While the performance of FSD has been the star of the Robotaxi Network, new details are emerging about Tesla using modified Model Ys for the service. According to a report from Business Insider, the program to modify some vehicles for Robotaxi is known internally as “Project Halo”, and it involves more than just a newer FSD version.
These details help connect the dots between the subtle physical changes that have been spotted on the Robotaxi Model Ys.
Physical Clue: Expanded Rear Housing
Eagle-eyed observers in Austin were quick to spot a key physical difference on the Robotaxi fleet vehicles: a larger-than-normal housing on the rear window. This immediately sparked speculation that Tesla had integrated new components to support the Robotaxi rollout. We initially expected that these may have been minor changes like Tesla is known to roll out, but now we have a better idea of what exactly is under that new housing.
Halo Communications Unit
According to the insider source, Tesla’s Halo vehicles are equipped with a second telecommunications unit. That’s a significant change from customer vehicles, which are equipped with just a single unit near the roof of the vehicle.
According to the report, this unit serves a dual purpose. It provides redundant, high-precision GPS data, and most importantly, allows the vehicle to maintain a constant, reliable connection with Tesla’s Robotaxi support team. That includes connectivity for teleoperation, if necessary. This hardware may be the physical backbone for the human assistance portion of the pilot phases of Robotaxi.
As we saw in the command center image shared by Ashok Elluswamy, these vehicles are streaming video from six cameras, potentially putting too much of a strain on the vehicle’s single cellular modem.
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Probably Not Starlink
While we initially mused that this could be holding a Starlink Mini dish, the space taken up by the housing is far too small to permit the installation of a Mini. Instead, it is approximately the same size as the telematics control unit that Tesla installs in the ceiling of its newer vehicles, which include a 5G modem.
Tesla is likely using the second connection for redundancy or to increase data throughput.
Quickly Iterating on FSD
All that data throughput likely serves a third purpose as well - providing live data streaming for Tesla’s Robotaxi Operations Hub back at Gigafactory Texas. That isn’t necessarily for support teleoperations, as we previously mentioned.
It is likely that Tesla is pulling video data from the Robotaxis to quickly improve the current version of Unsupervised FSD. Early-access testers noticed that in just a day, Tesla was issuing improvements, which means data is moving from vehicle to training in a snap.
Yesterday robotaxi would get like an inch away from this wall (first video) while pulling up. I saw 4 different Robotaxis do it.
Today it seems fixed. I've seen 2 robotaxis. Is Tesla really changing things this quickly? pic.twitter.com/zfdchBL771
Well before the launch, Elon said that the vehicles used for Robotaxi would be unmodified vehicles coming straight from the factory. It seems that isn’t exactly true, but it could be in the future.
So, how can we reconcile the unmodified statement with the clear evidence of Project Halo hardware? The key here lies in the difference between a stock Tesla’s FSD capabilities, versus the operational hardware required to run a commercial Robotaxi service.
Elon’s entire point is that the fundamental FSD hardware — the cameras, sensors, and FSD computer — is standard on every car coming off the line. From a capability standpoint, a consumer car can perform Unsupervised FSD.
The second communications unit is best understood as service hardware. They don’t make the car drive better, but they provide the redundant connectivity needed for operational oversight, remote assistance, and the massive data uploads required for a pilot program.
This hardware may also be necessary for Tesla to meet regulatory compliance requirements for a commercial autonomous vehicle service for the foreseeable future.
These are unmodified Tesla cars coming straight from the factory, meaning that every Tesla coming out of our factories is capable of unsupervised self-driving! https://t.co/n94ln0Uas6
The Business Insider report also mentioned that Halo vehicles would have self-cleaning cameras. That isn’t a new hardware feature; in fact, it appears to refer to the software feature where Robotaxis can thoroughly clean its front-facing cameras [video and details], which will eventually make its way to owner vehicles.
Wrapping Up
The insider confirmation of Project Halo and its specialized hardware helps to provide a clearer picture of exactly what Tesla is doing with Robotaxi. It seems that for now, it’s not simply just consumer cars running advanced hardware, it’s a fleet of very lightly purpose-modified vehicles meant to support the pilot rollout.
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Tesla has unveiled its 6-seat Model Y variant in China, known as the Model Y L. This new variant of one of the world’s best-selling vehicles comes with a longer wheelbase, adjusted C-pillar design, and most importantly, a six-seat interior layout.
The vehicle’s specifications have been officially listed in a filing with China’s Ministry of Industry and Information Technology (MIIT), confirming a launch for this fall.
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The addition of a longer wheelbase and a more spacious third row is a fantastic addition for the Model Y’s family utility, and positions this variant as sort of a mini Model X, but let’s compare the sizes to really know how this new Model Y compares to a Model X.
Meet the Model Y L
The defining feature of the new Model Y L is its six-seat configuration. This layout has previously been exclusive to the larger and more expensive Model X. While Tesla has offered the Model Y in a 7-seat configuration before, the third row was much too small to be utilized by anyone but small children.
Comparing Model Y L to the Model X
@xiaoteshushu on X
Let’s compare this upcoming Model Y L to the regular Model Y and the Model X.
Vehicle/Dimension
Wheelbase
Overall Length
Model Y
2,890mm / 113.8 in
4,797mm / 188.9 in
Model Y L
3,040mm / 119.7 in
4,976mm / 195.9 in
Model X
2,965mm / 116.7 in
5,060mm / 199.2 in
The new wheelbase of 3,040mm is a significant stretch from the standard wheelbase, and in fact, is longer than the Model X’s wheelbase of 2,965mm. However, the overall length of the vehicle is 84mm (~3 inches) shorter than the Model X. This means the vehicle sits neatly between the current Model Y and Model X, filling a much-needed gap.
