Tesla's Colorizer feature lets you customize the color of your Tesla
Not a Tesla App
Changing your Tesla’s color – whether through PPF/Vinyl or Paint, is a definite possibility. But how do you show those colors throughout the car’s software? Easy! Tesla’s Colorizer feature offers the ability to adjust the vehicle’s color in software.
You can even change what kind of wheels appear in the visualizations – a quick and easy way to match whatever you have on the car – as long as it’s a first-party wheel.
Where to Find the Colorizer
There are two ways to access Tesla’s Colorizer feature. You can go to the ToyBox app and choose Colorizer, or you can go to Controls > Software and tap on the colored square underneath your vehicle. Keep in mind this feature can only be accessed while the vehicle is parked.
Once enabled, you’ll be presented with the vehicle color wheel and menu – which offers a set of options to cater to your preferences. We’ll tackle some of those options a bit further down.
Where the Colorizer Feature Applies
Tesla's Colorizer feature even applies in the Beach Buggy Racing game
Not a Tesla App
So where do these colorizer changes apply? All throughout the vehicle, and in unexpected places too! It will display the chosen color directly in the visualization, both when parked and moving. These changes will also appear throughout settings and different parts of the car, including the mobile app, and even the Beach Buggy Racing game.
Keep in mind that the Colorizer is only available on Intel or AMD-based vehicles (MCU2+) vehicles – which means legacy vehicles won’t be able to benefit from these software color changes.
Colorizer Settings
The colorizer primarily offers a color wheel for easy selection of whatever hue you’d like to go with – whether for the day, or for longer. It also offers two other options – paint style, and trim style.
The three paint styles – Solid, Matte, and Metallic – are similar to regular car paints. The solid paint style is a flat color that matches most of Tesla’s paint offerings. The matte paint style is a bit smoother, and metallic is much more reflective. In our testing, matte often looks the best on screen.
Tesla also gives you two trim color options. Most legacy vehicles nowadays have chrome trims – and if you’d like to match that or you prefer chrome – you can also choose a chrome trim. Most modern vehicles have black – and it is selected by default.
Saving and Removing Presets
The Colorizer also offers you the ability to save presets – and to switch back to your car’s default paint – whatever it shipped with from the factory. The factory preset is located on the bottom right and quickly swaps the color back to the factory option if you can’t find one you’d like.
You can create new presets after deciding on a new color and pressing the plus box on the bottom left corner of the menu. This will add a new preset to the right of the plus icon. If you want to delete a preset, tap and hold on one, and an X will pop up – allowing you to delete that preset.
Changing Wheels in Software
You can also change your Tesla’s wheels from the car. Everywhere the Colorizer applies – these same changes apply.
You can access this by going to Settings (the grey vehicle icon), and then going down to the Service Menu. From there, select the Wheel and Tire sub-option on the right. You’ll be presented with a list of options.
However, keep in mind that selecting wheel options that do not match your current wheel size will impact your vehicle. Tesla provides a warning in this menu to not mismatch the wheel sizes – as it will impact range estimates and the vehicle’s speed display.
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.
Last night, Tesla released software update 2024.45.25.15, which includes FSD V12.6.1. This update adds support for all HW3 vehicles, including the Model 3 and Model Y. We’re excited to see the continued support for HW3 owners.
FSD V12.6.1
V12.6.1 is now going wide, according to Ashok Elluswamy, Tesla’s VP of AI. This update is going to the Model 3 and Model Y for the first time - as only the Model S and Model X were included in FSD V12.6.
V12.6 is a big step forward for HW3 - it includes End-to-End on Highway, Improved City Streets Behavior, and Smoother and More Accurate Tracking - all contributing towards a better, smoother, and more comfortable build of FSD. You can read our comparison between FSD V12.6 and V13.2.2 here.
In short, FSD V12.6 performs considerably closer to V13 than V12.5.4.2 - which is a massive improvement. It performs as well as the Cybertruck version of FSD V13, which is still missing a few features when compared to other HW4 vehicles, but it’s a great sign for HW3. A lot of the improvements can be pointed to in the improvements to lane selection and decision-making - the vehicle tends to hesitate far less on V12.6, meaning the ride is a lot smoother. Many early V12.6 testers mentioned that it felt more like V13-mini than anything else.
Legacy Model S & X
We haven’t seen this update hit any legacy Model S and Model X vehicles just yet. We’re not sure whether Ashok’s statement of “generally” applies here - but it should. If you do get the update, please let us know.
Legacy Model S and Model X vehicles are still on an older FSD build and potentially won’t see another FSD update for a little while longer. While they do have the same FSD hardware as other vehicles, there are enough hardware differences that require a build specifically for these vehicles.
FSD V12.6.1 is going out now to the redesigned Model S and X with HW3 and all Model 3 and Model Y vehicles with HW3. The initial wave went out last night, and we expect to see more later today or tomorrow. If this release ends up going “wide,” we should see much larger waves go out next week.
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