What’s Coming in Tesla FSD V13

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As part of an update to its AI roadmap, Tesla has also announced the features that will be in FSD v13. Tesla provided many details about what we can expect, and there’s a lot of info to break down.

Tesla’s VP of AI, Ashok Elluswamy, also revealed that FSD v13 is expected to make FSD Unsupervised feature complete. That doesn’t mean that autonomy will be ready, as each feature will still need to work at safety levels higher than a human, but it means every key feature of autonomous vehicles will be present in FSD v13.

Let’s examine the v13 feature list Tesla and Tesla employees have recently provided to see exactly what’s coming.

Higher Resolution Video & Native AI4

FSD v12 has been trained using Tesla’s HW3 cameras and downsampling the AI4 cameras to match. For the first time, Tesla will use AI4's native camera resolution to get the clearest image possible. Not only will Tesla increase the resolution, but they’re also increasing the capture rate to 36 FPS (frames per second). This should result in extreme smoothness and the ability of the vehicle to detect objects earlier and more precisely. It’ll be a big boon for FSD, but it’ll come at the price of processing all of this additional information.

The HW3 cameras have a resolution of about 1.2 megapixels, while the AI4 cameras have a resolution of 5.44 megapixels. That’s a 4.5x improvement in raw resolution - which is a lot of new data for the inference computer and AI models to deal with. 

Yun-Ti Tsai, Senior Staff Engineer at Tesla AI, mentioned on X that the total data bandwidth is 1.3 gigapixels per second, running at 36 hertz, with nearly 0 latency between capture and inference. This is one of the baseline features for getting v13 off the ground, and through this feature update, we can expect better vehicle performance, sign reading, and lots of little upgrades.

Bigger Models, Bigger Context, Better Data

The next big item is that Tesla will increase the size of the FSD model by three times and the overall context length by the same amount. What that means, in simple terms, is that FSD will have a lot more information to draw upon—both at the moment (the context length) and from background knowledge and training (model size). 

In layman’s terms, Tesla has made the FSD brain bigger and increased the amount of information it can remember. This means that FSD will have a lot more data to work with when making decisions, both from what's happening right now and from what it has learned in the past.

Beyond that, Tesla has also massively expanded the data scaling and training compute to match. Tesla is increasing the amount of training data by 4.2 times and increasing their training commute power by 5x.

Video of the inside of Cortex today, the giant new AI training supercluster being built at Tesla HQ in Austin to solve real-world AI pic.twitter.com/DwJVUWUrb5

— Elon Musk (@elonmusk) August 26, 2024

Audio Intake

Tesla’s FSD has famously only relied upon visual data—equivalent to what humans can access. LiDAR hasn’t been on Tesla’s books except for model validation, and radar, while used in the past, was mostly phased out.

Now, Tesla AI will integrate audio intake into FSD’s models, with a focus on better handling of emergency vehicles. FSD will soon be able to react to emergency vehicles, even before it sees them. This is big news and is in line with how Tesla has been approaching FSD—through a very human-like lens.

We’re excited to see how these updates pan out - but there was one more thing. Ashok Elluswamy, VP of AI at Tesla, confirmed on X that they’ll add the ability for FSD to honk the horn.

Other Improvements

The other improvements, while major, can be summarized pretty simply. Tesla is focusing on improving smoothness and safety in various ways. The v13 AI will be trained to predict and adapt for collision avoidance, navigation, and better following traffic controls. This will make it more predictable for users and other drivers and improve general safety.

Beyond that, Tesla is also working on a better representation of the map and navigation inputs versus what FSD actually does. In complex situations, FSD may choose to take a different turn or exit, even if navigation is telling it to go the other way. This future update will likely close this gap and ensure that your route and FSD’s path planner match closely.

Of course, Tesla will also be working on adding Unpark, Reverse, and Park capabilities, as well as support for destination options, including parking in a spot, driveway, or garage or just pulling over at a specific point, like at an entrance.

