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 Robotaxi services in Austin have been operating since last Summer, but Tesla has admittedly been delayed in its expansion of the geofence, fleet size, and other details in a bid to prioritize safety as new technology rolls out.
But those barriers are being broken with new guardrails being removed from the program.
Tesla has achieved a significant advancement in its autonomous ride-hailing program. As of May 4, the Robotaxi fleet in Austin, Texas, has begun operating unsupervised during evening hours for the first time. This expansion moves beyond previous limitations that restricted unsupervised service to daylight hours, typically ending in mid-afternoon.
Tesla Robotaxi in Austin is operating unsupervised in the evenings for the first time today.
Previously in Austin, unsupervised operation ended mid-afternoon
— Robotaxi Tracker (@RtaxiTracker) May 4, 2026
The change brings Austin in line with operations in Dallas and Houston. Those cities have supported evening unsupervised runs since their initial launches in April, and both recently received additions of new unsupervised vehicles to their fleets. This coordinated progress across Texas strengthens Tesla’s regional presence and provides a broader testing ground for the technology.
This milestone carries substantial weight in the development of autonomous vehicles. Extending operations into low-light conditions meaningfully expands the Robotaxi’s operational design domain (ODD)—the specific environments and scenarios in which the system is approved to operate safely without human intervention.
Nighttime driving presents unique technical demands: diminished visibility, headlight glare from oncoming traffic, reduced contrast for identifying pedestrians and lane markings, and greater variability in camera sensor exposure.
Tesla’s pure vision approach, powered by neural networks trained on vast real-world datasets rather than lidar or pre-mapped routes, must handle these variables reliably. Demonstrating consistent unsupervised performance after sunset validates the robustness of the end-to-end AI stack and its ability to generalize across diverse lighting conditions.
Beyond technical validation, the expansion holds important operational and economic implications. Evening hours often coincide with peak urban demand for rides, including commutes, dining, and entertainment outings.
Enabling service during these periods increases daily vehicle utilization, allowing each Robotaxi to generate more revenue while gathering additional high-value training data. Higher utilization accelerates the virtuous cycle of data collection, model improvement, and further ODD growth.
Looking ahead, this step paves the way for more ambitious rollouts. Success in low-light environments positions Tesla to pursue near-24-hour operations, potentially integrating highways and expanding into varied weather patterns. Regulators worldwide frequently demand evidence of safe performance across day-night cycles before granting wider approvals.
Proven capability in Texas could expedite deployments in planned cities such as Phoenix, Miami, Orlando, Tampa, and Las Vegas during the first half of 2026.
Tesla confirms Robotaxi expansion plans with new cities and aggressive timeline
Moreover, scaling evening service supports Tesla’s long-term vision of a high-efficiency robotaxi network. Greater fleet productivity lowers the cost per mile, making autonomous mobility more accessible and competitive against traditional ride-hailing.
As the company iterates on software updates informed by nighttime data, reliability is expected to compound rapidly, unlocking denser urban coverage and longer-distance trips.
In summary, the introduction of an unsupervised evening Robotaxi service in Austin represents more than an incremental schedule adjustment. It signals a critical maturation of the underlying technology and sets the foundation for broader geographic and temporal expansion.
With Texas operations gaining momentum, Tesla is steadily advancing toward transforming urban transportation at scale.
Cybertruck
Tesla Cybercab just rolled through Miami inside a glass box
Tesla paraded a Cybercab in a glass display at Miami’s F1 Grand Prix event this week.
Tesla set up an “Autonomy Pop-Up” at Lummus Park in Miami Beach from April 29 through May 3, 2026, embedded within the official F1 Miami Grand Prix Fan Fest. The centerpiece was a Cybertruck towing the Cybercab inside a glass display case marked “Future is Autonomous,” rolling through the beachfront crowd.
Miami is on Tesla’s confirmed list of cities for robotaxi expansion in the first half of 2026, making the promotion a strategic promotion that lays groundwork in a target market.
This was not Tesla’s first time using Miami as a showcase city. In December 2025, Tesla hosted “The Future of Autonomy Visualized” at its Miami Design District showroom, coinciding with Art Basel Miami Beach. That event featured the Cybercab prototype and Optimus robots interacting with attendees. The F1 pop-up this week marks Tesla’s return to Miami and follows a pattern Tesla has been running since early 2026. Just two weeks before Miami, Tesla stationed Optimus at the Tesla Boston Boylston Street showroom on April 19 and 20, directly on the final stretch of the Boston Marathon, letting tens of thousands of runners and spectators meet the robot for free, generating massive earned media at zero advertising cost.
