Tesla, Inc.

Q4 2025 Earnings Call — January 28, 2026

Analyst: Thank you so much. The next question, a bit related, are there still plans to launch new models to address different price segments and vehicle types, which could materially expand the TAM for Tesla?

Executive: Yeah. To further on what we were just talking about, we've launched our least expensive models ever over the last few months and are continuing to expand those models globally. Over the last decade, we have continually brought down the cost of our vehicles without sacrificing range, performance, or premiumness. And we'll continue to do that, as Vaibhav said, investing in our factories. But these are all tradeoffs of where we spend our time and money. And to Elon's point just now, with CyberCap coming, we are aiming to bring that Tesla premium ride experience to our largest market yet. That could be five or ten times our current levels of production. This new autonomous market, you have to start thinking about us as moving to providing transportation as a service more than the total addressable market for the purchased vehicles alone. Of course, we do have plans to have robo-taxis in various shapes and sizes, but obviously cyber cab will be the grand majority of that volume. Yeah, the vast majority of miles traveled will be autonomous in the future. You know, I would say probably less than, I'm just guessing, but probably less than 5% of miles driven will be where somebody is actually driving the car themselves in the future, maybe as low as 1%.

Analyst: The next question is, historically, Tesla has spoken about gross margin per model. Are there standalone gross margin targets for the current models, excluding the benefits for FSD sales?

Executive: You know, we've talked about this with the previous two questions, but transportation, as we know, is changing. And I think we cannot keep applying the same framework from a car sales model to the future, what we are trying to do. So it has to be looked at more holistically. You know, autonomy software will be the driver for growth from now on. And as we aim to maximize the global feed, we have been laser focused on cogs from our side because that is something which we manage. So we will keep focusing on that, but I think we need to look at it from a different dimension. Yeah, like this CyberCab, the whole design of CyberCab was to optimize the fully considered cost per mile of autonomous driving. And it's a different design problem than if you're trying to design cars for people who will be driving versus being driven.

And so CyberCap is, like I said, super optimized for minimum cost per mile and also for a much higher duty cycle. So we would expect CyberCap to be used, you know, probably 50 or 60 hours a week instead of the 10 or 11 hours a week that a driven vehicle is used. So typically people might drive their car for an hour and a half a day on average, so it's like 10 hours per week out of 168. But I think an autonomous vehicle is likely to be used probably five times as often, which means that you need – to design the vehicle for a much more wear and tear for you in time and much more resilience. It's more like a commercial truck that's in continuous operation or close continuous operation is how you design an autonomous vehicle. And so we will have – larger vehicles in the cyber cap in the future that are designed for full autonomy. And we've actually shown pictures of this and, in fact, have shown prototypes. So this is not exactly a secret. In fact, we've given people rides in them. You know, we're not keeping this, hiding this light under a bushel here. You know, it's like we're literally saying what we're going to do and have said what we're going to do for a while.

So, you know, I think long-term we would really the only vehicles that we'll make will be autonomous vehicles with the exception of the next generation Roadster, which we're hoping to debut in April. Hopefully. It's going to be something out of this world.

Analyst: The next question we unfortunately have to skip because it's not related to Tesla, and we would like to remind folks who use the SAVE platform to please focus these questions on Tesla. So with that in mind, we're going to move on to the next question, which is, what is the current bottleneck to increased robo-taxi deployment and personal use on supervised FSD? Is it the safety and performance of the most recent models, or is it people to monitor the robotaxis in car or remotely, or is there some other blocker?

Executive: Yeah, we have scaled the robot access service that's available to customers over the last year in order to just learn the scaling problems without having to wait for unsupervised. This year, two goals. One is to learn as much as possible from the fleet with the safety monitors. And secondly, we laser focused with the engineering team to solve the unsupervised FSD problem. I think we did both. By the end of last year, we, you know, we had a long tail of issues that we were able to churn through. And then in the last couple of weeks, we had started our unsupervised robot taxi service to public customers in Austin. I think some customers took pride last week and also the service continues today without any real cars or something like that. Separately, we did scale the fleet size in the Bay Area and in Austin, and through that we learned, you know, issues with charging and other issues that we would have seen once we sort of scaled the unsupervised fleet. So, both are happening in parallel.

A variant of the software that's used for the robot taxi service was shipped to customers with V14, and customers saw a huge jump in performance, like a lot of, you know, happy feedback from customers. So, and since then, we have improved the software significantly as well. And customers will continue to see with their own software releases that the software is so good that, you know, they're like screaming to remove the driver monitoring software because they're bored inside the car too much. Adding to that a little bit with what Ashok said about learning about our charging and service needs, you know, we're using our vast network of charging and service centers that really only Tesla has in this space to jumpstart our infrastructure build-out needs to get ahead of robotaxi and autonomous vehicle demand. And we expect that because of this network, we are the only company capable of scaling at the rate that is needed for the tsunami of autonomy that is coming.

Analyst: Great. Moving on to the next question. After the unveil of the Cybertruck, Elon stated that if it didn't sell well, Tesla would build a more conventional-looking pickup. How practical would it be to create this new design on the Cybertruck architecture, and could it be conveniently built on the existing production lines?

