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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Elon Musk makes a key Tesla Optimus detail official
“Since we are naming the singular, we will also name the plural, so Optimi it is,” Musk wrote on X.
Tesla CEO Elon Musk just made a key detail about Optimus official. In a post on X, the CEO clarified some key wording about Optimus, which should help the media and the public become more familiar with the humanoid robot.
Elon Musk makes Optimus’ plural term official
Elon Musk posted a number of Optimus-related posts on X this weekend. On Saturday, he stated that Optimus would be the Von Neumann probe, a machine that could eventually be capable of replicating itself. This capability, it seems, would be the key to Tesla achieving Elon Musk’s ambitious Optimus production targets.
Amidst the conversations about Optimus on X, a user of the social media platform asked the CEO what the plural term for the humanoid robot will be. As per Musk, Tesla will be setting the plural term for Optimus since the company also decided on the robot’s singular term. “Since we are naming the singular, we will also name the plural, so Optimi it is,” Musk wrote in his reply on X.
This makes it official. For media outlets such as Teslarati, numerous Optimus bots are now called Optimi. It rolls off the tongue pretty well, too.
Optimi will be a common sight worldwide
While Musk’s comment may seem pretty mundane to some, it is actually very important. Optimus is intended to be Tesla’s highest volume product, with the CEO estimating that the humanoid robot could eventually see annual production rates in the hundreds of millions, perhaps even more. Since Optimi will be a very common sight worldwide, it is good that people can now get used to terms describing the humanoid robot.
During the Tesla 2025 Annual Shareholder Meeting, Musk stated that the humanoid robot will see “the fastest production ramp of any product of any large complex manufactured product ever,” starting with a one-million-Optimi-per-year production line at the Fremont Factory. Giga Texas would get an even bigger Optimus production line, which should be capable of producing tens of millions of Optimi per year.
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Tesla is improving Giga Berlin’s free “Giga Train” service for employees
With this initiative, Tesla aims to boost the number of Gigafactory Berlin employees commuting by rail while keeping the shuttle free for all riders.
Tesla will expand its factory shuttle service in Germany beginning January 4, adding direct rail trips from Berlin Ostbahnhof to Giga Berlin-Brandenburg in Grünheide.
With this initiative, Tesla aims to boost the number of Gigafactory Berlin employees commuting by rail while keeping the shuttle free for all riders.
New shuttle route
As noted in a report from rbb24, the updated service, which will start January 4, will run between the Berlin Ostbahnhof East Station and the Erkner Station at the Gigafactory Berlin complex. Tesla stated that the timetable mirrors shift changes for the facility’s employees, and similar to before, the service will be completely free. The train will offer six direct trips per day as well.
“The service includes six daily trips, which also cover our shift times. The trains will run between Berlin Ostbahnhof (with a stop at Ostkreuz) and Erkner station to the Gigafactory,” Tesla Germany stated.
Even with construction continuing at Fangschleuse and Köpenick stations, the company said the route has been optimized to maintain a predictable 35-minute travel time. The update follows earlier phases of Tesla’s “Giga Train” program, which initially connected Erkner to the factory grounds before expanding to Berlin-Lichtenberg.
Tesla pushes for majority rail commuting
Tesla began production at Grünheide in March 2022, and the factory’s workforce has since grown to around 11,500 employees, with an estimated 60% commuting from Berlin. The facility produces the Model Y, Tesla’s best-selling vehicle, for both Germany and other territories.
The company has repeatedly emphasized its goal of having more than half its staff use public transportation rather than cars, positioning the shuttle as a key part of that initiative. In keeping with the factory’s sustainability focus, Tesla continues to allow even non-employees to ride the shuttle free of charge, making it a broader mobility option for the area.
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Tesla Model 3 and Model Y dominate China’s real-world efficiency tests
The Tesla Model 3 posted 20.8 kWh/100 km while the Model Y followed closely at 21.8 kWh/100 km.
Tesla’s Model 3 and Model Y once again led the field in a new real-world energy-consumption test conducted by China’s Autohome, outperforming numerous rival electric vehicles in controlled conditions.
The results, which placed both Teslas in the top two spots, prompted Xiaomi CEO Lei Jun to acknowledge Tesla’s efficiency advantage while noting that his company’s vehicles will continue refining its own models to close the gap.
Tesla secures top efficiency results
Autohome’s evaluation placed all vehicles under identical conditions, such as a full 375-kg load, cabin temperature fixed at 24°C on automatic climate control, and a steady cruising speed of 120 km/h. In this environment, the Tesla Model 3 posted 20.8 kWh/100 km while the Model Y followed closely at 21.8 kWh/100 km, as noted in a Sina News report.
These figures positioned Tesla’s vehicles firmly at the top of the ranking and highlighted their continued leadership in long-range efficiency. The test also highlighted how drivetrain optimization, software management, and aerodynamic profiles remain key differentiators in high-speed, cold-weather scenarios where many electric cars struggle to maintain low consumption.

Xiaomi’s Lei Jun pledges to continue learning from Tesla
Following the results, Xiaomi CEO Lei Jun noted that the Xiaomi SU7 actually performed well overall but naturally consumed more energy due to its larger C-segment footprint and higher specification. He reiterated that factors such as size and weight contributed to the difference in real-world consumption compared to Tesla. Still, the executive noted that Xiaomi will continue to learn from the veteran EV maker.
“The Xiaomi SU7’s energy consumption performance is also very good; you can take a closer look. The fact that its test results are weaker than Tesla’s is partly due to objective reasons: the Xiaomi SU7 is a C-segment car, larger and with higher specifications, making it heavier and naturally increasing energy consumption. Of course, we will continue to learn from Tesla and further optimize its energy consumption performance!” Lei Jun wrote in a post on Weibo.
Lei Jun has repeatedly described Tesla as the global benchmark for EV efficiency, previously stating that Xiaomi may require three to five years to match its leadership. He has also been very supportive of FSD, even testing the system in the United States.