Tesla is sending its humanoid Optimus robot to the Boston Marathon
Tesla has confirmed plans to expand its robotaxi service to seven cities in the first half of 2026, including Dallas, Houston, Phoenix, Miami, Orlando, Tampa, and Las Vegas, building on the unsupervised service already running in Austin. Musk has said he expects robotaxis to cover between a quarter and half of the United States by end of year. On the production side, Musk told shareholders that the Cybercab manufacturing process could eventually produce up to 5 million vehicles per year, targeting a cycle time of one unit every ten seconds. Scaling robotaxis to 10 million operational units over the next ten years is a key condition of his compensation package, alongside selling 20 million passenger vehicles.
As for the Cybercab’s price, Musk has said buyers will be able to purchase one for under $30,000, with an average operating cost around $0.20 per mile. Whether those numbers hold through full production remains to be seen.
Cybercab at F1 Fan Fest in Miami
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Tesla Semi gets new product launch as mass manufacturing hits Plaid Mode
While the 1.2 MW Megacharger handles quick 30-minute en-route boosts, the Basecharger serves as a reliable overnight solution for longer dwell times at warehouses, distribution centers, fleet yards, and even, potentially, homes.
The Tesla Semi is getting a new production launch as mass manufacturing on the all-electric truck is gearing up to hit Plaid Mode.
Tesla has introduced a game-changing addition to its commercial charging lineup with the new 125 kW Basecharger for Semi. Launched this week as part of the new “Semi Charging for Business” program, this compact unit is purpose-built for depot and overnight charging of Tesla Semi trucks.
While the 1.2 MW Megacharger handles quick 30-minute en-route boosts, the Basecharger serves as a reliable overnight solution for longer dwell times at warehouses, distribution centers, fleet yards, and even, potentially, homes.
Our new 125 kW Basecharger is designed for longer dwell times and overnight charging of Semis. It’s the “home charging” for heavy-duty fleets.
It features a fully integrated design that eliminates the need for a separate AC-to-DC cabinet, simplifying installation. The 6 meter… https://t.co/ovy1C4PsRW pic.twitter.com/vBUCNMzs57
— Tesla Charging (@TeslaCharging) May 1, 2026
Delivering up to 60 percent of the Semi’s range in roughly four hours, perfect for overnight top-ups during mandated driver rest periods or while trucks are loaded or unloaded. Its fully integrated design eliminates the need for bulky separate AC-to-DC cabinets.
Tesla engineers tucked one of the power modules from a V4 Supercharger Cabinet directly inside the sleek post, resulting in a compact footprint. It also features a six-meter cable for layout flexibility. This is one thing that must have been learned through the V4 Supercharger rollout.
Installation and operating costs drop dramatically thanks to daisy-chaining. Up to three Basechargers can share a single 125 kVA breaker, slashing electrical infrastructure requirements. The unit outputs 150 amps continuous across an 180–1,000 VDC range, matching the Semi’s high-voltage architecture while supporting the MCS 3.2 standard.
Tesla Semi sends clear message to Diesel rivals with latest move
Priced from $40,000 for a minimum order of two units, the Basecharger is far more affordable than the $188,000 Megacharger setup for two posts. Deliveries begin in early 2027. Buyers also receive Tesla’s full network-level software, remote monitoring, maintenance, and a guaranteed 97 percent or higher uptime—critical for fleet reliability.
This launch arrives as Tesla accelerates high-volume Semi production at its Nevada factory, targeting 50,000 units annually. By pairing affordable depot charging with ultra-fast highway options, Tesla removes one of the biggest obstacles to electrifying Class 8 trucking: infrastructure cost and complexity.
Fleet operators stand to gain lower electricity rates during off-peak hours, dramatically reduced maintenance compared to diesel, and quieter yards at night. The Basecharger isn’t just another charger—it’s the practical bridge that makes large-scale electric semi adoption economically viable.
With the Basecharger handling “home” duties and Megachargers powering the road, Tesla is delivering a complete ecosystem that could finally tip the scales toward zero-emission freight. For trucking companies ready to go electric, the future just got a whole lot more charger-friendly.
Tesla Robotaxi service in Austin achieves monumental new accomplishment
Tesla Cybercab just rolled through Miami inside a glass box