Executive: Actually, in its segment, Cybertruck continues to be a leader in selling more than any other electric truck out there, while our competition continues to pull back. But to the question itself, from a line standpoint, we always design our lines to be super flexible. We built 3 and Y on the same line. We built S and X on the same line still, showing that we can do that. The Cybertruck line was designed in the same way and is one of our most fully ready for autonomy platforms. Yeah, we will transition the Cybertruck line to just a fully autonomous line. And there's obviously a market there for cargo delivery, like you say, like localized cargo delivery within a city, within a few hundred miles, something like that. There's a lot of cargo that needs to move locally within a city, and an autonomous Cybertruck could be very useful for that.

Analyst: Great. Moving on to the next question. Regarding Optimus, could you share the current number of units deployed in Tesla factories and actively performing production tasks? What specific roles or operations are they handling, and how has their integration impacted factory efficiency or output?

Executive: Yeah, we're still very much at the early stages of Optimus. It's still in the R&D phase. We have had Optimus do some basic tasks in the factory, but as we iterate our new versions of Optimus, we deprecate the old versions. And so it's not in usage in our factories in a material way. It's more so that the robot can learn. We wouldn't expect to have, you know, any kind of significant Optimus production volume until probably the end of this year. Optimus Gen 3 is an awesome robot. It is awesome. Yeah, it's an awesome robot that minimizes any differences. Basically, it looks like a human. People could be easily confused that it's a human. And this helps our strategy for the AI, too, because you can learn from how humans do these tasks, and it's very easy to teach the robot to do it in the same way as opposed to previous robots. Yeah, I mean, I guess one thing I should say, like, is, you know, there's a lot of news of, like, you know, various companies announcing layoffs and whatnot. But, you know, at our Tesla factory in Fremont, we actually expect to increase headcount over time and to significantly increase output from our factories. So we don't have any layoff plans. We expect to actually increase headcount.

Analyst: Great. The next question, similar to the other autonomy questions, but slightly different. When is FSD going to be 100% unsupervised?

Executive: Well, it is 100% unsupervised, and FSD is 100% unsupervised. I mean, we obviously have cars operating with no one in them and no safety monitor and no follow car or anything like that in Austin right now. For customers, we... we're being just very cautious with the rollout. I mean, with each successive version, as we prove it out and we make sure that there are no sort of unique issues in particular cities, because sometimes you get like some very difficult intersection. And it'll be an intersection where a lot of humans have accidents, by the way. There's like some pretty nutty intersections where a lot of humans make mistakes and have accidents in various cities. So we want to make sure that FSD can handle those unusual intersections. Like we take L.A., for example, where Wilshire and Santa Monica combine is like there's about I don't know, 20 traffic lights. And people are constantly having accidents there. So you want to make sure that FSD can handle unique things in a particular city. And we're also just being paranoid about safety. But with each successful release of FSD, we will reduce the amount of driver monitoring that's needed proportionate to the safety of the FSD build.

Analyst: Great. As it relates to RoboTaxi, what has surprised you about the rollout so far? We've talked about what's constrained the fleet expansion to date, but it appears there are 200 vehicles based on public tracking. Is that something that we can confirm?

Executive: I don't think there's anything that really surprised us because we had a large fleet, we had all the metrics, so there was not sort of a surprise. It was just continued work to grind down on the long period of issues, and that's what enabled us to launch the unsupervised service in Austin. Yeah, and I mean, in terms of robo-taxi vehicles carrying paid customers, I think we're well over 500 at this point between the Bay Area and Austin. Yeah, there's varying amounts of, like, vehicles depending on the load. But, yeah, you can have, like, more vehicles during, like, peak times and then fewer vehicles in the off hours. This will probably, you know, double every month type of thing. It's on an exponential curve. I mean, one other thing people forget that, you know, we've been deliberate on all this in the sense that we have the supporting infrastructure already been in place, whether it's service centers, charging. Yes, we'll have to augment as the fleet grows depending upon the density of where the demand is and whatnot. But it's not something like we just stumble upon it and we're starting to – we've been at it for years. Yes, not every city is – designed the same way, same thing. Our infrastructure is also not the same in every city, but you have to give us credit that it's been a journey. And like Lars said, if there is some company which can do it, we've already been at it, so we should be able to deliver much better.

Analyst: Great.

The next question is about chase cars, which we already covered. So moving on to the last question. Elon, you've been spending significant personal time on Tesla's chip design. What was the forcing function behind this increased involvement? And do you think external chip sales will represent a significant portion of Tesla's valuation by the end of the decade?

Executive: Well, I mean, I tend to spend time on whatever the most critical issue is for the company. And completing the AI5 chip design and having it be a great chip is – It's arguably the number one most critical thing to get done, which is why I'm spending more time on that than currently anything else at Tesla. I spend pretty much every Saturday on this and a chunk of every Tuesday. So it's like if I'm spending my Saturdays on something, it's going to be something pretty important. I do think AI5 will be a very good chip, and I feel quite confident about the design at this point. And then AI6, which will follow that, aspirationally would follow that in under a year, will be yet another big leap beyond AI5. I feel pretty good about our chip strategy right now. But in terms of selling it outside of Tesla, we first need to make sure we have enough chips for all of our vehicle production and all of our Optimus production. And then we will actually use the AI5 chips in our data centers. We already use the AI4 chips in our data centers. So when we do training, it's a combination of the AI4 chips and NVIDIA hardware primarily that we do training with.