Finally, they’re also working on adding improved camera self-cleaning and better handling of camera occlusion. Currently, FSD can and will clean the front cameras if they are obscured with debris, but only if they are fully blocked. Partial blockages do not trigger the wipers. Additionally, when the B-Pillar cameras are blinded by sunlight, FSD tends to have difficulties staying centered in the lane. This specific update is expected to address both of these issues.

FSD V13 Release Date

Tesla announced that FSD v13 will be released to employees this week, however, it’ll take various iterations before it’s released to the public. Tesla mentioned that they expect FSD v13 to be released to customers around v13.3, but surprisingly, they state that this will happen around the Thanksgiving timeframe — just a few weeks away.

Tesla is known for delays with its FSD releases, so we’re cautious about the late November timeline. However, the real takeaway is that FSD v13 is expected to offer a substantial leap in capability over the next few months—even if it’s exclusive to AI4.

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Tesla Reveals How It Tests FSD - A Series of Videos

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Tesla has published a 16-post series covering a wide range of unique scenarios against which the company tests each FSD release. Tesla’s VP of AI, Ashok Elluswamy, also provided some additional context, which we’ll cover below.

These scenarios could be difficult for a regular driver to respond to and are a good demonstration of FSD’s capabilities. Let’s take a look at all the different scenarios that Tesla regularly tests against. According to Ashok, these tests are only one of 10 ways Tesla validates their software. These tests were done against FSD v12.5.6.3, the HW4 build that’s on approximately 20% of the fleet.

We’ve embedded each video below and also provided some additional information.

1. Reverse Cut-in (Occluded)

This first test is for a car reversing out of a parking space, while occluded (vision blocked) by another car or obstacle. In the test, the Model Y notices the incoming car and then brakes with space left over.

2. Peeking (Occluded)

In this video, it's hard to even spot the car on the right that’s “peeking” forward—it's occluded by bushes on the side of the road. FSD notices and stops in time to let the other vehicle safely pass.

3. Left Turn Cut-in

An incoming vehicle that takes a left turn to enter the same lane of travel as FSD - spotted, stopped, and then continuing smoothly. In the second shot, you can see FSD left a considerable amount of space to let the vehicle cut in.

4. Parallel Cut-in (Occluded)

This is honestly one of the most common scenarios on a highway - someone cuts in while obscured into your lane of travel. Once again, FSD does its thing with plenty of space to spare.

5. Yield for Oncoming During Overtake

FSD’s path planner plans an overtake around a stationary vehicle here, sees the oncoming traffic, and politely waits its turn to continue. This is another everyday scenario, especially on urban and suburban streets.

6. Stop Sign Right-of-Way Violator

There are a surprising number of people who don’t know how stop signs work. However, FSD does know how they work and also knows what to do if others act unpredictably. This is one of the best demonstrations of FSD’s capability to react quickly and effectively to unpredictable behavior on the roads.

7. Door Opening During Overtake

Another overtake scenario, but this time the vehicle being overtaken throws open its door into traffic. Not necessarily the wisest of moves, but humans are unpredictable. Good to see Tesla working to save its vehicles from both hitting the door or having the door hit with its new Blind Spot Monitoring While Parked feature.

8. Right Turn Harsh Braking

This scenario is another common one - someone is taking a right turn, and you expect them to complete the turn, but they go ahead and slam on the brakes. Here, FSD brakes in time - using Automatic Emergency Braking - and then continues safely. Tesla has been working to improve AEB and the scenarios it can react to - and these are all a part and parcel of FSD’s real-time and active safety features.

9. Left Turn Across Path

This one is pretty clean-cut - someone takes a left turn even though you’re on your way through the intersection. This particular accident is one of the most common - 53% of cross-path accidents involve a left turn through an intersection where a side impact will be lethal. FSD can make a big difference - over 8,000 people die in North America alone in this particular scenario.

