Musk Shares Tesla FSD Roadmap: What's in the Next FSD Update

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In a flurry of posts on X following the recent sightings of driverless Robotaxis on the streets of Austin, Elon has laid out a fairly detailed roadmap of Tesla’s upcoming changes for FSD in the coming year.

Musk shared details on two distinct new versions of FSD that are currently in development - one of which is coming soon and another that promises another leap in FSD’s abilities.

It’s a new version of software, but will merge to main branch soon.

We have a more advanced model in alpha stage that has ~4X the params, but still requires a lot of polishing.

That’s probably ready for deploy in a few months.

— Elon Musk (@elonmusk) June 10, 2025

FSD Increase Parameters By 4.5x

While the Robotaxis running around Austin are identical to new customer vehicles, they’re not running the same FSD build on customer vehicles. These Robotaxi Model Ys are running a newer FSD build.

While the exact version of FSD is unknown, Musk said that it’ll be released to customers soon. However, more interestingly, he also shared details on a newer version that’s coming next.

The newer version will include a 4.5 times increase in parameters and better memory usage. Earlier this year, Ashok shared details that the [amount of] on-board memory is restricting context size, so these memory improvements presumably allow Tesla to increase the context size in this latest version of FSD.

Musk said that this version will also arrive to customers later this year. This 4.5 times model appears to be in a relatively early alpha stage. This jump in parameters is even larger than the “3X increase” that’s detailed in the Upcoming Improvements of the FSD V13 changelog. Other improvements listed in the FSD v13 changelog were a 3x context length improvement, audio inputs, improvements to reward predictions and false braking, and support for destination options when arriving at the destinations. However, it’s not clear whether any of these others are included.

It’s a new version of software, but will merge to main branch soon.

We have a more advanced model in alpha stage that has ~4X the params, but still requires a lot of polishing.

That’s probably ready for deploy in a few months.

— Elon Musk (@elonmusk) June 10, 2025

What Increased Parameters and Context Length Mean

The increase in parameters allows FSD to understand the world with greater nuance, which in turn means smoother and more human-like decision-making and path planning. It also means FSD will become more capable of handling edge cases or inclement weather, a stressor noted by Tesla’s Executive team during the Q1 2025 Earnings Call.

Increasing the context length allows the vehicle to consider a longer history when making decisions. Context length and responsiveness are closely linked: a shorter context length enables quicker reactions, while a longer context length provides more informed decisions but introduces latency. The context length in terms of FSD is measured in seconds, where the vehicle uses just the past few seconds of video data to make a decision.

Retraining FSD

~4.5X increase in params should be ready for wide release later this year.

Super frugal use of memory bandwidth, caching exactly what is needed & squeezing microseconds out of everything are needed to maintain the frame rate.

And the whole system needs to be retrained.

— Elon Musk (@elonmusk) June 10, 2025

A more powerful AI model requires more computational power, and Elon provided some more insights into what exactly that means for the Tesla AI team. Frugally using memory bandwidth and squeezing every last drop of performance from AI4’s hardware is necessary to maintain its ability to keep up with the environment around it.

Musk says that this new, larger FSD version will require Tesla to retrain FSD from the ground up. Tesla is already planning on expanding its compute nodes with a second Cortex Supercomputer cluster. It takes an astronomical amount of data, time, and energy to train FSD, and with a major update on the horizon, it seems like Tesla has been putting the lion’s share of compute into this new build.

FSD Timeline

Musk laid out a relatively rough timeline for these new FSD improvements. Remember, with all things Elon, two weeks could very well be two months.

Soon: The current, tried and tested build that’s running on Tesla’s Robotaxi fleet in Austin will be merged into the main public FSD (Supervised) build. This build will be the next major build for customers. This could be FSD V13.3. It’ll be a step up, but not as large as the next version.

Late 2025: The new 4.5X parameter model is slated for a wider release several months from now. We’ll tentatively call this FSD V14 - because it sounds like an entirely new version being built from the ground up.

This is a much-needed update from Elon and Tesla on where FSD is headed and when. It’s been more than eight months since the last Autonomy Roadmap in October 2024, even if these updates are encoded in “Elon Time.” 

The streets will change very rapidly.

Autonomous cars will be very common throughout the world in 2 to 3 years.

— Elon Musk (@elonmusk) June 10, 2025

Licensing FSD

Elon also touched on the ultimate goals and the long-term business plan for FSD. With FSD already being considerably safer than the average human driver, alongside its superhuman reflexes and precision, Tesla will be well-positioned to license FSD.

Tesla AI/Autopilot could probably beat the best human around a track already.

Eventually, it really won’t be a contest at all. Human reflexes cannot match machines.

— Elon Musk (@elonmusk) June 10, 2025

As FSD and the Robotaxi network become widespread and other autonomy solutions fail to materialize in a financially prudent fashion, other companies will naturally turn to Tesla for autonomy. 

It’s Tesla’s golden moment to do all it can to implement the dream that it’s been striving for for over a decade. 

With a new FSD version on its way to customers and a fully rebuilt version on the horizon, there’s a lot for everyone to look forward to.

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Tesla Officially Unveils Bigger, 6-Seater Model Y L

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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.

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?

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Tesla’s Dojo 2 Supercomputer Chip Enters Mass Production

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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.

Can play Crysis at a billion frames per second

— Elon Musk (@elonmusk) July 12, 2025

Exascale AI: FSD, Optimus, and More

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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