In 2020, at a resort in San Antonio, a Model S owner had their car damaged by a valet who wanted to test out Cheetah mode. The joyride did not end well for this valet who crashed the car into a concrete wall, which was captured on the car’s dash cam.
Many luxury carmakers have invented ways to prevent a valet from damaging the car or accessing personal data. Some carmakers introduced valet keys that could limit top speed, reduce acceleration and lock the glove box. Although these features improved the safety and privacy of the car, the physical keys were impractical because they could be stolen or lost. Valet keys have been outdated since Chevrolet introduced virtual Valet Mode in 2014.
Tesla also implemented a Valet Mode of its own that improves upon the safety and privacy features of the valet key. Tesla's Valet Mode is a feature that prevents valets from driving recklessly and having access to the owner's personal information. Tesla introduced the feature in 2015 as part of an over-the-air software update.
Tesla's Valet Mode
MonsterGadgets/YouTube
Everything Valet Mode Does
When Valet Mode is activated, Tesla’s operating system restricts some of the car's functionality. Valet Mode will limit the car's maximum speed to 70 mph, reduce acceleration by about 50 percent and disable the use of autopilot.
In addition to these safety features, the security and privacy features include the automatic locking of the glove box and frunk. Valet Mode also keeps the user's information private by blocking certain personal information from appearing on the display screen. This keeps information such as addresses, contacts and schedules completely private. Valet Mode also disables Wi-Fi, Bluetooth and navigation functionality.
Valet Mode Restrictions
Valet Mode restrictions the following features:
Speed limited to 70 mph
Acceleration restricted to “Chill”
The front trunk and glove box will lock, the trunk will remain accessible
Voice commands are disabled
Navigation is disabled so that it does not allow access to recent destinations, favorites or home and work addresses
Autopilot/FSD is disabled
Allow Mobile Access setting cannot be changed
HomeLink (if applicable) is not available
Driver profiles are not available
The touchscreen will not display the list of keys that can access the car
Wi-Fi and Bluetooth are disabled, and you cannot view or add a new device
Sentry Mode options can’t be changed (if Sentry Mode is on, it can’t be turned off)
Smart summon is disabled
Calendar is not available
The Upgrades section in Controls > Upgrades is disabled
There are a few other features that are inaccessible while Valet Mode is enabled. The most obvious of which is Ludicrous Mode, which allows the driver to access the full acceleration power of the Tesla.
This mode is only available for some performance models. Smart Summon is also inaccessible while in Valet Mode. However, if your Tesla is parked in Valet Mode, you can disable Valet Mode from the mobile app, and proceed to Smart Summon your car.
Charging
Although Tesla limits many features while the vehicle is in Valet Mode to protect your privacy and your vehicle, it does not limit the ability to charge.
This can be useful when you visit a valet location with chargers on site. The valet can plug your Tesla in to charge while it is parked.
Speed Limit
Although the speed limit for Valet Mode defaults to 70 mph, you can customize it to your preference using "Speed Limit Mode". The speed limit can be set in safety settings by turning on the Speed Limit Mode and creating a 4-digit PIN.
By turning on Speed Limit Mode, you can set a custom maximum speed that cannot be changed without your PIN. You can set the maximum speed in the car or in the Security section of the Tesla app.
How to Turn On Valet Mode
Valet Mode can be activated from within the vehicle and through the mobile app. To activate it from within the car, tap your profile name on the display screen. A drop-down menu will appear, select the last tab labeled “Valet Mode.” you will be prompted to enter a four-digit PIN the first time you enable Valet Mode. Once the PIN is entered, the screen will display that Valet Mode has been enabled. You can also use the mobile app to turn Valet Mode on and off, assuming the vehicle is parked, by clicking ”Security” and then “Valet Mode”.
PIN to Drive
If you use PIN to Drive, an additional security feature that requires you to enter a valid PIN code to start the car, this feature is disabled while the car is in Valet Mode. Once you start Valet Mode, you’ll be prompted to enter your PIN to Drive code. This code will be saved and will not require the valet driver to enter a PIN to start the car.