While this Model Y L is slightly smaller than the Model X, it doesn’t necessarily mean that it’s smaller inside. The Model X features a much larger front end than the Model Y, accounting for several inches. When you line up the front wheel base of the Model X with this new Model Y, the vehicles are almost exactly the same length.
Tesla has designed this Model Y to be a bit more compact and efficient than the Model X, and likely much cheaper, while featuring the well-loved design of the new Model Y.
Other Specifications and Price
The MIIT filing also provided a detailed look at some additional specifications. The Model Y L is a dual-motor, AWD variant, so it will likely be more expensive than the current Model Y AWD that’s available in China today. Tesla charges an additional $6,500 USD when upgrading the Model X from a 5-seat configuration to a 6-seat layout, so we may see something similar here.
The extra length has been added behind the C-pillar, resulting in a longer rear profile for the Model Y L. To accompany this, Tesla has added an updated rear spoiler, similar to the one found on Performance variants, but not carbon fiber. There is also a new wheel design to complement the updated look, along with unique Model Y L badging and a new light gold paint option.
In classic Tesla fashion, no Tesla is slow - and the Y L has a 0-100 km/h (0-60mph) time of 5.9s, with a top speed of 217km/h. Alongside an 82.5 kWh LFP battery pack, the Model Y L boasts an impressive CLTC range of 688 km (427 mi).
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Launch & Availability
According to posts from Tesla China on Chinese social media, the new Model Y L is scheduled to launch in the fall of 2025. Its official listing in the MIIT database is essentially the final regulatory step required before sales can begin, which means the launch is really just around the corner. For now, it appears that Tesla intends to launch this vehicle only in China, as no other filings have been made in other regions. However, these could be revealed in the coming months.
The new Model Y L is a huge addition to Tesla’s lineup - one that addresses the Chinese preference for vehicles with longer wheelbases and additional passenger room in a compact SUV package. The question is - will this variant make its way to North America and Europe?
Solving real-world artificial intelligence - whether for autonomous driving, real-world robotics, or advanced reasoning - requires an almost unfathomable amount of computational power. To meet this challenge, Tesla has been developing its own custom AI training hardware while simultaneously purchasing hardware in the open market.
Now, the next-generation Dojo 2 chip has reportedly entered mass production with the world’s largest semiconductor manufacturer, TSMC. While many may consider this a side quest, expanding Tesla’s computing base will be necessary to achieve exascale supercomputing, which will be crucial for all of Tesla’s AI ambitions.
Elon Musk called Dojo 2 “a good computer,” and then followed up with a classic computer performance joke - Dojo 2 can indeed play Crysis at a billion frames per second.
While Tesla has effectively utilized powerful third-party GPUs to train its models to date, the Dojo supercomputer is a ground-up, application-specific solution designed for a single purpose. It will efficiently process massive amounts of video data for training neural networks. The Dojo 2 chip itself is the key that unlocks this potential.
Dojo 2 will train the vision-based neural nets that FSD relies on, allowing Tesla to process video from its massive global fleet of vehicles even faster. As Tesla continues to improve FSD, one of the biggest challenges has been the intake of video for handling difficult edge cases.
Hundreds of thousands of miles of training data may pass by before an edge case is identified and trained on, but it all needs to be analyzed, labeled, and processed, which is key for Dojo 2. Each new useful piece of training data will help Tesla proceed down the march of 9s, making FSD just that little bit better every time.
This process requires massive amounts of compute and training time - but it is an absolute necessity to improve FSD. Of course, this goes beyond just FSD in vehicles. Tesla’s humanoid robot, Optimus, also runs on FSD to navigate and interact with the physical world.
While it may be a custom version of FSD, it remains FSD at its core, which means the same neural nets that analyze the environment and build a 3D map of the world for your car perform the same work for Optimus.
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Custom Approach to AI Hardware
Dojo 2’s power doesn’t just come from raw compute; it comes from a series of architectural choices that make it excel at training FSD and differentiate it from general-purpose hardware, or even other AI-specific hardware.
To this end, Tesla is using TSMC’s new Integrated Fan-Out with Silicon-on-Wafer (InFO-SoW) packaging technology. For massive AI workloads, heat and the speed at which data moves between chips are often the biggest bottlenecks.
This new packaging technique allows for high-bandwidth connections directly between processing dies, which lowers latency and dramatically improves heat dissipation, all key to building massive and dense compute clusters.
Unlike general-purpose chips, Dojo 2 is designed with a custom instruction set, specifically built to train FSD. The cores are specifically made to accelerate the exact mathematical operations, like matrix multiples and systolic arrays, which form the backbone of Tesla’s vision-based neural networks.
By building its own hardware, Tesla can then integrate its own software and compilers directly with the silicon, optimizing for specific workloads and avoiding the performance penalties that can result from using third-party software, such as Nvidia’s CUDA.
The start of Dojo 2 may seem like a side quest for some, but it’s actually a key step for Tesla’s AI technologies that give them an advantage over the competition using off-the-shelf hardware. They’ll need to continue investing in custom hardware to improve FSD at a reasonable pace, rather than the current glacial pace we’ve seen over the last few months.
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