All right. Hello everybody. Welcome to the second day of big tech earnings as they begin. I'm here with Tanner, Jose, and then something that also looks like Jose even though it's not Jose. Our friend Neil, who is using Jose's thumbnail today, to...
You should just keep that as your background.
Yeah. Yeah. Honestly, I think like Jose overload, Jose like...
It is such a good thumbnail, dude. It is such a good thumbnail.
Thank you. Sometimes I'm okay with creativity.
Jeez.
Okay, so yesterday we had Netflix and SpaceX. Today we have Meta and Tesla. I'm going to put a poll right here in the chat. Which one do you guys think outperforms? I think the majority of us and our collective audiences owns Meta more than Tesla, but I'm pretty sure a decent chunk of our audiences own Tesla. So, put in the chat which one you own more of. For me, it's definitely Meta, and I think for the rest of these guys, it is also Meta. Neil might be Tesla because he was there very early. But Neil, we'll start with you. Pick which one you want to talk about. What do you think is going to happen today?
Well, I have no Tesla anymore. I have way more Meta. So, there is that. Um, which one do I want to talk about more?
Yeah, let's start, let's start with Meta then. Let's start with the one you own. Like, what do you think?
Because like it's not because I don't own Tesla that I don't want to talk about it. There is just way more to talk about Meta today than there is about Tesla. Just like there is way more to talk about SpaceX than there is about Tesla as of today. That's just the reality of it. Unless they suddenly come out with something Optimus, but I don't think that they'll give us, they'll give us way more information during the call. So Meta, I would love to hear way more on Muse adoption, subscriptions, enterprise. I mean, we saw some enterprises, businesses, business adoption, what they're seeing there. WhatsApp Business, we know that that has been doing very well for them over the past two years or so. I just don't see how the capex number stays the same after SpaceX yesterday. Is that going to have a negative impact on the stock? Well, previous quarters, yes. This quarter, if they can mix the increasing capex with the, okay, Muse adoption is through the roof, we just need way more compute in order for this to go globally, then maybe, maybe that's going to be good enough for them. I still think that the core business is going to be completely fine. So, I don't know what the stock will do. The stock did pull back a little bit over the last couple of days. So, we are close to $700, which is still cheap in my opinion, but I am biased because I hold shares. But yeah, I'm expecting a good report and definitely an exciting call.
Okay. Um, Jose, I know you've been buying Meta a lot over the past couple weeks and months. Your thoughts on his earnings?
Yeah, so I think what I'm super excited about Meta is to finally get some more clarity from Zuck. I think last earnings the market really wanted him to talk more about selling compute, and Mark really kind of pushed. He's like, that's a great market, but we believe selling intelligence is higher margins and a better product to do with our compute now that Muse is getting a lot of traction. I want him to show a little bit more details on that business. Right? We just heard from SpaceX yesterday that selling compute is extremely, extremely positive for our business. So, does Mark still believe that the right way to go about it is to sell intelligence? And is Muse accelerating that, or are we getting some business results out of that right now? Because if we are, I think if they do increase capex, the market would be a lot more right with that case. Like if they go, look, we're actually making money out of Muse right now. We're actually seeing improvements, and because of that, we're going to increase our capex. I don't think the market will punish it as much opposed to if it just says, you know what, we're just going to increase capex because the man is crazy. Give me a little bit more meat. And then yeah, so that's one of the things, kind of the Muse interaction, the monetization, and if we see an increase in capex.
Tanner, are you also looking for a little more meat out of Zuckerberg today?
Well, um, yeah. I mean, I'm excited to hear from Mark and the rest of the team, but no. Okay, jokes aside, I'm really interested to hear how their operating expenses will adjust to the Muse blowup. We essentially went from, you know, a nent amount of people using Muse Spark 1.3 to the world using Muse. So, that I'm really excited about, but we do have to factor in that $12 billion hit. Um, my understanding is they're taking it this quarter rather than trying to spread it across a larger time frame. So, there will be, from my understanding, a $12 billion hit to net income this quarter. I don't know if Wall Street has adjusted numbers, so I imagine...
And that's from the legal expenses due to the correct lawsuit, right?
