Tesla appears to have started slowly rolling out v11 of the Full Self-Driving Beta program this morning, just a few days after CEO Elon Musk stated the company would begin releasing it to more vehicles.
Tesla’s FSD Beta v11.3.1 started to roll out to employees late last year and a select few of the automaker’s long-standing testers a few weeks ago.
The controlled rollout allows Tesla to monitor its behaviors and tendencies in a highly safe way, as it can determine issues or bugs in a small sample size and fix them before a wider release begins.
On March 14, Musk stated that “ V11 starts going wide this weekend,” and we’ve heard it before. However, it appears the automaker is happy with the early reviews and is starting to release it to more vehicles.
V11 starts going wide this weekend
— Elon Musk (@elonmusk) March 15, 2023
v11.3.2 is the newest version of the Beta and is being rolled out with Tesla Software Update 2022.45.11. According to statistics from TeslaScope, more vehicles are being updated with the new FSD Beta v11, and more drivers on the r/TeslaMotors subreddit are beginning to report that they have received the update.
Drivers who have experienced the early editions of this rollout have reported that there have been several improvements to highway driving, and inner-city street navigation has also been refined and feels more accurate than ever before, which is undoubtedly a step in the right direction.
The full release notes for the FSD Beta are available below via TeslaScope:
- 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.
- Improved recall for close-by cut-in cases by 15%, particularly for large trucks and high-yaw rate scenarios, through an additional 30k auto-labeled clips mined from the fleet. Additionally, expanded and tuned dedicated speed control for cut-in objects.
- Improved the position of ego in wide lanes, by biasing in the direction of the upcoming turn to allow other cars to maneuver around ego.
- Improved handling during scenarios with high curvature or large trucks by offsetting in lane to maintain safe distances to other vehicles on the road and increase comfort.
- Improved behavior for path blockage lane changes in dense traffic. Ego will now maintain more headway in blocked lanes to hedge for possible gaps in dense traffic.
- Improved lane changes in dense traffic scenarios by allowing higher acceleration during the alignment phase. This results in more natural gap selection to overtake adjacent lane vehicles very close to ego.
- Made turns smoother by improving the detection consistency between lanes, lines and road edge predictions. This was accomplished by integrating the latest version of the lane-guidance module into the road edge and lines network.
- Improved accuracy for detecting other vehicles’ moving semantics. Improved precision by 23% for cases where other vehicles transition to driving and reduced error by 12% for cases where Autopilot incorrectly detects its lead vehicle as parked. These were achieved by increasing video context in the network, adding more data of these scenarios, and increasing the loss penalty for control- relevant vehicles.
- Extended maximum trajectory optimization horizon, resulting in smoother control for high curvature roads and far away vehicles when driving at highway speeds.
- Improved driving behavior next to row of parked cars in narrow lanes, preferring to offset and staying within lane instead of unnecessarily lane changing away or slowing down.
- Improved back-to-back lane change maneuvers through better fusion between vision-based localization and coarse map lane counts.
- Added text blurbs in the user interface to communicate upcoming maneuvers that FSD Beta plans to make. Also improved the visualization of upcoming slowdowns along the vehicle’s path. Chevrons render at varying opacity and speed to indicate the slowdown intensity, and a solid line appears at locations where the car will come to a stop.
- Improved the recall and precision of object detection, notably reducing the position error of semi-trucks by 10%, increasing the recall and precision of crossing vehicles over 100m away by 3% and 7%, respectively, and increasing the recall of motorbikes by 5%. This was accomplished by implementing additional quality checks in our two million video clip autolabeled dataset.
- Reduced false offsetting around objects in wide lanes and near intersections by improving object kinematics modeling in low speed scenarios.
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In a move echoing its earlier commitment to open innovation, Tesla CEO Elon Musk announced recently that the company plans to make the design and software of its Model S and Model X fully open source.
This follows the same approach Tesla took with its original Roadster, releasing all available design, engineering, and diagnostic materials in November 2023 so that “whatever we have, you now have.”
Just as Tesla made the original Roadster design & software open source, we plan to do the same with Model S & X
— Elon Musk (@elonmusk) July 24, 2026
The Model S, introduced in 2012, was Tesla’s first mass-produced vehicle and a groundbreaking luxury electric sedan. It offered impressive range, rapid acceleration, and over-the-air software updates that redefined expectations for electric cars.
The Model X, launched in 2015, built on that foundation as a high-performance electric SUV notable for its distinctive falcon-wing doors, spacious interior, and advanced safety features. Both models served as flagships that helped establish Tesla as a leader in the EV industry and popularized long-range battery-electric vehicles.
Production of the Model S and Model X was wound down earlier in 2026, with manufacturing ending in the second quarter. Tesla redirected the Fremont factory space previously used for these vehicles toward higher-priority projects, including Optimus humanoid robots and the Cybercab autonomous vehicle.
By the time of Musk’s open-source announcement, custom orders had closed and only remaining inventory was available.
Open-sourcing the designs and software offers several clear advantages. Owners of these aging but still capable vehicles gain better access to technical documentation, diagnostic tools, and software resources, making independent repairs and modifications easier and more affordable.
Independent repair shops and third-party specialists can support the large existing fleet without relying solely on Tesla’s service network. Enthusiasts and engineers can study real-world implementations of Tesla’s battery, powertrain, and software systems, potentially accelerating broader industry progress in electric mobility.