10. Cut-Out to Static Cone

Here, FSD smoothly reacts to an object on the road as the vehicle ahead dodges it. We’d love to see this scenario done with different types of objects or debris, as this is another common item - especially with roadkill on country roads. A good demo of FSD’s collision avoidance maneuvers too!

11. Dynamic Debris (Dropped Cone)

Taking it one step further, FSD successfully notices, slows down, stops itself from hitting the bouncing cone, and then makes it around safely. If you’ve ever seen someone strap something down in the bed of a pickup and forget to say “This ain’t going anywhere” - this is that exact scenario.

12. U-Turn Cut-in (Occluded)

Another high-speed occluded cut-in, this time for a vehicle making a U-Turn from an oddly shaped intersection. FSD started braking the moment the first couple pixels of the Model Y were beyond the bush occluding vision. With a human’s reaction time, this would have resulted in a T-bone.

Ashok Elluswamy, Tesla’s Director of AI - mentioned that this is possible because of low latency and high intelligence - combined together, it enables FSD to make a threat assessment and decide what to do, very quickly. It also considers the potential of a rear-end collision - and there is collision avoidance baked into that decision-making.

13. High-Speed Cut-out to Stationary Vehicle

Similar to the cone cut-out, this one happens at 73mph (117km/h)! FSD sees the car dodging, notices there’s an obstacle, and moves out of the way without dropping speed.

14. High-Speed Harsh Braking

Another common scenario - in fact, the number one reason why pileups occur on highways is the harsh, sudden braking of vehicles in front. FSD once again notices and comes to a safe stop here.

15. High-Speed Stationary Child

Tesla has been previously greatly criticized for its ability to come to a safe stop for children playing on the road. Here, Tesla is demonstrating its capability of doing so - once again with highway speeds of 73mph. 

16. High-Speed Crossing Child

And to really make the point - it can do it with a crossing child too. Tesla has made a strong commitment to safety for vulnerable road users, and this is a good way to show how it works.

That’s a lot of unique scenarios that Tesla tests against - and each and every build has to be vetted against this huge list of different safety tests in order to ensure that the build that ends up in customer hands is as safe as possible. With FSD v13 looking like it's coming soon, we’re excited to see where this takes Tesla next. 

With Musk announcing that FSD v13 is coming soon, it really is starting to feel like Unsupervised FSD and Robotaxi could be pushed out sometime next year.

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Musk Confirms FSD V13 is Coming Soon

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Tesla announced an updated roadmap for FSD in late October. With it, they announced that FSD v13, the one that’s expected to make Unsupervised FSD feature complete (although not 100% reliable), would start being sent to employees by the end of the week.

We have yet to see any hints or sightings of employees testing FSD v13, but Elon Musk has now stated that FSD v13 is coming soon.

It sounds like Musk is talking about the employee release as it usually does, but it’s not immediately clear. Tesla originally predicted that select owners would receive FSD v13.3 around Thanksgiving.

Musk also mentioned that FSD v13 is trending to be about 500% better than the current build of v12.5.5.3 on the Cybertruck. If that’s true, Unsupervised FSD is just a regulatory leap away, rather than a technical or training challenge. However, let’s remember that Musk has often thrown out these vast improvement numbers that don’t appear to materialize when the update rolls out to customers. There’s no doubt that FSD v13 will be a big milestone and have several new features, such as Autopark at destination_, Unpark and more, but the much lower miles per intervention will likely come in later revisions.

Tesla has already seen drastic improvements this year, moving from V11.4.9 to v12.3.6, and then more recently to V12.5.4.2. Each successive build has had major improvements in how FSD is able to react and respond in real-time while also becoming smoother and safer.

We’re in for some exciting times as an even better FSD version makes its way to customers soon. And in order to really make the point, Tesla has also shown off how they conduct FSD Safety Testing in a series of videos, which we’ll include below.

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