Ashok Elluswamy, Tesla’s Autopilot director, commented on our article and gave additional insight into how Tesla was able to add support for HW3 and what they’re working on next. He confirmed that Tesla’s FSD team was able to achieve similar performance between AI4 and HW3 with FSD V12.5
Similar Performance, Smaller Model
One of the key points Ashok mentioned was that HW3’s FSD 12.5 release has similar, but not exactly the same performance as the AI4 release. This appears to be due to the smaller AI model for HW3, which has been compute-constrained by memory and speed limitations.
Of course, Ashok also tells us to mind the fact that the parameter counts and size of the AI model aren’t exactly everything. Hardware 3 still has the advantage of being the primary focus of Tesla’s FSD teams until the new Supercomputer Cluster at Giga Texas comes online. That, plus the tremendous reams of data that Tesla has acquired from Hardware 3 vehicles on the road today means that the current Hardware 3 version of FSD V12.5 is probably in a pretty good spot.
Larger Model Coming to HW3
It looks like the Tesla FSD team is working on emulating AI4 in Hardware 3 now, as there are some unique hardware-based operations supported on AI4, that aren’t supported on Hardware 3. Ashok says that in order for Tesla to support the larger model on HW3 they’ll need to implement these AI4’s hardware features with software on HW3. He confirms that Tesla is actively implementing and verifying these operations and they plan to support the larger FSD model on HW3 in the future.
Right now it sounds like Tesla is compressing the model, but still able to get close to the same FSD performance of AI4.
We’re looking forward to seeing FSD 12.5 hitting HW3 vehicles in the upcoming weeks if all goes well with initial employee testing.
We were able to achieve similar performance as the AI4 12.5 release with a relatively smaller model for AI3. Deploying the larger model requires us to implement a few kernels in the compiler to emulate the same operations that are natively supported on the AI4 hardware. The team…
One of the keys here is Ashok has focused on mentioning that the same FSD V12.5 model can run on both hardware platforms in the future. He noted that the performance was similar, but not the same. We’re not quite sure how big the difference is going to be just yet, but it looks to be negligible – especially from the positivity behind his post.
Ashok also doesn’t mention FSD V12.6 or future major iterations of FSD, but we aren’t worried. It sounds like Tesla is still committed to supporting HW3 in future iterations of FSD working, so it looks like it’ll be in a good spot for the foreseeable future.
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To show off its scalability, Tesla has officially launched its first major expansion of its Robotaxi service area in Austin, Texas. The expansion comes just 22 days after the program’s initial public launch.
That’s a stunningly quick pace that sets a benchmark for how fast we’ll be expecting Tesla to roll out additional expansions as they validate and safety-check in additional area and cities. The new geofence not only adds a significant amount of new territory, but also makes Tesla’s service area in Austin approximately 4 miles larger than Waymo’s.
The expansion, which went live for users in the early access program earlier today, reshapes the map into… what we can call an upside-down T. It helps connect more parts of the city, and increases the service area by more than double.
So far, the initial launch has been operating without any significant issues, which means Tesla is ready and willing to continue expanding the program.
Rapid Scaling
While the larger map is a clear win for early-access users and especially those who live in Austin, the most significant aspect here is just how fast Tesla is going. Achieving a major expansion in just over three weeks since its initial launch is a testament to Tesla’s generalized autonomy approach with vision only.
Unlike methods that require intensive, street-by-street HD mapping that can take months or even years just to expand to a few new streets, Tesla’s strategy is built for this type of speed.
This is Tesla’s key advantage - it can leverage its massive fleet and AI to build a generalized, easily-applicable understanding of the world. Expanding to a new area becomes less about building a brand-new, high-definition map of every street light and obstacle, but instead a targeted safety validation process.
Tesla can deploy a fleet of validation vehicles to intensely focus on one zone, allowing the neural nets to learn the quirks of that area’s intersections and traffic flows. Once a high level of safety and reliability is demonstrated, Tesla can simply just redraw the geofence.
Geofence Size
Tesla went from approximately 19.7 sq mi (51 sq km) to 42.07 sq mi (109 sq km)in just 22 days, following the initial launch and safety validation. Within a few short days of launch, we began seeing the first Tesla engineering validation vehicles, hitting Austin’s downtown core, preparing for the next phase.
The larger footprint means more utility for riders, and that’s big, especially since the new service area is approximately four square miles larger than Waymo’s established operational zone in the city.
