We’ve now uncovered more details on how Tesla achieved such drastic improvements in the vehicle’s power consumption, which Tesla estimated to be a 40% reduction.
Tesla made architectural changes to how it processes and analyzes video — optimizing which components handle which tasks. While the Cybertruck is the first to benefit from these advancements, Tesla plans to extend these upgrades to other vehicles in the future.
Sentry Mode Power Consumption
Tesla vehicles feature two main computers: the MCU (Media Control Unit) computer, which powers the vehicle’s infotainment center, and the FSD computer, which is responsible for Autopilot and FSD. Both of these computers remain on and powered any time the vehicle is awake, consuming about 250-300 watts.
Typically, the vehicle only uses this power while it’s awake or actively driving. It’s not a major concern since the car automatically goes to sleep and shuts down its computers after about 15 minutes of inactivity. However, the larger issue is that these computers also need to remain on when Sentry Mode is active, causing a 250-watt draw whenever Sentry Mode is on.
Interconnected System
Today, the vehicle’s cameras are connected to the FSD computer, which connects to the MCU, which is finally connected to the USB ports. Because of this interconnected setup, everything needs to remain powered. Footage needs to be streamed from the FSD computer into the MCU, where processes like motion detection occur. The data then needs to be compressed before finally being written to the USB drive. That’s a lengthy process, requiring multiple computers to remain on in order to be able to record and save live video.
Architectural Changes
Tesla is making some architectural changes to address Sentry Mode’s high power consumption by shifting the responsibilities of the vehicle’s computers. By shifting motion detection and possibly the compression activity to the FSD computer, Tesla will now be able to keep the MCU computer asleep. The MCU is still required to push the video to the USB drive, but Tesla can now wake up the system only when it’s needed.
For instance, the FSD computer will still handle the connection to the vehicle’s cameras, but it will now also detect motion. When that Sentry event occurs, it can wake up the MCU to write the data to the USB drive and then have it go back to sleep.
This approach ensures the MCU isn’t continuously powered to analyze and compress video, instead activating it only when data needs to be written.
Processor Isolation & Task Allocation
Tesla’s current architecture separates the Autopilot Unit (APU) from the MCU. This is done for several reasons - but first and foremost is safety. The MCU can be independently restarted even mid-drive without impacting the APU and key safety features.
Additionally, by isolating the APU from the MCU, tasks that are optimized for each unit—processing versus image transcoding—can be offloaded to the processing unit that’s better suited for it. This helps keep both the APU and MCU operating at their optimal power and performance parameters, helping to manage energy consumption more efficiently.
Kernel-Level Power Management
Tesla’s been working on more than just FSD or new vehicle visualization changes and has been putting in the effort to optimize the operating system’s underlying kernel. While not in heavy use, Tesla is underclocking the processors of both the MCU and APU, reducing power usage and heat generation.
Of course, other kernel optimizations and programming tricks, such as the ones Tesla uses to optimize its FSD models, also factor into the increased overall efficiency of the vehicles.
Additional Benefits
Since Tesla vehicles also include a Dashcam that processes video, it’s possible we may also see these additional power savings whenever the vehicle is awake. This could also affect other features, such as Tesla’s Summon Standby feature, which keeps the vehicle awake and processing video to give users almost instant access to the vehicle’s Summon feature.
Roll Out to Other Vehicles
While the Cybertruck was the only vehicle to receive these power improvements to Sentry Mode, we were told that they’re coming to other vehicles too. Tesla is introducing these changes with the Cybertruck first, leveraging its smaller user base for initial testing before expanding the rollout to other vehicles.
USB Port Power Management
To further conserve energy and reduce waste, Tesla now powers down USB ports, even if Sentry Mode is active. This change has impacted many users who rely on 12v sockets or USB ports to remain powered to keep accessories such as small vehicle refrigerators on.
It’s not immediately clear whether these changes to Sentry Mode impact this change or whether power to 12v outlets was removed strictly due to safety concerns.
Subscribe
Subscribe to our newsletter to stay up to date on the latest Tesla news, upcoming features and software updates.
The Super Manifold is Tesla’s solution to reducing the complexity of a heat pump system for an EV. Tesla showed off its engineering chops back with the original Model Y in 2019, where it introduced a new 8-way valve (the Octovalve) and a new heat pump alongside the uniquely designed Super Manifold to improve efficiency.
Now, Tesla is launching an improved version with the refreshed Model Y - the Super Manifold V2. We got to hear about it thanks to Sandy Munro’s interview with Tesla’s Lars Moravy (Vice President of Vehicle Engineering) and Franz Von Holzhausen (Chief of Vehicle Design). You can watch the video further below.
