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Tesla FSD Beta V11.3 starts shipping to employees (Release Notes)

Credit: Drive in EV/Twitter

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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.

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. 

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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Tesla Model Y L’s new features flexed at unveiling event at Diner

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Tesla Model Y L in a field
Credit: Tesla

Tesla flexed the new features of the Model Y L with a dedicated media event at the company’s Diner on Santa Monica Boulevard in Los Angeles.

The Model Y L is the extended-wheelbase version of the all-electric crossover, which has been voted the best-selling car in the world on three occasions. The vehicle is already rolling off production lines at Gigafactory Texas, and first deliveries are slated to take place later this year.

Tesla brings Model Y L ‘Launch Series’ to the U.S. at $61,990

Teslarati was invited to the event, but due to some scheduling conflicts, we could not make it to Los Angeles. Instead, we will have our hands on a media unit sometime in August, so we’ll be able to spend some more extended time with the Model Y L.

However, plenty of those who made it to LA shared some cool features that set the Model Y L apart from the Model Y.

Multi-Row Climate Control

Tesla fitted the Model Y L with full climate control on all three rows on the front screen. It can be adjusted by selecting which row you’d like to modify on the right-hand side of the touch screen:

Better Rear Window Visibility

One of the strangest things about the Model Y, especially the Juniper iteration, is the rear window has extremely limited visibility when looking into the rearview mirror.

Tesla has improved upon this with the Model Y L:

PowerShare will be included

Model Y L will come with PowerShare in North America, with an 11.5kW output to your home. Tesla said it would require Powerwall 3 for operation.

Wireless Charging Pad

There has been some speculation that Tesla would upgrade the wireless charging pads in the United States, but this is not the case.

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Tesla owner fixes common feature complaint with crafty DIY retrofit

Tesla confirmed that it does not come with the cooled pads as the Y L in China does. This is because North America has not adopted Qi charging yet.

Thermal Management Improvements

These improvements in the Model Y L were seen with thermal management:

  • Up to 15% faster cabin cooling
  • +23% thermal efficiency gained in hot weather, 7 miles of real-world range gained
  • 8x more solar energy reflection off of glass roof
  • 30% reduction in solar energy entering the cabin

Demand

Tesla said the Model Y L is almost sold out in the U.S. It comes with

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  • 1 year of FSD Supervised
  • 1 year of Supercharging
  • 1 year of Premium Connectivity
  • Free exterior paint color, interior, and wheel option at no additional cost
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Elon Musk

Tesla CEO Elon Musk denies ridiculous Gigafactory Shanghai rumor

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(Credit: Tesla)

Tesla CEO Elon Musk took to his social media platform X on Thursday night to deny a ridiculous rumor regarding the sale of the company’s Chinese vehicle production plant, Gigafactory Shanghai.

On Thursday, the Wall Street Journal, citing sources familiar with the matter, claimed in a scathing new report that Tesla was exploring a potential sale of the entire China business in an effort to help bolster a potential merger between SpaceX and Tesla.

Musk immediately denied the rumor not once but twice, initially calling it “fake news,” and then calling it “absurdly fake news” in a separate post just a few moments later:

The original poster of the Wall Street Journal article that Musk saw deleted the initial post sharing the headline and the rumored sale of Tesla’s China business.

The report seemed absolutely and unequivocally false to begin with; Tesla’s business in China is among the most important pieces of the company’s business. Not only does the factory supply vehicles for the domestic market, but also for various other markets in Asia and Europe.

China is also one of the largest automotive markets in the world, and Tesla has performed well there despite the robust competition.

The speculation regarding a Tesla and SpaceX merger has started to gain steam this year as the space exploration company went public just a month ago. There has been speculation that Musk will bridge all of his companies under one “umbrella company,” and analysts believe this could happen before the end of the decade.

The Tesla and SpaceX merger everyone is talking about is quietly building

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This is the latest iteration of Musk’s very evident war on mainstream media. Reports regarding any of Musk’s companies are quick to get the dreaded “false” or “fake news” response from the CEO when they are unfounded.

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Elon Musk

Tesla AI boss reveals how big Optimus is going to get

Tesla’s Optimus chief corrected himself on X, confirming a staggering 10 million robot production target.

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Tesla Optimus Gen 3 [Credit: Tesla]

Tesla’s Optimus program has a new number attached to it, after Ashok Elluswamy, the executive who has run the humanoid robot program since June 2025, posted a three word correction on X Thursday, “Correction, 10 million robots.”

The line clarifies the long term annual capacity Tesla is building toward its planned second Optimus production line at Gigafactory Texas, a figure Musk has cited repeatedly since last year’s shareholder meeting.

The scale is worth noting, because ten million robots a year would mean Tesla building more units annually than most countries sell in new cars. Tesla has framed this as a second line, not the first. The buildout is happening in two phases: a roughly one million unit per year line inside Tesla’s Fremont factory, installed on the floor space vacated when Model S and Model X production ended earlier this year, and a much larger dedicated facility under construction at Giga Texas that broke ground on its first steel structure in May. That Texas facility is the one Elluswamy’s correction refers to, and is expected to reach volume production sometime in 2027.

Tesla Optimus project fires up as Musk sees production line progress

Elluswamy took over Optimus from Milan Kovac last summer and has spent the months since talking up the program’s trajectory. Elon Musk has also floated the ten million figure at Tesla’s 2025 shareholder meeting.

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Ending Model S and Model X production to make room for the first Optimus line was one of the more consequential manufacturing decisions in the company’s recent history, retiring two flagship vehicles in favor of a robot that has yet to enter mass production. Musk has previously estimated per unit production costs at $20,000 to $25,000 once Tesla reaches a million units a year, though he hasn’t said what that cost looks like at ten times the volume.

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