So, but you said by the end of the decade, I mean, that's like – Things are changing so fast that it's hard to imagine what happens at the end of the decade. I mean, when I look ahead at, say, what's the limiting factor for Tesla growth, if you go, say, three or four years out, I think it actually is chip production. Is there enough AI logic and enough memory, enough RAM for our volume. And right now, I see that as being the thing that probably limits our growth in three or four years, which would imply that we're not selling chips outside of Tesla because we need them.

Executive: In fact, I think it's going to make sense and this is definitely going to be sort of a controversial. But I think Tesla needs to pull the tariff out. I mentioned this at the meeting. But even when we look at the output of – the best-case output of all of our key suppliers, and I would say even – beyond suppliers like strategic partners like Samsung, TSMC, and Micron, and we say, like, what's the most you could possibly make, then it's not enough. So I think in order to – remove the constraint, the probable constraint in three or four years, we're going to have to build a Tesla TerraFab, a very big fab that includes logic, memory, and packaging domestically. And that's actually also going to be very important to ensure that we are protected against any geopolitical risks. I think people may be underweighting some of the geopolitical risks that are going to be a major factor in a few years. Now, you know, a lot of people will say, like, that's crazy. FABs are really hard. I'm like, yes, I know FABs are really hard. I don't think they're easy. But we do a lot of hard things. You know, we didn't used to have car factories.

We didn't used to have battery cell factories or lithium refineries or, you know, mega pack factories or, you know, all these other things. We figured it out. So I think it's – I think if we don't do the Tesla tariff app, we're going to be limited by – supplier output of chips. And I think maybe memory is an even bigger limiter than AI logic. So, you know, for example, we have chip supply deals with TSMC in Arizona and Samsung in Texas, but currently there are no advanced memory fabs at scale in the United States. There are zero, literally zero. Hopefully, you know, Micron will have something going in a few years. They're all headquartered in Idaho, you know, where they make a lot of potato chips, where they need to make computer chips, too. So, anyway, we're working with our strategic partners on the chip front, memory and logic. But I think... I think we've got to also try our hand at building a large-scale fab that integrates logic memory and packaging. And if we don't do that, we're just going to be fundamentally limited by supply chain, especially if there's some geopolitical situation, it would be quite a severe situation.

So I think it would be crazy not to try the tariff app. So, yeah. Great. We'll have a bigger announcement on this in the future.

Analyst: Awesome. With that, we're going to move on to analyst questions. The first analyst is Emmanuel from Wolf Research. Emmanuel, please feel free to unmute yourself.

Analyst (Emmanuel Rosner, Wolf Research): Great. Thank you so much. My first question is on the CapEx. You signal a pretty large increase to over $20 billion for this year. I was hoping to better understand where the investments are going. Any way to dimension for us which of the product line or technologies account for the bulk of the increase? And also, do you view this as like one time in nature, 2026? I guess how much of this is an ongoing level of high spending for a number of years and then just finally still on that, with that level of spending you're going to be burning cash how should we think about cash balance or any other way to finance this?

Executive: Yeah, I mean I tried to put this in my opening remarks too but I'll try and go a little bit deeper. There's about starting production this year. So there's a lot of cash, capex, which is going into that. Then as we are trying to scale Optimus, we need a lot more compute. So we're putting more money towards compute as well. And then we're training. And then we're also going to be spending money to expand the capacity at existing factories. On top of it, you know, just keep in mind that none of these numbers which I shared of 20 billion factors and anything to do with the solar fab or the semiconductor chip fab, those would be, as Elon mentioned, would come later on. And you think your second part of your question was, is this one-off or would we expect more? I think we're getting into this investment phase because we have big aspirations. And when you look at it, some of these aspirations are, I call them as infrastructure play, especially if you have to do a chip fab and we have to do a cell manufacturing fab. Those are infrastructure plays. And that funding takes a little bit longer. And you would be in an investment cycle for a little bit longer.

Initially, the third part of your question was how are we going to fund it? Initially, obviously, we have over $44 billion of cash and investments on the books. So we'll use our internal resources. But there are ways where we can fund it, especially when we look at the robo-taxi fleet because – you know anytime you have a consistent stream of cash flow you can go and get money from the banks and we have had conversations with banks about it and that is something how we're going to do it and then on the infrastructure play side yeah like i said we don't have a number yet but given that it's it's an infrastructure player it's a longer tail we will have to look at a little bit more in terms of how we fund it, whether it's through more debt or other means.

Analyst (Andrew, Morgan Stanley): Great.

Our next question comes from Andrew from Morgan Stanley. Andrew, please feel free to unmute yourself.

Analyst (Andrew): Great. Thanks so much for taking the question. I just want to start on the XAI investment that you guys announced today. You know, you talked about there being some collaboration, you know, between the companies. So I'm just hoping to get more information or if you're hoping that you could shed more light on what that looks like and maybe how the work XAI is doing can be leveraged at Tesla and vice versa.