The step aligns with Tesla’s 2014 patent pledge and its overall mission to advance sustainable transport by sharing hard-won knowledge rather than locking it behind proprietary walls.
By releasing these materials now that the models have left production, Tesla ensures continued support for its early adopters while freeing internal resources for future technologies. The open-source release of the original Roadster already enabled simulations, community projects, and deeper technical understanding.
Extending that practice to the Model S and Model X should deliver similar benefits on a larger scale, helping keep these influential vehicles relevant and repairable for years to come
Tesla flexed one incredible Robotaxi metric during the Q2 Earnings Call that skeptics have to hate to hear. The company’s platform has already driven more than 380,000 miles of unsupervised ride-hailing across several states with no notable incidents.
During the company’s Q2 Earnings Call on Wednesday, Vice President of AI, Ashok Elluswamy, said:
“First of all, I’d like to state that the Robotaxi program has been operating extremely well. Especially in terms of safety, the program has had an impeccable safety record. We have driven more than 380,000 miles of unsupervised Robotaxi, now across six cities in two different states. We have had zero notable incidents. Any reports have been of other actors impacting us when we were stationary. I like to emphasize how safe the operation has been so far. Zero notable incidents over 380,000 miles.”
Elluswamy’s claim over Robotaxi miles is a significant milestone for Tesla in the grand scheme, especially considering this is a sizeable number of miles without any incident.
0 notable incidents across over 380,000 miles traveled by Robotaxi
— Tesla (@Tesla) July 22, 2026
Tesla’s self-driving approach is much different than that of other companies. Tesla has maintained that vision is the only thing needed to have a solid and effective self-driving suite. Many self-driving companies utilize things like LiDAR, sensors, and other elements to improve performance, but Elluswamy sent a jab at those who believe it’s needed.
“Historically, the so-called experts have always claimed that you need LiDARs, radars, HD maps, and the entire kitchen sink to drive safely. Here we show that such is not true. You can have safe, comfortable, and affordable autonomy with just cameras. This record should be a huge validation of Tesla’s entire AI approach.”
The feat of accumulating this many miles without any driver behind the wheel is impressive. The thing is, Tesla is also doing this across several different locations, with varying traffic rules, pedestrian levels, weather patterns, and other important factors.
While Tesla is not ready to roll out an unsupervised platform completely, it is a slow but steady indication that the company is well on its way to figuring things out.
The company’s attitude toward expansion is slow, safe, and controlled, and despite this huge milestone, it will still be some time until we see Tesla truly unleash unsupervised rides more aggressively.
Elon Musk
SpaceX Starship just nailed something it’s never done before
SpaceX’s Starship flew successfully Friday, landing both stages and deploying its first Starlink V3 satellites.
Starship’s thirteenth test flight delivered exactly what SpaceX needed with a clean liftoff, two successful stage recoveries, and the first real payload the vehicle has ever carried to space. Booster 20 and Ship 40 lifted off at 5:51 p.m. CT from Starbase, and by the time the mission wrapped roughly an hour later, both halves of the rocket had done exactly what they were supposed to do.
Booster 20 separated from Ship 40 a few minutes into the flight and stuck a controlled splashdown in the Gulf of Mexico about six minutes after liftoff. That is a meaningful turnaround from Flight 12 in May, when the booster lost several engines during its boostback burn before a hard water landing attempt.
Starship as seen from Starlink satellites pic.twitter.com/e2hvfmnewh
— Elon Musk (@elonmusk) July 25, 2026
Starship 40’s performance was arguably the bigger win. The vehicle deployed the first 20 operational Starlink V3 satellites Starship has ever carried, then flew a suborbital arc to a landing in the Indian Ocean that SpaceX commentator Dan Huot called the company’s softest splashdown yet. “This is a dream scenario for this team that’s trying to get this heat shield data,” Huot said on the live broadcast, according to Space.com’s live coverage. “I’m a little over the moon right now. Wow. Lucky number 13.”
Unlike the mass simulators SpaceX flew on Flight 12, these were production Starlink V3 satellites, meant to extend solar arrays and antennas and attempt to link with the broader constellation before reentering minutes later. Getting real hardware through a full deploy sequence on only the second flight of the V3 generation keeps Starship on schedule for the payload work NASA is counting on for future Artemis lunar landings.
What an awesome launch, really seems like everything went super well and it was all incredibly smooth.
SpaceX is awesome. Very interested to see how the market will respond on Monday pic.twitter.com/KSHmyBfV55
— TESLARATI (@Teslarati) July 25, 2026
— TESLARATI (@Teslarati) July 25, 2026
The flight also arrives at a moment when SpaceX needed a win. SPCX has traded below its $135 IPO price since mid-July, as Teslarati reported when the mission slipped to Friday, and short interest has climbed to roughly a third of the tradable float. A clean flight will not fix a balance sheet, but it does answer the one question SpaceX absolutely needed answered this week: whether the fixes made after the July 16 abort would hold up under real flight conditions. They did, on both stages, on the first try after the redesign.
SpaceX has not set a target date for Flight 14, though the company has said it wants to push toward an orbital attempt on the next mission. After Friday, that goal looks a lot more within reach.
Tesla to open source Model S and Model X designs and software
Tesla flexes incredible Robotaxi metric that skeptics will hate
