While some owners may receive an update within a few days of it being released, most owners will actually not receive the latest update for several weeks.
There are a couple of reasons why Tesla doesn't update all of its vehicles at the same time.
Unfortunately, updates for Teslas aren’t like mobile devices where an update is available for everyone right away. There’s a little more that goes into pushing updates for vehicles, especially for a vehicle that can drive itself.
How Tesla Rolls Out Updates
Tesla rolls out updates to its fleet based on the vehicle's VIN, region, model, hardware, and other factors. The main reason Tesla rolls out updates in this manner is to minimize risk and to assess how an update is performing.
Rolling out updates slowly lets Tesla quickly iterate on their update and focus on feedback and bug fixes before a potential issue has the chance to affect a large number of vehicles.
If, for example, an update caused the MCU reboot
, making the display go dark while the vehicle was in motion, Tesla could more easily isolate the issue. Tesla would then be able to roll out a fix before the issue had a chance to affect a larger portion of their fleet.
Your vehicle model or other hardware in your vehicle is taken into account as well. For example, if Tesla is looking to gather feedback on a feature that requires MCU 2 or MCU 3, they may first send the update to those vehicles before releasing it more widely.
If you look at our software updates page you'll see that there are Tesla vehicles on a wide variety of updates. Some may be on the same major update, but on a different revision, while others may be one or two major updates 'behind'.
Although a vehicle can have an update that gets 'stuck' while downloading, that's usually relatively rare. If you notice that your vehicle falls too far behind, you can send a message to Tesla Service to see whether there is an issue with your vehicle.
What do the Numbers in Tesla Updates Mean?
Tesla's release process is why you may notice several versions for the same update.
For example, Tesla may first release update 2022.36, but as new issues are found and Tesla fixes them, Tesla will roll out further updates such as 2022.36.1 and 2022.36.2.
The 2022 in the version number stands for the year in which development began for this update. The 36 stands for the week number, and the last number stands for the revision of the update.
So in general, 2022.36.1 would include the same features as update 2022.36 but would contain several fixes for issues that were found in 2022.36, while 2022.36.2 would contain fixes that were fixed after 2022.36.1 was released.
This isn't always the case since Tesla does sometimes release new features with a minor revision, or but in general it's a good rule of thumb.
Once Tesla is confident they have solved all known issues, they'll then send out the update to the entire Tesla fleet.
Can I Force My Vehicle to Receive an Update?
Unfortunately, no. Under normal circumstances, there is no way to force your Tesla to receive an update. You'll simply have to wait until the update is available for your vehicle.
However, there are a couple of things you can do to receive updates as soon as possible.
It's not clear how much this toggle does anymore, but if you're interested in receiving updates as soon as they're available it's a good idea to toggle on “Advanced Updates” under the Software tab in your vehicle.
You'll also want to make sure your car is connected to Wi-Fi as often as possible, such as at home or work. Tesla prefers to download updates over Wi-Fi so this will ensure you get an update as soon as it's available to you.
You can track which updates are going out to by checking our software updates page.
How to Check if Your Tesla is Running the Latest Update
If an update is available for your Tesla, it will usually show up in your mobile app, although it's not clear how often the mobile app checks for updates. If you suspect an update may be available for your vehicle, you can check in your vehicle, although Tesla has recently started limiting this check to once per 24-hour period.
To check if there is an update available for your Tesla, tap Controls (the car icon), and then tap on Software. On the right side, you'll be able to check your vehicle's version and whether an update is available.
Your vehicle does not need to be connected to Wi-Fi to check whether an update is available
Do I Need to be on Wi-Fi?
For the most part, Tesla requires that updates be downloaded while the vehicle is connected to Wi-Fi.
However, there are exceptions to this. If an update includes important fixes or a recall then it is usually available over cellular. The same goes if you haven’t updated your vehicle in a while, are on FSD Beta, or other unique scenarios.
If you can't connect to Wi-Fi at home or work, you can try using public Wi-Fi networks or using your mobile phone as a hotspot for your vehicle.
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.