Executive: Yeah, I mean, if you looked at the disclosure, which we also put in there, we do talk about this is literally a furtherance of our Master Plan 4. And even today, if you look at Tesla vehicles, we are using GROK in there. And as we look at whether we can do it ourselves. Yes, there are a lot of things which we can do ourselves, but if there are things which XCI can help accelerate our progress, then why should we not do that? And that is the reason why we've gone ahead with such an investment, because this is part of the strategic initiative, because as it is, if you remember, I talked about how many things which we're doing ourselves. If there are ways and means we can find efficient ways for others to help us, and XAI literally fits into that mold. So that's why we went ahead with it. We just had like a lot of investors ask us to do this. There was like a lot of investor, a ton of shareholders said like we should invest in XAI. So that's like we're just doing what shareholders have like asked us to do pretty much. But Grok will be very helpful in, say, maximizing the efficiency of the management of a large autonomous fleet.

So, I mean, if you've got an autonomous fleet that's, you know, in the future – 10 million vehicles or tens of millions of vehicles then optimizing the efficient use of that fleet grok will be way better than any heuristic solution or sort of manually managed solution. And if you say you're managing say a large team of optimist robots to build a factory or build a refinery you know and and say a rare hypothetical like a this is a hypothetical example a rare earth ore refinery, which we do desperately need in America, then you say, well, like what's going to organize the Optimus robots to build that ore refinery? That would, you know, you kind of need an orchestra conductor. And so then Grok would be kind of the orchestra conductor for the Optimus robots to build the Hypothetically, it might not be hypothetical in the future. I'm just saying it's not currently on our plans. But, you know, we do need a lot more ore refining capacity in the U.S. So then what's going to manage, let's say, 1,000 Optimus robots?

Analyst: Ready. We're going to move on to the next question, which is coming from Dan Levi at Barclays. Dan, please feel free.

Analyst (Dan Levi, Barclays): Great. Great. Thank you. Elon, you talked about some of the constraints on memory. Given the very tight supply, are there any near-term constraints on procuring memory? And if there are, to what extent could you look at modifying the functionality in the vehicle, similar to what you did in 21 when we saw shortages on MCUs? And maybe how are you thinking about bridging in the next few years?

Executive: Well, the Tesla AI is very compute efficient and very memory efficient. So I think one of the metrics one should consider for any given AI model is the intelligence per gigabyte, especially when you're constrained on RAM, having an AI that has very high intelligence density per gigabyte. I actually think Tesla is ahead of the rest of the world in intelligence density of AI by an order of magnitude or more. Like, this is going to sound like a pretty bold statement, but I kind of know what the, you know, what the intelligence efficiency of the big models are, like GROK and, you know, a bunch of the other models. And I tell those AIs, like, in terms of its memory efficiency, more than an order of magnitude better. So... So that puts us in a pretty good position, actually, for scaling. And we actually do think that there's – we do have a solution for scaling logic and memory for, let's say, the next roughly three years.

But if you start going beyond three years and we look at the scaling plans and how many fabs are getting built, and especially if you factor in geopolitical uncertainty, You know, there's always risk that maybe those chips don't arrive that people were expecting to arrive. So that's why I think we need to have more fab capacity in the U.S., just in case, you know, chips don't stop arriving for any reason. You know, this is really existential for Tesla because if – Optimus is completely useless without an AI chip. It's not like, you know, at least the cars we can put steering wheels and pedals in or retrofit them if need be, but Optimus is just a mannequin without, you know, it's like the Tin Man or whatever from Wizard of Oz, but even worse, he's a Tin Man who can walk. Optimus won't even be able to, or just sit there without an AI chip. So we've got a good solution for a significant scale for the next roughly three years. Beyond that, we will be supplier limited. And so we've got to figure out some game plan to not be supplier limited.

Analyst (George, Canaccord): Great.

Our next question is going to come from George at Canaccord. George, please feel free to unmute yourself.

Analyst (George): Hi, everyone. Thank you for taking my question. So there's been a surge of startups, particularly from China, entering the humanoid market. I'm wondering what the long-term competitive advantages that keep Tesla ahead are and how, based on what you've seen, will Optimus fundamentally differ from these competitors? Thank you.

Executive: Well, I do think that by far the biggest competition for humanoid robots will be from China. China is incredibly good at scaling manufacturing, actually quite good at AI, as you can see from the open source, or not the open source, but I guess some of them are open, actually. But basically the... the models that China is distributing for free are actually quite good, and they keep getting better. So China is very good at AI, very good at manufacturing, and will definitely be the toughest competition for Tesla. To the best of our knowledge, we don't see any – significant competitors outside of china but china will definitely be the tough competition is there's no two ways about it. I always think like people sort of outside of china kind of underestimate china. China’s an ass kicker next level so. I guess we're going to vote. We think Optimus will be much more capable than any robot that we are aware of under development in China. So we think we'll be ahead in terms of the real-world intelligence, the electromechanical dexterity, especially the hand design, which is a by far the hardest thing in the robot.

In fact, I'd say there's really three hard things about humanoid robots. Building an incredible hand that has the same degrees of freedom and dexterity as a human hand is an incredibly difficult engineering challenge. Then there's the real-world AI and scaling production. Those are the three hardest problems by far for humanoid robots. I think where Tesla is the only company that actually has all three of those components.