What Is The Super Manifold?
The Super Manifold (get it, Superman?), is an all-in-one package that brings in all the components of a heat pump system into one component. The Super Manifold packs all the refrigerant and coolant components around a 2-layer PCB (printed circuit board).
This Super Manifold would normally have 15 or 20 separate components, but Tesla managed to integrate them all into one nice package. That presented Tesla with a new challenge: how to integrate a heat pump—capable of both heating and cooling—into a single, efficient platform?
Several years ago, Tesla designed the Octovalve. It combines inlets and outlets and can variably change between heating or cooling on the fly - without needing to be plumbed in different directions. This is especially important for EVs, which may need to heat the battery with the waste heat generated from the motors or the heat pump while also cooling the cabin - or vice versa.
Original Super Manifold V1.1
Tesla launched the Super Manifold V1.1 back in 2022, and it provided some minor improvements to the waste heat processing of the heat exchange system. It also tightened up the Octovalve, preventing the leakage of oils into the HVAC loop that could cause it to freeze at extremely low temperatures.
Tesla has been using the V1.1 for several years now, and it has really solved the vast majority of issues with the heat pump system that many older Model Ys experienced.
Super Manifold V2 Coming Soon
Now, Tesla is introducing the Super Manifold V2 in the new Model Y. It will improve the overall cooling capacity provided by the original Super Manifold, but unfortunately, not every single new Model Y will come with it equipped. Tesla will be introducing it slowly across the lineup and at different rates at different factories, depending on part availability.
Eventually, the Super Manifold V2 will also make its way to other vehicles, potentially including the upcoming refresh for the Model S and Model X, but initially, it’ll be exclusive to the new Model Y. Tesla expects to have the new manifold in every new Model Y later this year.
If you’re interested in checking out the whole video, we’ve got it for you below.
Mark Rober, of glitter bomb package fame, recently released a video titled Can You Fool A Self-Driving Car? (posted below). Of course, the vehicle featured in the video was none other than a Tesla - but there’s a lot wrong with this video that we’d like to discuss.
We did some digging and let the last couple of days play out before making our case. Mark Rober’s Wile E. Coyote video is fatally flawed.
The Premise
Mark Rober wanted to prove whether or not it was possible to fool a self-driving vehicle, using various test scenarios. These included a wall painted to look like a road, low-lying fog, mannequins, hurricane-force rain, and bright beams.
All of these individual “tests” had their own issues - not least because Mark didn’t adhere to any sort of testing methodology, but because he was looking for a result - and edited his tests until he was sure of it.
Interestingly, many folks on X were quick to spot that Mark had been previously sponsored by Google to use a Pixel phone - but was using an iPhone to record within the vehicle - which he had edited to look like a Pixel phone for some reason. This, alongside other poor edits and cuts, led many, including us, to believe that Mark’s testing was edited and flawed.
Flaw 1: Autopilot, Not FSD
Let’s take a look at the first flaw. Mark tested Autopilot - not FSD. Autopilot is a driving aid for lane centering and speed control - and is not the least bit autonomous. It cannot take evasive maneuvers outside the lane it is in, but it can use the full stable of Tesla’s extensive features, including Automatic Emergency Braking, Forward Collision Warnings, Blind Spot Collision Warnings, and Lane Departure Avoidance.
On the other hand, FSD is allowed and capable of departing the lane to avoid a collision. That means that even if Autopilot tried to stop and was unable to, it would still impact whatever obstacle was in front of it - unlike FSD.
As we continue with the FSD argument - remember that Autopilot is running on a 5-year-old software stack that hasn’t seen updates. Sadly, this is the reality of Tesla not updating the Autopilot stack for quite some time. It seems likely that they’ll eventually bring a trimmed-down version of FSD to replace Autopilot, but that hasn’t happened yet.
Mark later admitted that he used Autopilot rather than FSD because “You cannot engage FSD without putting in a destination,” which is also incorrect. It is possible to engage FSD without a destination, but FSD chooses its own route. Where it goes isn’t within your control until you select a destination, but it tends to navigate through roads in a generally forward direction.
The whole situation, from not having FSD on the vehicle to not knowing you can activate FSD without a destination, suggests Mark is rather unfamiliar with FSD and likely has limited exposure to the feature.
Let’s keep in mind that FSD costs $99 for a single month, so there’s no excuse for him not using it in this video.
Flaw 2: Cancelling AP and Pushing Pedals
Many people on X also followed up with reports that Mark was pushing the pedals or pulling on the steering wheel. When you tap on the brake pedal or pull or jerk the steering wheel too much, Autopilot will disengage. For some reason, during each of his “tests,” Mark closely held the steering wheel of the vehicle.