Teen Drivers
Valet Mode can also come in handy when letting a teen drive to prevent them from speeding or using functionality that could be dangerous for a new driver, such as using the car’s full acceleration or using Autopilot. None of the Tesla’s safety features are disabled while in Valet Mode.
If you prefer, you can just enable Speed Limit Mode so that they can still access navigation, music, and other features.
Teslas are fun cars to drive and some people may be tempted to test the car’s instant torque, fast acceleration and amazing Autopilot capabilities, but these features should be used with permission.
Since Teslas are capable of high speed and fast acceleration, Valet Mode is an advisable feature to use. The higher performance of a car, the greater the risk of an accident when left in the hands of a valet driver.
Tesla owners can have peace of mind knowing that Valet Mode can prevent speeding and reckless driving and protect their privacy when someone else is behind the wheel.
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Tesla launched two FSD updates simultaneously on Saturday night, and what’s most interesting is that they arrived on the same software version. We’ll dig into that a little later, but for now, there’s good news for everyone. For Hardware 3 owners, FSD V12.6.1 is launching to all vehicles, including the Model 3 and Model Y. For AI4 owners, FSD V13.2.4 is launching, starting with the Cybertruck.
FSD V13.2.4
A new V13 build is now rolling out to the Cybertruck and is expected to arrive for the rest of the AI4 fleet soon. However, this build seems to be focused on bug fixes. There are no changes to the release notes for the Cybertruck with this release, and it’s unlikely to feature any changes when it arrives on other vehicles.
FSD V12.6.1 builds upon V12.6, which is the latest FSD version for HW3 vehicles. While FSD V12.6 was only released for the redesigned Model S and Model X with HW3, FSD V12.6.1 is adding support for the Model 3 and Model Y.
While this is only a bug-fix release for users coming from FSD V12.6, it includes massive improvements for anyone coming from an older FSD version. Two of the biggest changes are the new end-to-end highway stack that now utilizes FSD V12 for highway driving and a redesigned controller that allows FSD to drive “V13” smooth.
It also adds speed profiles, earlier lane changes, and more. You can read our in-depth look at all the changes in FSD V12.6.
Same Update, Multiple FSD Builds
What’s interesting about this software version is that it “includes" two FSD updates, V12.6.1 for HW3 and V13.2.4 for HW4 vehicles. While this is interesting, it’s less special when you understand what’s happening under the hood.
The vehicle’s firmware and Autopilot firmware are actually completely separate. While a vehicle downloading a firmware update may look like a singular process, it’s actually performing several functions during this period. First, it downloads the vehicle’s firmware. Upon unpacking the update, it’s instructed which Autopilot/FSD firmware should be downloaded.
While the FSD firmware is separate, the vehicle can’t download any FSD update. The FSD version is hard-coded in the vehicle’s firmware that was just downloaded. This helps Tesla keep the infotainment and Autopilot firmware tightly coupled, leading to fewer issues.
What we’re seeing here is that HW3 vehicles are being told to download one FSD version, while HW4 vehicles are being told to download a different version.
While this is the first time Tesla has had two FSD versions tied to the same vehicle software version, the process hasn’t actually changed, and what we’re seeing won’t lead to faster FSD updates or the ability to download FSD separately. What we’re seeing is the direct result of the divergence of HW3 and HW4.
While HW3/4 remained basically on the same FSD version until recently, it is now necessary to deploy different versions for the two platforms. We expect this to be the norm going forward, where HW3 will be on a much different version of FSD than HW4. While each update may not include two different FSD versions going forward, we may see it occasionally, depending on which features Autopilot is dependent on.
Thanks to Greentheonly for helping us understand what happened with this release and for the insight into Tesla’s processes.
At the 2025 Consumer Electronics Show, Nvidia showed off its new consumer graphics cards, home-scale compute machines, and commercial AI offerings. One of these offerings included the new Nvidia Cosmos training system.
Nvidia is a close partner of Tesla - in fact, they produce and supply the GPUs that Tesla uses to train FSD - the H100s and soon-to-be H200s, located at the new Cortex Supercomputing Cluster at Giga Texas. Nvidia will also challenge Tesla’s lead in developing and deploying synthetic training data for an autonomous driving system - something Tesla is already doing.