Analyst (Colin, Oppenheimer): Great. And

our last question is going to come from Colin at Oppenheimer. Colin, please feel free to unmute yourself.

Analyst (Colin): Thanks so much. You talked a lot about the CapEx spend, but this is an incredibly ambitious technology development program that you're talking about. Can you talk a little bit about the R&D spend and how you're thinking about the synergies of the different components, particularly on the hardware side? You know, if you think about, you know, batteries into chips, into memory and the efficiency of the system and what sort of advantages you think you'll end up getting out of, you know, some of these purpose-built devices that you'll end up integrating into multiple end markets.

Executive: Well, really all we're trying to do is make sure that we can scale to a very high volume with autonomous vehicles, with humanoid robots, and that we address geopolitical risk, which I think, you know, there's so many companies out there that are asleep at the switch with regard to geopolitical risk or they just have their head in the sand and hope nothing bad will happen. I'm way more paranoid than that. I always think of Andy Grove's famous statement, only the paranoid survive. Why did he come up with that statement? I didn't tell. Let's think. So I think there's a lot of wisdom in that statement. So we're going to be paranoid and make sure that we can continue to build batteries and robots and AI chips no matter what happens. And companies that don't do that, a bunch of them will cease to exist. Yeah, I mean, remember, all this comes out of necessity. It's not that we want to do it. It's just we have no choice. Yeah, I mean, we built the most advanced lithium refinery in the world, by the way. So it's not just... Like our lithium refinery in Corpus Christi is not just a copy of what others have done.

It's an entirely new process that is fundamentally more efficient and more advanced than anything else in the world. The same is true of our cathode refinery here in Austin. And we wish others would build this. Can other people please... For the love of God, in the name of all that is holy, can others please build this stuff? It's not the first time you've said that. Exactly. I mean, this is not the first time you've said something like this. Like, why do we have to build these things? Why can others not also please, can some others build these things? I mean, it's very hard to build these things. We build them out of desperation. Not because nobody else is building lithium refineries and cathode refineries. You know, we're pretty much not just the largest, but also the only lithium refinery and cathode refinery in America. So, yeah, so we're making moves to make sure that no matter what happens, Tesla will prosper.

Executive: Great. Unfortunately, that's all the time we have for Q&A today. We really appreciate everyone's questions, and we look forward to talking to you next quarter. Thank you very much, and goodbye.

Q3 2025 Earnings Call — October 22, 2025

Emmanuel (Wolf): Hi, everybody. So, Ilan, you talked about expanding production of vehicles as fast as possible now that you have confidence in the unsupervised autonomy. How should we think about that in the context of your existing capacity of 3 million units? Is that where you're hoping to get volume to? What sort of timeline are we talking about? And would this require some level of boosting or incentivizing demand? Like would this basically be prioritizing volume over near-term profitability, given the longer-term opportunity?

Ilan (Executive): Well, our capacity isn't quite 3 million, but it will be 3 million at some point. Aspirationally, it could be 3 million within, we could probably hit an annualized rate of 3 million within 24 months, I think, maybe less than 24 months. Bearing in mind there's an entire supply chain, like a vast supply chain, that's got to also move in tandem with that. So we're going to expand production as fast as we can and as fast as our suppliers can keep up with it. And then we're going to think about where do we build incremental factories beyond that. The single biggest expansion in production will be the CyberCab, which starts production in Q2 next year. That's really a vehicle that's optimized for full autonomy. It, in fact, does not have a steering wheel or pedals and is really an engineering optimization on minimizing cost per mile, like fully considered cost per mile of operation. So that's, you know, for the economy.

For our other vehicles, they still have a little bit of the horseless carriage thing going on where, obviously, if you've got steering wheels and pedals and you're designing a car that people might want to go very fast acceleration and tight cornering, like high performance cars, then you're going to design a different car than one that is optimized for a comfortable ride but doesn't expect to go past 85 or 90 miles an hour. and it's just aiming for a gentle ride the whole time. That's what CyberCab is. Do I think we'll sacrifice margins? I don't think so. I think the demand will be pretty nutty. Here's the killer app, really, what it comes down to is, can you text while you're in the car? And if you tell someone, yes, the car is now so good, you can be on your phone and text the entire time while you're in the car. Anyone who can buy the car will buy the car. End of story. Um, so, um, that's what everybody wants to do. In fact, not everyone wants to, they do do that. And that's why, in fact, the reason you've seen like there's been an uptick in accidents, uh, pretty much worldwide is because people are texting and driving.

Um, so, uh, autopilot actually dramatically improves the safety here. Um, because if somebody is looking down at their phone, they're not driving very well. Um, so that's, that's really the game changer. At this point, I feel 100% confident that we can solve unsupervised full self-driving at a safety level much greater than human. We've released 14.1. We've got technology roadmap that's I think pretty amazing we'll be adding reasoning to the car. Our weld simulator for sim for reinforcement learning is is pretty incredible like our like our when you see it that the tesla reality simulator um it's you can't tell if a screen the video that's generated by the tesla reality simulator and the actual video looks exactly the same. Um So that allows us to have a very powerful reinforcement learning loop to further improve the Tesla AI. We're going to be increasing the parameter count by an order of magnitude. That's not in 14.1. There are also a number of other improvements to the AI just that are quite radical. So it's... this car will feel like it is a living creature. That's how good the AI will get with the AI for computer with this before AI five.