This comes off as rather odd - at the extremely short distances he was enabling AP at, there wouldn’t be enough time for a wheel nag or takeover warning required. In addition, we can visibly see him pulling the steering wheel before “impact” in multiple tests.
Over on X, techAU breaks it down excellently on a per-test basis. Mark did not engage AP in several tests, and he potentially used the accelerator pedal during the first test - which means that Automatic Emergency Braking is overridden. In another test, Mark admitted to using the pedals.
Flaw 3: Luminar Sponsored
This video was potentially sponsored by a LiDAR manufacturer - Luminar. Although Mark says that this isn’t the case. Interestingly, Luminar makes LiDAR rigs for Tesla - who uses them to test ground truth accuracy for FSD. Just as interesting, Luminar’s Earnings Call was also coming up at the time of the video’s posting.
Luminar had linked the video at the top of their homepage but has since taken it down. While Mark did not admit to being sponsored by Luminar, there appear to be more distinct conflicts of interest, as Mark’s charity foundation has received donations from Luminar’s CEO.
Given the positivity of the results for Luminar, it seems that the video had been well-designed and well-timed to take advantage of the current wave of negativity against Tesla, while also driving up Luminar’s stock.
Flaw 4: Vision-based Depth Estimation
The next flaw to address is the fact that humans and machines can judge depth using vision. On X, user Abdou ran the “invisible wall” through a monocular depth estimation model (DepthAnythingV2) - one that uses a single image with a single angle. This fairly simplified model can estimate the distance and depth of items inside an image - and it was able to differentiate the fake wall from its surroundings easily.
Tesla’s FSD uses a far more advanced multi-angle, multi-image tool that stitches together and creates a 3D model of the environment around it and then analyzes the result for decision-making and prediction. Tesla’s more refined and complex model would be far more able to easily detect such an obstacle - and these innovations are far more recent than the 5-year-old Autopilot stack.
While detecting distances is more difficult in a single image, once you have multiple images, such as in a video feed, you can more easily decipher between objects and determine distances by tracking the size of each pixel as the object approaches. Essentially, if all pixels are growing at a constant rate, then that means it’s a flat object — like a wall.
Case in Point: Chinese FSD Testers
To make the case stronger - some Chinese FSD testers took to the streets and put up a semi-transparent sheet - which the vehicle refused to drive through or drive near. It would immediately attempt to maneuver away each time the test was engaged - and refused to advance with a pedestrian standing in the road.
Would FSD hit a transparent film wall? This test showed it just avoids it.
Thanks to Douyin and Aaron Li for putting this together, as it makes an excellent basic example of how FSD would handle such a situation in real life.
Flaw 5: The Follow-Up Video and Interview
Following the community backlash, Mark released a video on X, hoping to resolve the community’s concerns. However, this also backfired. It turned out Mark’s second video was of an entirely different take than the one in the original video - this was at a different speed, angle, and time of initiation.
Mark then followed up with an interview with Philip DeFranco (below), where he said that there were multiple takes and that he used Autopilot because he didn’t know that FSD could be engaged without a destination. He also answered here that Luminar supposedly did not pay him for the video - even with their big showing as the “leader in LiDAR technology” throughout the video.
Putting It All Together
Overall, Mark’s video was rather duplicitous - he recorded multiple takes to get what he needed, prevented Tesla’s software from functioning properly by intervening, and used an outdated feature set that isn’t FSD - like his video is titled.
Upcoming Videos
Several other video creators are already working to replicate what Mark “tried” to test in this video.
To get a complete picture, we need to see unedited takes, even if they’re included at the end of the video. The full vehicle specifications should also be disclosed. Additionally, the test should be conducted using Tesla’s latest hardware and software—specifically, an HW4 vehicle running FSD v13.2.8.
In Mark’s video, Autopilot was engaged just seconds before impact. However, for a proper evaluation, FSD should be activated much earlier, allowing it time to react and, if capable, stop before hitting the wall.
A wave of new videos is likely on the way—stay tuned, and we’ll be sure to cover the best ones.
![Tesla Updates Energy App in Update 2025.8.3: Adds Reset and Distance Filter [VIDEO]](https://www.notateslaapp.com/img/containers/article_images/2025/updated_energy_app.jpg/979943fb17df5ae4e9fa668b8cd61fca/updated_energy_app.jpg)
![A Look at the Tesla Cybertruck’s Crumple Zones [VIDEO]](https://www.notateslaapp.com/img/containers/article_images/cybertruck/cybertruck-crash-test.webp/e43ef2433bd6e44ae8db63421604a4fb/cybertruck-crash-test.jpg)
