord Genuity analyst George Gianarikas raised his Tesla (NASDAQ:TSLA) price target from $482 to $551. He also maintained a “Buy” rating for TSLA stock over the company’s improving long-term outlook, which is driven by autonomy and robotics.
The analyst’s updated note
Gianarikas lowered his 4Q25 delivery estimates but pointed to several positive factors in the Tesla story. He noted that EV adoption in emerging markets is gaining pace, and progress in FSD and the Robotaxi rollout in 2026 represent major upside drivers. Further progress in the Optimus program next year could also add more momentum for the electric vehicle maker.
“Overall, yes, 4Q25 delivery expectations are being revised lower. However, the reset in the US EV market is laying the groundwork for a more durable and attractive long-term demand environment.
“At the same time, EV penetration in emerging markets is accelerating, reinforcing Tesla’s potential multi‑year growth runway beyond the US. Global progress in FSD and the anticipated rollout of a larger robotaxi fleet in 2026 are increasingly important components of the Tesla equity story and could provide sentiment tailwinds,” the analyst wrote.
Tesla’s busy 2026
The upcoming year would be a busy one for Tesla, considering the company’s plans and targets. The autonomous two-seat Cybercab has been confirmed to start production sometime in Q2 2026, as per Elon Musk during the 2025 Annual Shareholder Meeting.
Apart from this, Tesla is also expected to unveil the next-generation Roadster on April 1, 2026. Tesla is also expected to start high-volume production of the Tesla Semi in Nevada next year.
Apart from vehicle launches, Tesla has expressed its intentions to significantly ramp the rollout of FSD to several regions worldwide, such as Europe. Plans are also underway to launch more Robotaxi networks in several more key areas across the United States.
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Waymo sues Santa Monica over order to halt overnight charging sessions
In its complaint, Waymo argued that its self-driving cars’ operations do not constitute a public nuisance, and compliance with the city’s order would cause the company irreparable harm.
Waymo has filed a lawsuit against the City of Santa Monica in Los Angeles County Superior Court, seeking to block an order that requires the company to cease overnight charging at two facilities.
In its complaint, Waymo argued that its self-driving cars’ operations do not constitute a public nuisance, and compliance with the city’s order would cause the company irreparable harm.
Nuisance claims
As noted in a report from the Los Angeles Times, Waymo’s two charging sites at Euclid Street and Broadway have operated for about a year, supporting the company’s growing fleet with round-the-clock activity. Unfortunately, this has also resulted in residents in the area reportedly being unable to sleep due to incessant beeping from self-driving taxis that are moving in and out of the charging stations around the clock.
Frustrated residents have protested against the Waymos by blocking the vehicles’ paths, placing cones, and “stacking” cars to create backups. This has also resulted in multiple calls to the police.
Last month, the city issued an order to Waymo and its charging partner, Voltera, to cease overnight operations at the charging locations, stating that the self-driving vehicles’ activities at night were a public nuisance. A December 15 meeting yielded no agreement on mitigations like software rerouting. Waymo proposed changes, but the city reportedly insisted that nothing would satisfy the irate residents.
“We are disappointed that the City has chosen an adversarial path over a collaborative one. The City’s position has been to insist that no actions taken or proposed by Waymo would satisfy the complaining neighbors and therefore must be deemed insufficient,” a Waymo spokesperson stated.
Waymo pushes back
In its legal complaint, Waymo stated that its “activities at the Broadway Facilities do not constitute a public nuisance.” The company also noted that it “faces imminent and irreparable harm to its operations, employees, and customers” from the city’s order. The suit also stated that the city was fully aware that the Voltera charging sites would be operating around the clock to support Waymo’s self-driving taxis.
The company highlighted over one million trips in Santa Monica since launch, with more than 50,000 rides starting or ending there in November alone. Waymo also criticized the city for adopting a contentious strategy against businesses.
“The City of Santa Monica’s recent actions are inconsistent with its stated goal of attracting investment. At a time when the City faces a serious fiscal crisis, officials are choosing to obstruct properly permitted investment rather than fostering a ‘ready for business’ environment,” Waymo stated.
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Tesla FSD v14.2.2 is getting rave reviews from drivers
So far, early testers have reported buttery-smooth drives with confident performance, even at night or on twisty roads.
Tesla Full Self-Driving (Supervised) v14.2.2 is receiving positive reviews from owners, with several drivers praising the build’s lack of hesitation during lane changes and its smoother decision-making, among others.
The update, which started rolling out on Monday, also adds features like dynamic arrival pin adjustment. So far, early testers have reported buttery-smooth drives with confident performance, even at night or on twisty roads.
Owners highlight major improvements
Longtime Tesla owner and FSD user @BLKMDL3 shared a detailed 10-hour impression of FSD v14.2.2, noting that the system exhibited “zero lane change hesitation” and “extremely refined” lane choices. He praised Mad Max mode’s performance, stellar parking in locations including ticket dispensers, and impressive canyon runs even in dark conditions.
Fellow FSD user Dan Burkland reported an hour of FSD v14.2.2’s nighttime driving with “zero hesitations” and “buttery smooth” confidence reminiscent of Robotaxi rides in areas such as Austin, Texas. Veteran FSD user Whole Mars Catalog also demonstrated voice navigation via Grok, while Tesla owner Devin Olsen completed a nearly two-hour drive with FSD v14.2.2 in heavy traffic and rain with strong performance.
Closer to unsupervised
FSD has been receiving rave reviews, even from Tesla’s competitors. Xpeng CEO He Xiaopeng, for one, offered fresh praise for FSD v14.2 after visiting Silicon Valley. Following extended test drives of Tesla vehicles running the latest FSD software, He stated that the system has made major strides, reinforcing his view that Tesla’s approach to autonomy is indeed the proper path towards autonomy.
According to He, Tesla’s FSD has evolved from a smooth Level 2 advanced driver assistance system into what he described as a “near-Level 4” experience in terms of capabilities. While acknowledging that areas of improvement are still present, the Xpeng CEO stated that FSD’s current iteration significantly surpasses last year’s capabilities. He also reiterated his belief that Tesla’s strategy of using the same autonomous software and hardware architecture across private vehicles and robotaxis is the right long-term approach, as it would allow users to bypass intermediate autonomy stages and move closer to Level 4 functionality.