And then, and then AI five, like I said, is by some metrics, 40, 40 times better. Um, let's just say safely, it's a 10 X improvement. Um, so it might almost be too much intelligence for a car. I do wonder like how much intelligence should you have in a car? It might get bored. Um, actually, um, And then one of the things I thought like, well, if we got all these cars that maybe are bored, well, while they're, while they're sort of, if they are bored, we could actually have a giant distributed in inference fleet and say like, well, if they're not actively driving, let's just have a giant distributed inference fleet. Um, you know, at some point, if you've got like tens of millions of cars in the fleet, or maybe at some point, a hundred million cars in the fleet, um, and, um, let's say they had. At that point, I don't know, a kilowatt of high-performance inference capability, that's 100 gigawatts of inference distributed with cooling and power conversion taken care of. So that seems like a pretty significant asset.

Adam (Morgan Stanley):

The next question comes from Adam from Morgan Stanley.

Dan (Barclays): Hi, good evening. Thank you for taking the question. Elon, I know that Tesla's really focused on with master plan for bringing AI into the physical world. And I think we've seen over the past, this willingness for Tesla to engage and go into new markets, new TAMs. So when you think about the growth prospects, how do we define the areas that are really within Tesla's core competency versus where do you draw the line for markets or AI applications that are outside of Tesla's core competency?

Ilan (Executive): Actually, I'm not sure what you mean by AI applications outside of Tesla's core competency. But we kind of. we didn't have any of these core competencies when we started, you know? Um, so it's like we had zero core competencies, total competency of zero actually. Um, so I mean, you can think of Tesla as like, I don't know, a dozen startups in one company. Um, you know, and, and, uh, I've initiated every one of those startups. So it's, uh, it wouldn't use to make battery packs, stationary battery packs, but now we're do. make them for the home, make them for utility scale with Powerwall Megapack. We've created the supercharger network globally. No one else has created a global supercharger network. In fact, our North American supercharger network is so good that basically every other manufacturer in North America has converted to our standard and uses the Tesla supercharger network. But if it was so easy, why don't they just do it? Um, and, uh, the chip design team, um, started that from scratch. The Tesla AI software team was started from scratch. Um, I literally just say, Hey, we're going to start this thing.

I posted on Twitter now X, and then, you know, join us if you'd like to build it. Um, in fact, uh, Ashok was, I believe the first person I interviewed for the Tesla autopilot team, which we're now called Tesla AI software team. because it is the ad software team. So, you know, it's core competencies created while you wait. And, you know, optimists at scale, it is the infinite money glitch. It's like, this is a, it's difficult to express the magnitude of, like, if you've got something like that, Optimus, I think, could probably achieve 5x the productivity of a person per year because it can operate 24-7. It doesn't even need to charge. It can operate it tethered, so it's plugged in the whole time. That's why I call it, if you're true of sustainable abundance, where working will be optional. You know, there's a limit to how much AI can do in terms of enhancing the productivity of humans. But there is not really a limit to AI that is embodied. That's why I call it the infinite money glitch.

Management: One thing which I'll further add is, I mean, people forget, like, our first iteration of Autopilot was 10 years back. So, you know, Elon had started this way back in the day. We've got the tweets to prove it. Exactly. And then even on the Optimus side, as much as people think, okay, this is a new thing, I still remember, was it four plus years back, we were in a finance meeting with Elon, and Elon said, hey, our car is a robot on wheels. And that's where we started developing. In fact, most of the engineering team, which is working on Optimus, has come from the vehicle side. And that's why, you know, when we talk about manufacturing process, we have the wherewithal because the same engineers who worked back in the day on drive units are working on actuators now. So that's where we can, if there is any company which can do it at scale, that is going to be us. But we also have actually added a lot of new engineers as well to the team.

So there's actually a lot of the credit for the Optimus engineering is actually also new engineers many of them that are just out of college actually yeah uh so uh the optimus engineering uh team is a very talented engineering team um i'd say like wow actually so um and uh you know the optimus reviews at this point are that there's the engineering review um and then there's the manufacturing review being done simultaneously um with an iterative loop between engineering design and and manufacturing because then we see we we design something and we say like oh man that's really difficult to make we need to change that design to make it easier to manufacture um so we've made radical improvements to the design of optimus while increasing the functionality but making it actually possible to manufacture like i'd say optimus 2 is almost impossible to manufacture frankly um but um To Bob's point, we've gone from a person in a robot outfit to what people have seen with Optimus 2.5, where it's doing kung fu. Optimus was at the Tron premiere doing kung fu out in the open with Jared Leto. Nobody was controlling it.

It was just doing kung fu with Jared Leto. uh you know at the cron premiere um you can see the videos online um and um actually the funny thing is like a lot of people walked past it uh thinking it was uh just a person even though with optimus uh 2.5 you can see that it has uh you know a waist that's three inches wide that results in not a human um so uh but but the movements were so human-like that people didn't realize a lot of people didn't realize they were looking at a robot So, um, and what I'm saying is like Optimus three will be a giant improvement on that. Um, and made it scale. Um, but like I said, a very difficult thing. Um, yeah, the, the, the Optimus, uh, sort of injuring and manufacturing reviews. And there's the Friday night meeting with Optimus, which sometimes goes till midnight. Um, and then. My Saturday meeting is the Saturday afternoons with the AI5 chip design team. So those two things are crucial to the future of the company.