Highways and Fleet Size
The new territory enables longer and more practical trips, with the longest trip at tip-to-tip taking about 42 minutes from the southern edge of the old geofence to the northern edge of the new geofence. For now, Tesla has limited its fleet to operating exclusively on surface streets and does not use highways to complete its routes.
We also don’t know if Tesla has increased the vehicle fleet size quite yet - but if they’re intending to maintain or reduce wait times for even the early-access riders, the fleet size will easily need to be doubled to keep up with the new area.
This video clip shows the @robotaxi follows the Interstate (I-35) but does not take the highest.
Perhaps the most telling bit about how fast Tesla is expanding is that they’re already laying the groundwork for the next expansion. Validation vehicles have been spotted operating in Kyle, Texas, approximately 20 miles south of the geofence’s southern border.
Robotaxi Validation vehicles operating in Kyle, Texas.
Financial_Weight_989 on Reddit
This means that while one expansion is being rolled out to the public, Tesla is already having its engineering and validation teams work on the next expansion. That relentless pace means that if this keeps up, Tesla will likely have a good portion of the Austin metropolitan area - the zone they’ve applied for their Autonomy license for - serviceable by the end of 2025.
The pilot? A success. The first expansion? Done. The second expansion? Already in progress. Robotaxi is going to go places, and the next question won't be about whether the network is going to grow. Instead, the new questions are: How fast, and where next?
One of the most welcome features of the recently refreshed 2026 Model S and Model X is the addition of a front bumper camera. Now, thanks to some clever work by the Tesla community, it has been confirmed that this highly requested feature can be retrofitted onto older HW4-equipped (AI4) Model S and Model X vehicles.
The discovery and first installation were performed by Yaro on a Model X, and Tesla hacker Green helped provide some additional insight on the software side.
Unused Port and a Software Switch
The foundation for this retrofit has been in place for a long time, laid by Tesla itself. All HW4-equipped Model S and Model X vehicles, even those built before the recent refresh, have an empty, unused camera connector slot on the FSD computer, seemingly waiting for this exact purpose.
While the physical port is there, getting the car to recognize the camera requires a software change. According to Green, a simple configuration flag change is all that is needed to enable the front camera view on the vehicle’s main display once the hardware is connected and ready.
The Hardware: Parts & Costs
Yaro, who performed the installation on a Model X, provided a detailed breakdown of the parts and approximate costs involved.
Front Camera - $200 USD
Bumper Grill (with camera cutout) - $80 USD
Bumper Harness - $130 USD
Washer Pump - $15 USD
Washer Hoses - $30 USD
The total cost for the Model X hardware comes to around $455 USD, which isn’t too expensive if you were to DIY it. Tesla’s Electronic Parts Catalog has some of these parts available for order, and some can be ordered via your local Service Center. Yaro did note that he had to jerry-rig the camera connector cable, having salvaged the cable from a different camera harness.
The Model S vs Model X
This is where the project varies significantly. For the Model X, the retrofit is relatively simple. Because the main bumper shape is the same, only the lower bumper grill needs to be swapped for the version with the camera opening, along with installing the camera itself and the washer hardware.
For the Model S, the process is a bit more complex and expensive. Due to the different shape of the pre-refresh bumper, the entire front fascia assembly must be replaced to accommodate the camera. This makes the project far more expensive and laborious.
DIY or Official Retrofit?
The official front bumper camera on the Model X
Not a Tesla App
Right now, this is only a DIY retrofit. Tesla hasn’t indicated that they intend to offer this as an official retrofit for older vehicles at this time, but given the fact that it isn’t too complex, we expect that there is a possibility that they may do so in the near future.
All in all, this is about 3-5 hours of labor for the Model X, and approximately 5-7 hours of labor for the Model S, based on the official Tesla Service Manuals, using the front fascia reinstall process as a guide.
That means if Tesla does offer this as a retrofit service, it will likely cost between $800 and $1,200 USD when factoring in Tesla’s labor rates, but the total cost will vary regionally.
For those who own an AI4 Model S or Model X, it could be possible to request service for this installation, but as far as we’re aware, there is no official service notice for this retrofit at this time.
What About the Model 3?
For owners of the refreshed Highland Model 3, the only vehicle now left without a front bumper camera, the possibility of a retrofit is still uncertain. It has been noted by Green that some, but not all Model 3s built in late 2024 have an empty camera port on the FSD computer. This inconsistency means that while a retrofit may be possible for a subset of Model 3s, it isn’t a guaranteed upgrade path like it is for the Model S or Model X.
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