However, this is far more important for other manufacturers. We’re going to take a look at what Nvidia is offering and how it compares to what Tesla is already doing. We’ve done a few deep dives into how Tesla’s FSD works, how Tesla streamlines FSD, and, more recently, how they optimize FSD. If you want to get familiar with a bit of the lingo and the background knowledge, we recommend reading those articles before continuing, but we’ll do our best to explain how all this synthetic data works.
Nvidia Cosmos
Nvidia’s Cosmos is a generative AI model created to accelerate the development of physical AI systems, including robots and autonomous vehicles. Remember - Tesla’s FSD is also the same software that powers their humanoid robot, Optimus. Nvidia is aiming to tackle physical, real-world deployments of AI anywhere from your home, your street, or your workplace, just like Tesla.
Cosmos is a physics-aware engine that learns from real-world video and builds simulated video inputs. It tokenizes data to help AI systems learn quicker, all based on the video that is input into the system. Sound familiar? That’s exactly how FSD learns as well.
Cosmos also has the capability to do sensor-fused simulations. That means it can take multiple input sources - video, LiDAR, audio, or whatever else the user intends, and fuse them together into a single-world simulation for your AI model to learn from. This helps train, test, and validate autonomous vehicle behavior in a safe, synthetic format while also providing a massive breadth of data.
Data Scaling
Of course, Cosmos itself still requires video input - the more video you feed it, the more simulations it can generate and run. Data scaling is a necessity for AI applications, as you’ll need to feed it an infinite amount of data to build an infinite amount of scenarios for it to train itself on.
Synthetic data also has a problem - is it real? Can it predict real-world situations? In early 2024, Elon Musk commented on this problem, noting that data scales infinitely both in the real world and in simulated data. A better way to gather testing data is through real-world data. After all, no AI can predict the real world just yet - in fact, that’s an excellent quantum computing problem that the brightest minds are working on.
Yun-Ta Tsai, an engineer at Tesla’s AI team, also mentioned that writing code or generating scenarios doesn’t cover what even the wildest AI hallucinations might come up with. There are lots of optical phenomena and real-world situations that don’t necessarily make sense in the rigid training sets that AI would develop, so real-world data is absolutely essential to build a system that can actually train a useful real-world AI.
Tesla has billions of miles of real-world video that can be used for training, according to Tesla’s Social Media Team Lead Viv. This much data is essential because even today, FSD encounters “edge cases” that can confuse it, slow it down, or render it incapable of continuing, throwing up the dreaded red hands telling the user to take over.
Cosmos was trained on approximately 20 million hours of footage, including human activities like walking and manipulating objects. On the other hand, Tesla’s fleet gathers approximately 2,380 recorded minutes of real-world video per minute. Every 140 hours - just shy of 6 days - Tesla’s fleet gathers 20 million hours of footage. That was a little bit of back-of-the-napkin math, calculated at 60 mph as the average speed.
Generative Worlds
Both Tesla’s FSD and Nvidia’s Cosmos can generate highly realistic, physics-based worlds. These worlds are life-like environments and simulate the movement of people and traffic and the real-life position of obstacles and objects, including curbs, fences, buildings, and other objects.
Tesla uses a combination of real-world data and synthetic data, but the combination of data is heavily weighted to real-world data. Meanwhile, companies who use Cosmos will be weighting their data heavily towards synthetically created situations, drastically limiting what kind of cases they may see in their training datasets.
As such, while generative worlds may be useful to validate an AI quickly, we would argue that these worlds aren’t as useful as real-world data to do the training of an AI.
Overall, Cosmos is an exciting step - others are clearly following in Tesla’s footsteps, but they’re extremely far behind in real-world data. Tesla has built a massive first-mover advantage in AI and autonomy, and others are now playing catch-up.
We’re excited to see how Tesla’s future deployment of its Dojo Supercomputer for Data Labelling adds to its pre-existing lead, and how Cortex will be able to expand, as well as what competitors are going to be bringing to the table. After all, competition breeds innovation - and that’s how Tesla innovated in the EV space to begin with.
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