Tesla offers Long Range model owners the ability to increase their vehicle's performance
The Kilowatts/Twitter
If you haven't driven a Tesla, you might not be familiar with the rollercoaster-like feeling of going from 0 to 60 mph. The Long Range Model 3, for example, can accomplish this in 4.2 seconds as-is. All Teslas pull you off the line almost instantly and are already quicker than most internal combustion engine vehicles.
What if, though, you could increase the speed of your Tesla even more? We break down what Tesla's Acceleration Boost is, and whether it's worth the price tag.
What Does Tesla's Acceleration Boost Do?
If you drive a Long Range Model 3 or Model Y, you may be able to purchase the 'Acceleration Boost' upgrade that increases your vehicle's acceleration and lowers your 0-60 time.
The Tesla Model 3 Long Range already has an acceleration from 0 to 60 mph time of about 4.2 seconds. With Acceleration Boost, Tesla claims that time is reduced to 3.7 seconds.
The Tesla Model Y Acceleration Boost shaves off half a second on the vehicle’s 0 to 60 mph time, dropping its run from 4.8 seconds down to 4.3 seconds.
It’s worth highlighting that these are the only two vehicles that are eligible to purchase this upgrade. When Tesla first started delivering the new Model Ys with the 4680 cells, owners of the Standard version were able to upgrade, but the company has since removed this option.
Acceleration Boost vs Performance Times
While Acceleration Boost will give you a very noticeable boost in all performance aspects, it will not turn your vehicle into a Performance model.
Here are the 0 to 60 mph time comparisons between the Long Range model, Long Range with Acceleration Boost and Performance models.
Model
Long Range
Acceleration Boost
Performance
Model 3
4.2 seconds
3.7 seconds
3.1 seconds
Model Y
4.8 seconds
4.3 seconds
3.5 seconds
As you can see from the table above, a Long Range model with the Acceleration Boost upgrade falls roughly between a Performance model and the Long Range model in terms of acceleration.
An owner independently tests out Tesla's Acceleration Boost
MagnusMako/Tesla Motors Club
The graph above was created by an independent owner and displays the vehicle's performance from 0 to 10, 0 to 20, 0 to 30 and 0 to 60 mph after purchasing Tesla's Acceleration Boost. From the graph we can see how the vehicle's acceleration rate remains fairly constant from 0 all the way to 60 mph.
Does Acceleration Boost Add Track Mode?
Track Mode is a feature that is exclusive to Performance models. It allows you to adjust how your vehicle handles and performs. For example, it allows you to adjust features that may be useful on a track, such as adjusting the motor bias from front to rear, reducing traction control or adjusting vehicle cooling.
Although vehicles with Acceleration Boost have better performance than their Long Range counterparts, they do not include Tesla's Track Mode feature.
Is Acceleration Boost Worth It?
While the Acceleration Boost update can be a costly one at $2,000, it unquestionably gives drivers acceleration capabilities that are comparable to those of the Performance model.
According to Tesla drivers who have purchased the upgrade, the actual acceleration boost is quite notable and affects all speeds, not just 0-60 mph.
On the other hand, your Model 3 or Model Y's quick acceleration will result in quicker tire wear. Additionally, it can result in decreased efficiency, which results in higher ownership costs. However, this does depend on the individual and how often they take advantage of the speed boost.
Performance models are usually quite a bit more expensive than the Long Range models, so in terms of value, the Acceleration Boost upgrade is a good deal that will increase the vehicle's value. If you own your vehicle, you'll also likely recoup some of the upgrade's cost if/when you decide to sell the car or trade it in at some point in the future.
Cost and How to Purchase
The price for Acceleration Boost hovers around USD 2,000, depending on your region and local tax rate. Owners can conveniently purchase the upgrade directly from their Tesla app, or through Tesla's website.
To purchase or see if the upgrade is available for your vehicle, open the Tesla app and navigate to the Upgrades section.
Then tap on Software Upgrades and if the feature is available for your Tesla you will see Acceleration Boost listed.
If you'd like to purchase the upgrade, make sure your vehicle is in Park and connected to Wi-Fi or has a strong cellular connection so that the vehicle can download an updated configuration.
You can add the Acceleration Boost upgrade to your cart and follow the payment instructions.
The upgrade is a one-time payment that can be made with a credit card, debit card, or Apple Pay. However, it is not possible to add the cost of the upgrade to your lease or vehicle loan payments.
Once the payment has been processed, the update should only take a few minutes to show up in your vehicle.
How to Check if Your Vehicle Has Acceleration Boost
Once you've made the purchase, you can confirm that you have received the upgrade by tapping on Controls (car icon) and navigating to Software. Below your vehicle's image, you'll see a list of features, including possible features like Full Self-Driving, Premium Connectivity and more.
If your car has received the upgrade, you should now see Acceleration Boost listed.
In addition to the upgrade appearing under the Software tab, you can also navigate to the Pedals & Steering section and your acceleration choices will now be 'Chill' and 'Sport,' instead of the previous options of 'Chill' and 'Standard.'
Your vehicle should now be noticeably faster.
An owner independently tests out Tesla's Acceleration Boost
Smvarg/Medium
Is there an Acceleration Boost Trial?
Although not formally promoted as a trial period, Tesla does provide you the chance to get a refund for your original purchase within 48 hours of purchase, if you change your mind or the upgrade didn't meet your expectations.
It is not possible, however, to receive another refund if you re-purchase the Acceleration Boost upgrade at a later time. Any future purchases for Acceleration Boost will be final.
The Acceleration Boost upgrade might be worthwhile for you if you frequently travel on long, open highways or appreciate experiencing the acceleration surge when you depress the pedal. But if you use your Tesla for routine activities like grocery shopping or being stuck in traffic on the way to and from work, it might not be the best bang for your buck.
However, if you initially had your eye on the Performance model and ultimately decided on the Long Range version, Acceleration Boost is a great way to get closer to the performance of the higher-end trim.
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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