Yeah. And then today we got hit with potentially another $25 billion penalty. However, I think that'll be appealed, and that'll be a lot longer before we end up seeing anything from that. But the $12 billion, that is what Meta agreed to pay, and that's settled. So, they are likely to miss on EPS. It's just how much on revenue can they end up beating by. On the Tesla side, it's one of those things where I agree with Neil and Jose, you know, what have we seen? But it's like one of those things where it's like, I mean, we'd need to see flying cars for me to be interested in this company. And then there we go. But it's not going to be materially impactful to their overall growth. The one interesting part that I am interested to hear from Elon and the team, from what I heard, that was their largest spike of Tesla website traffic. And if they are going to say, 'Hey, this actually did make a material difference to the amount of car sales that we think we are going to do,' that could be quite interesting. But right now, I mean, I'll focus on Meta. I've got Meta shares. I don't have Tesla shares. So, I'm excited to listen to the call. And I think that's at 4:30. Actually, it'll be a little bit earlier.
Yeah. So, for the structure of the stream today, we'll have Meta's call at 4:30. I believe we'll have Tesla's at 5:30. I don't think Tesla's doing a video call. But we will be listening to Meta and Tesla. Now, a couple things on Meta. So, Tanner talked about this $25 billion New Mexico potential penalty. This would be like disgusting for their EPS guide next year if they actually have to pay this. I agree they'll probably appeal it, but nonetheless, not the best headline today. And then, I don't know how many people saw this, but unfortunately, this was reported by Semaphore. Meta plans to issue new non-voting shares to fund AI investments without diluting Zuckerberg's control. Meta could officially announce the non-voting stock plan as soon as Wednesday alongside quarterly earnings. I doubt if they're going to do this, they wouldn't announce it today. Which means if they do it, have they already pre-negotiated some stock sales with like a Berkshire type of company? Are they just giving it straight to the public? What is the price that they're diluting at? Does Zuck think, okay, 650 to 700 is a good range? Like, I think there's a lot of questions that we're going to have to deal with today. And on top of that, you have this just come out right now. Anthropic is officially rolling out something called Claude Duet. Yes. Wait, what?
Why'd you say yes if you didn't even... You said yes first time there.
No, no, it's the way that he pronounced it that drove me crazy. They just announced their agent, which is similar to ChatGPT's. But I just don't like the way Mitch pronounces things.
It's do it. Like what do you... what... it's det. I hear now. I hear it now.
It's duet. It's a duet. Is it like Nike just do it or...
So everyone says do it versus do it.
That's those two people that go up on stage and they're speaking together. That's a do it.
No, it's not. No. When you say it like that sometimes.
I mean maybe. Anyway, the point is Anthropic just entered into Muse's category, which obviously means Anthropic thinks it's important. But nonetheless, that's more competition on Meta as it falls below 700 right here. So, we have a lot of questions to get into. Not to mention, Zuck has to actually give us a good call. The past two quarters have been, in my opinion, as a shareholder of this company, just not good performances by Zuck on the call. So, hopefully we get some good numbers and we can withstand it here today. The majority of people in the chat are saying Meta will do better than Tesla. I think people are underestimating Tesla just because it's been a year and there's not been much growth, but it's up 3%. I mean, do we think there's a world where they announce something today, Tanner or Neil, that gets this thing back above 400 after hours?
I'll send that over to Neil.
Uh, I don't know because we already know production delivery numbers. We know the energy deployment, and I think that was a bit lower than expected for this quarter. So, I don't know. I don't know. I don't want to say stupid things, so I'll shut up.
One thing that I am curious about Tesla, last earnings they talked about potentially, they mentioned they have so much power with the chargers that they have that they're thinking of ways to maybe adding compute to them. I know I feel like every single quarter we kind of hear some new story. I want to see if maybe we hear that story again and see if there's any actual... I don't even want to use the word anymore, meat, any meat to this story, or if it was just like, hey, we're just talking again for another quarter, and then we're going to hear something else this quarter.
So EPS on Meta we're looking for 540 on the GAAP basis, 63 billion of revenue. On Tesla we are looking for about 26 cents on a GAAP basis, 28 billion of revenue. I think both companies are probably going to beat the top and the bottom. Meta maybe misses because of the legal expenses, but I think it's going to be about the guide, Meta Muse, and then for Tesla, it's all going to be robo taxi and Optimus, and I don't know how much they can communicate on the slide deck versus the call. But I think Meta definitely will have a bigger reaction up or down versus Tesla given how aggressive the algos are on another number that's very important to Meta because it's treated like a hyperscaler. But just capex, I mean, I think the guide for next year, correct me if I'm wrong, Jose, is like close to 180 billion. And if that goes to like 250 or something...