Dan (Barclays): Did you have a follow-up?

Dan (Barclays): Yeah, just as a related question. Maybe you could just talk about to what extent are the AI efforts at Tesla and XAI complementary, or are they just different forms of AI? Maybe you could just help distinguish for the audience. Thank you.

Ilan (Executive): Yeah, there are different forms of AI. So the XAI, so Grok is like a giant model. that you could not possibly squeeze Grok onto a car. That's for sure. It is a giant piece of a model. With Grok, it's trying to solve for artificial general intelligence with a massive amount of AI training compute and inference compute. So, for example, Grok 5 will actually only run effectively on a GB300. That's how much of a beast that Grok 5 is. So, whereas Tesla's models are, I don't know, maybe about less than 10% the size, maybe closer to 5% the size of Grok. So, yeah, they're really coming at the problem from very different angles. XAN and Grok are competing with Google Gemini and OpenAI, ChatGPT, and that kind of thing. Some of it is complementary. For example, for Grok voice, being able to interact with Grok in the car is cool. For Optimus, voice recognition and voice generation. So that's that's helpful there, but they are coming at it from kind of opposite ends of the spectrum.

Walt (LightShed): Alrighty, Adam, let's give it another try. When you're ready, please unmute yourself for the next question.

Walt (LightShed): Did you hear me now? Yes. Perfect, thank you. Just getting back to Austin, if you can remove the safety driver at year end, is the limitation in the Bay Area just regulatory or is it kind of the market by market learning process? And I guess similarly in the eight to 10 markets that you mentioned to get added, Is the decision there to put a safety attendant in the passenger seat or the safety driver in, is that your step-by-step process to opening up a market, or is it really just the regulation in the individual market?

Ilan (Executive): Well, I think even if the regulators weren't making us do it, we'd still do that as the right, cautious approach to a new market. So just to make sure that we're being paranoid about safety, uh, I think it makes sense to have a sort of, uh, sort of either safety driver or safety occupant in the car, um, when we first go to new markets to just to confirm that there's not something we're missing, um, because all it takes is like one in ten thousand trips to go wrong and and you've got you've got an issue so um it's just to make sure like is there some about a city like a very difficult intersection or, I don't know, something that's an unexpected challenge in a city for that one in 10,000 situation. So I think we probably could just let it loose in these cities, but we don't want to take a chance. And like, you know, what we're talking about here is, you know, maybe three months of safety driver in a new Metro to confirm that it's good. And then I would take the safety driver off that, that kind of thing.

Walt (LightShed): Okay. And then on, on FSD 14, it has a different feel than 13. And it's also, I think a little different than what it feels like in Austin. Are you, is it basically deaf different development paths path that you're doing in terms of the robo taxi stuff versus what you're dropping to the early adopters? And when you, and when you push these new builds, Is it that you're looking for notable improvements in intervention rates, or is that largely solved and it's more about adding the functionality, like the parking, the drive modes, or just the overall comfort?

Ilan (Executive): The first priority when we release a major new software architecture for autopilot is safety. So it starts off with safety, obviously safety prioritized, and then we solve comfort thereafter, which is why I don't recommend people take the initial version. That's why I say most people should wait until 14.2 before they actually download version 14, because by 14.2, we'll have addressed many of the comfort issues. The priority is very much safety first, and then thereafter, the comfort issues. That's why most people are like, it'll be safe, but jerky. Um, and, uh, we just need time to kind of smooth the rough edges, um, and soulful comfort in addition to safety with a, with a major news, uh, autopilot architecture, uh, change. Um, but, uh, it, it really is, uh, I mean, I, I know what the, you know, the roadmap is for the Tesla real world AI and, and, uh, very granular data detail. Obviously Ashok is leading that, um, And I spent a lot of time with the team going in excruciating detail here on what we're doing to improve the real-world AI. And like I said, this car is going to feel like it is a living creature. And that's with AI 4 before even AI 5.

Yeah, the roadmap is super exhilarating. We're waiting so much to release all the stuff we are working on. In terms of what we ship to customers versus Robotaxi, it's mostly the same. Obviously, customers have some more features. They can choose whether the car wants to park in a spot or drive here or something like that, which is not super relevant for Robotaxi. But there's only a few minor changes like those ones. But the majority of the algorithms and architecture and everything is the same between those two platforms. Yeah. But as I mentioned earlier, we'll be adding reasoning to, um, I don't know, is that like reasoning in like 14.3, maybe 14.4, something like that. Um, yeah. So with reasoning, it's literally going to think about which parking spot to pick, uh, at this. So it's going to say, this is the entrance, but actually probably there's not a parking spot right at the entrance. If it's a full, you know, if the, if the parking lot is fairly full, the probability of an open parking spot right at the entrance is very low. Um, but actually what it'll simply do is drop you off at the entrance of the store and then go find a parking spot.

