Tesla has officially begun internal testing of its awaited virtual queueing system for Superchargers. The news was shared by Tesla’s Director of Charging, Max de Zegher on X.
The Tesla Charging team has begun pressure testing the new feature and is planning for public pilots as their next step. While most users won’t experience heavy congestion at Superchargers, for those who do, it could be a real pain point. Virtual queues are designed to make it easier to charge at congested Superchargers by having a digital queue, rather than relying on owners to remain in line with their vehicles.
Pressure testing virtual queuing with the awesome @TeslaCharging teams, including for corner cases & bad actors. Public pilots next. If we get this right, it will be a big improvement for those rare cases with a wait. https://t.co/mxpFarYgJipic.twitter.com/IgVVH2wiOe
When we originally delved into Tesla’s plans to introduce a virtual queue system, it seemed obvious that the virtual queue would replace the current “Wild West” first-come, first-served system of vehicles trying to get pulled into a stall. This process will likely have two key integrations.
First up is integration directly into the vehicle software for Tesla vehicles. This means that when you’re navigating to a Supercharger that’s busy and virtual queuing is enabled, you will be automatically placed into the virtual queue upon arrival.
Then, your position in line is displayed on-screen and provides an estimated wait time, allowing you to relax, eat, or take a bathroom break without worrying about your place in line. Finally, once a stall becomes available and it’s your turn, you will receive a notification on your vehicle’s screen, as well as on the Tesla app, directing you to the open stall that will presumably only allow your vehicle to charge. We imagine that there will be a grace period for owners to pull up with their car. If that doesn’t happen within a certain period, the next car will likely be offered the charger.
The second integration is in the Tesla app for non-Tesla drivers. As Tesla continues to install Magic Docks and open Superchargers to non-Tesla EVs, more and more traffic comes to the world’s most reliable fast charging network. That means that Tesla also needs to manage expectations and queue times for non-Tesla vehicles, likely through a similar process, but done over the Tesla app instead.
The Devil’s in the Details
A simple “first-in, first-out” queue sounds great, but Max noted that it is easy to exploit things with bad actors. What prevents a driver from joining a queue remotely to reserve a spot, ignoring a notification, or trying to hop into an unreserved spot?
Well, Tesla should be able to manage these fairly easily, but they still require technical effort to implement. That means GPS geofencing for those attempting to join a queue, a short countdown timer for those late to take their spot, and a lockout for those who try to skip the queue are all needed.
What’s Next?
As Tesla has just started internal testing of this feature, it likely means that public-facing user interfaces and flows aren’t quite ready yet, but the underlying functionality is. It also means that Tesla is working to refine the little details to make the process as smooth and as easily accessible as possible.
While no pilot locations have been announced yet, it seems likely that Tesla will launch the pilot at some of the most notoriously busy Supercharger sites to gather testing data in the near future, once internal testing is complete. That means holiday travel routes or major highways, likely in California first, before rolling out elsewhere.
Virtual Queuing is a fantastic tech-first solution for the Supercharger network that helps transform that experience into a more calm and orderly process. Additionally, establishing a fair system that allows both Tesla and non-Tesla EVs to access will likely improve the overall experience. Along with the pilot program for dynamic Supercharger pricing that incentivizes people to use less-congested Superchargers, these changes should improve the Supercharger experience.
While Max mentioned it was designed for “those rare cases with a wait”, that tends to be the experience in larger cities further North, especially in New York, Michigan, or within Canada, where the few smaller Supercharger sites in big cities tend to be heavily congested. These queues will make the experience smoother for everyone involved, so we’re looking forward to seeing this come to fruition.
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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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