But I mean, we were just... I was just talking to Neil earlier this morning. If, right, and we talked about it, right, Neil was like, if SpaceX is trying to do 10 gigawatts of compute next year and it's about what, 50 to 40 to 50 billion, you're telling me SpaceX is planning on spending north of 300, 400 billion in capex, and every other hyperscaler or big tech is going to be like, you're the only one, we're going to stay here with our 180, 200 billion dollars. So, I don't know. I don't know if it's going to be this quarter or next quarter, but we're going to be surprised by the capex races we're going to start to see.
Yep. I think that's definitely a number that Wall Street's going to care about as well. Farzod, thank you for the $20 super chat. First time where two of my major holdings report earnings on the same day. I'm shaking uncontrollably. Amit, nice haircut. You look cute.
Okay, before Farzat leaves here, because of him, I've been playing with Grokbot today. I've used some of his Grokbot bots or whatever. I don't know. You can click on a link that he made, and then poof, your Grokbot just learns a new skill. So, not bad. Not bad at all. Not bad at all. Burning tokens like a [__] here. But...
I didn't hear a thank you, though. That's all I... You should say thank you.
Well, I was also going to say thank you for the compliment, and I was going to say that I just got out of the shower, and Tanner told me to leave my hair exactly how it is because he thought it was so uncontrollably cute. So that's what... so...
Uncontrol... I was shaking uncontrollably.
Yeah, exactly. So you got to thank Tanner for the hairdo today. All right, here we go. 10 seconds. This is what we live for. Meta and Tesla on the same day. Thank you everybody for being here. Wednesday, October 21st, 4 p.m. The stock market is now closed.
All right, we should be getting results in the next two minutes. We also have IBM. Put in the chat if anyone owns SAP, IBM, Lam Research. I think Jose, you like this one. Texas Instruments, another two important players in the semiconductor race, but Tesla and Meta are where all eyes are on, and that's what we're going to be looking for here after the bell. SPY actually had a good day. I mean, it was very low volume, but we ended green on SPY up .54. SpaceX had a good day. It was up about 7%. Tesla, good day. Pounder back above 200. So, overall price action today, not horrible in the context of some of these other tech companies. Um, I'm looking for those Meta numbers.
Yeah, they should be out literally in the next 30 seconds if not minute, and then we will get into it. I think the majority of people right here when I said who owns more Meta than Tesla, I feel like I saw a lot more Metas than Tesla. It is still a very large position, or these are two very large stocks that take up a large part of portfolios, especially given people, you know, bought Teslas so many years ago. So definitely will have some market moving events. I think implied volatility on both of these names is around 5 to 7%. So that's what you should be expecting up or down on these results. Meta, the numbers are definitely out because I'm seeing price action stocks.
Huge EPS miss, 44% miss. Called that. And then revenue beat by 2%. So instead of 63.4 billion in revenue, we got 64.6 billion. Revenue is up 26% year-over-year. In EPS, we got $3.83 versus $6.80 expected. Now, once again, the EPS miss is because of the 12 billion of tax legal expenses. So, that shouldn't be the craziest thing that the street's going to react to.
Yeah. Although it was a miss, it was very well... like this was expected. So, you're probably not even going to see a large reaction just off that.
As you can see, the stock...
Capex 145 billion. They did not increase 2026 capex. I don't have a 2027 guide.
Meta has established a new non-voting class share of common stock called Class C shares. No headline on how much they're going to dilute by or if they're going to announce it today. Revenue 64.6 versus 63. That's a beat. EPS missed by 40%. Operating margins 20%. Operating income was 12.9 versus 20 billion. That has to do with the legal expenses. Third quarter, Reality Labs revenue missed pretty badly as well. 443 versus 517. Again, small part of their business, but that is a miss. Operating loss was a little bit aggressive as well, 4.13 billion. Ad revenue 63.06 billion versus 61, so they definitely beat on the ad revenues. And then overall fourth quarter revenue 64.6 versus 63.3. Stock is up two and a half percent. They did approve the new Class C common stock that has non-voting...
Jose with another not listening claim.
Number... do we say that capex at least on the bottom range did increase for this year? Instead of 130, it's now 135. They increased about by five billion on the lower end.
There, okay.