Um, but it's, it's going to get very smart about figuring out a parking spot. It's going to spot, figure out it's going to spot empty spots much better than human. It's got 360 degree vision. Um, and it's going to, yeah. Yeah. Like I said, just, it's going to re use reasoning to solve things. I'm putting that all inside the computer that has a four. is the actual challenge. That's what the team is working on. Because obviously, you can do reasoning on the server. That takes forever. But then in the car, you need to make real-time decisions. So putting all that into the computer that's in the car, that's the challenge. Yeah, that's why I say I have a pretty good understanding of AI, the giant model level with Grok and with Tesla. And I'm confident in saying that Tesla AI has the highest intelligence density. When you look at the intelligence per gigabyte, I think Tesla AI is probably an order of magnitude better than anyone else. And it doesn't have any choice because that AI has got to fit in the AI4 computer.

But the discipline of having that level of AI intelligence density will pay great dividends when you go to something that has an order of magnitude more capability like AI5. Now you have that same intelligence density, but you've got 10 times more capability in the computer.

Colin (Oppenheimer): Great.

The next question will come from Colin at Oppenheimer. Colin, please unmute yourself when you're ready.

Colin (Oppenheimer): Thanks so much, guys. I appreciate you bringing up the challenges of hand dexterity and humanoids, along with the complexity of the supply chain and the vertical integration you guys are pursuing. I'm just trying to harmonize the timeline for the start of production next year with the current state of the supply chain and what sounds like a fair amount of work remaining on the dexterity before you can really freeze the hardware design and start to scale up production.

Ilan (Executive): Well, the hardware design will not actually be frozen even through start of production. There'll be continued iteration because a bunch of the things that you discover are very difficult to make. You only find that pretty late in the game. So we'll be doing rolling changes for the Optimus design even after start of production. But I do think that the new hand is an incredible piece of engineering and know that's well like i said we'll have um a production intent prototype uh ready to show off in you know q1 probably february or march um and then we're uh yeah we're going to be building a you know million unit optimus production line um you know hopefully with the production start towards the end of next year. But that production ramp will take a while to get to an annualized rate of a million because it's going to move as fast as the slowest, dumbest, least lucky thing out of 10,000 unique items. But it will get to a million units. And then ultimately, we'll do Optimus 4. That'll be 10 million units. Optimus 5, maybe. 50 to 100 million units. I mean, it's really pretty nutty.

Management: Alrighty. That is, unfortunately, all the time we have for Q&A today. Before we conclude, though, Vebav has some closing remarks.

Vebav (Executive): Thanks, Travis. I want to take the time to talk about an extremely important vote, which is being held on November 6th. The meeting will shape the future of Tesla, and we are asking you for as our shareholders to support Elon's leadership through the two compensation proposals and the re-election of Ira, Kathleen, and Joe to the board. Note that it is a team sport, and here at Tesla, the board is an integral part of the winning team. Shareholders are at the center of everything we do at Tesla, and a special committee has laid out a compensation package. Like Elon said, we don't even want to call it a compensation package. Yeah, the point is that there needs to be enough voting control to give a strong influence, but not so much that I can't be fired if I go insane. But, you know, and I think that sort of number is in the mid-20s approximately. As a company that has already gone public, there's no... We've investigated every possible way to...

How do you achieve increased voting control without... know um is there some way to have like a super voting stock but there really isn't there is no way to have a super voting stock after you've gone public um but for example uh google uh meta um you know many other companies have this um but they they had it before they went public and so it sort of gets i guess grandfathered in um tesla does not have that um so It's just, like I said, I just don't feel comfortable building a robot army here and not, and then, uh, you know, being ousted because of some asinine, uh, recommendations from ISS and glass Lewis who have no frigging clue. I mean, those guys are corporate terrorists and, and the problem. Yeah. So let me like explain like the core problem here is that, uh, so many of the index funds, um, the passive funds vote along the lines. of whatever Glass-Lewis and ISS recommend. Now, they have made many terrible recommendations in the past, that if those recommendations have been followed, would have been extremely destructive to the future of the company.

But if you've got passive funds that essentially defer responsibility for the vote to Glass-Lewis and ISS, then you can have extremely disastrous consequences for a publicly traded company if too much of the publicly traded company is controlled by index funds. It's de facto controlled by Glass-Lewis and ISS. This is a fundamental problem for corporate governance, because they're not voting along the lines that are actually good for shareholders. That's the big issue. I mean, that's what it comes down to. ISS, Glass-Lewis, corporate terrorism. Yeah, and I would say, you know, the special committee did an amazing job in constructing this plan for the benefit of the shareholders. There's nothing which gets passed on until the time shareholders make substantial returns. So that's why, you know, in the end, I would say I would urge you to not only vote on the plan, but also vote on all the three directors because of their exceptional knowledge and experience. And literally, we at Tesla work with these directors day in, day out. I mean, there is not even a single day that one of the directors I haven't spoken to or one of my colleagues hasn't spoken to.

And even the directors out here are not just reading out of PowerPoint presentations. They're actually working with us day in, day out. So again, I just urge you guys as shareholders to vote along the board's recommendation. Thank you, guys.

Management: Great. Thank you, Vibhav. We appreciate everyone's questions today. We look forward to talking to you next quarter. Thank you very much and goodbye.