Tesla, so third quarter Adjusted EPS 48 cents versus 44 cents. That is a beat. Adjusted revenue 28.05 versus 28.13. A slight miss on revenue. Gross margins 19.6 versus 17.8. That's a beat. EPS 22 cents versus 39 cents year-over-year. That is a miss. Well, that's a miss on the year-over-year growth, but overall miss on the adjusted EPS from expectations is correct. Gross margins again, that's a beat. Services 4.66 billion versus 4.3. Tesla basically flat. And then revenue 28.05 versus 28.13. So a very slight miss on revenue and then a 7% beat on EPS. And you're not seeing too much reaction from the stock right here. I'm looking through Meta's metrics right now. These are just insane. They did 10% more ad impressions year-over-year. How many more people did they add? Let's see. Like, but anyway...
You guys are saying... people are saying two-for-one stock split. I do not see that anywhere.
Cool. I also don't know why they would do it. No on Meta. Like why would they do a two-for-one? They would, if anything, it would be like three-to-one or five-to-one. I do not see that headline.
Well, hold on. I see what people are saying.
It's the new shares. It's... Okay, so Meta is creating a new class of non-voting capital stock. It declared a one-time stock dividend of one Class C share for each outstanding Class A, Class B, which works out to a two-for-one split.
Does that mean we're going to have... I actually don't know what that means. I don't know if that's internally or if that's affecting every shareholder. I genuinely, you guys, I have no idea.
Going back, I just want to say their daily active people metric went up 3% year-over-year while ad impressions went up 10% year-over-year, and then average price paid per ad is up 14% while also reducing headcount by 15%. I mean, this is a juggernaut of a business.
Yeah, that is... I mean, the fact that they keep finding more people is amazing. More people, charging them more ads, and no one's leaving. And the purchasers of those, like the companies, are happy to pay 14% more than last year on top of also doing more ads. Like those are two compounding curves at the same time.
And then the ads are getting better and better as well, like very entertaining ads, I would say, obviously AI-generated ones, but still keeps me watching.
Someone said bots. It can't be bots if the price per ad is going up.
Because the conversion has to be going up in order for the customers to, or for the businesses to be comfortable paying more.
Yeah. Like even if bots are clicking ads, if it's not leading to sales, companies aren't going to pay more to access those users. By the way, people are saying it's like Google and Google maybe. So, we're going to get a...
Another class of shares to trade on the stock market, but I don't know if that means if you have 100 shares, you're going to get 200 shares. Now, based on that split...
They're going to change the T and the A around.
It's going to be Meta and Meta P.
Pick it up. It spells... it spells meat. Sorry.
Oh, that was a good joke. If I picked it up...
That was... If I would have picked it up, it would have been good. Tanner...
Could go back to...
You know, that wouldn't be the worst thing either as well. Okay. Lam Research, that looks like it has some pretty decent numbers right here. Another semiconductor player, they beat on EPS 2.19 versus 2.18, revenue 8.2 versus 8.14. Jose, anything you're seeing here that is impressing you or still looking through it right now?
Still looking through it. One thing that I would want to see from, just like we saw from ASML, is the maintenance, the service charge has increased, has been a good revenue driver. I'm wondering if we're going to see the same thing from Lam Research. I'm pulling up their presentation right now. Stock is down 5%. Did we get 400 on Tesla?
Did we? Very close. 394. We're pulling up the slide deck on Tesla in the meantime. Let's get some more coverage on Meta, and then we'll get IBM as well.
That comes to 26% revenue growth for the quarter, ahead of the 24% expected. You see shares are just hovering on the flat right now. That is Meta's highest revenue ever for a quarter. Now the company also guiding to fourth quarter revenue of between 73 and 76 billion, the midpoint of that ahead of the consensus estimate. As for capex, Meta is raising the bottom end of its capex range from 130 billion to now between 135 and 145 billion this year. Meta reporting GAAP EPS of $3.83. That number is impacted by a nearly $10 billion previously announced settlement. The company says excluding that settlement, adjusted EPS would be $7.40. Now, another big piece of news here from Meta. The company's announcing plans to create a new class of non-voting capital stock, which will be distributed to all existing stockholders through a stock dividend, effectively a two-for-one stock split that will begin trading in late January. Now, as for 2027 guidance, the company saying, quote, 'Though we are not providing a full-year 2027 revenue outlook, the benefits our AI investments are delivering to the core business, combined with emerging opportunities from model advances and product launches, position us to sustain strong overall revenue growth throughout 2027.'
All right, we're going to have the Meta call in a bit. It sounded like what she's saying is people will get an additional share, but I think it also could be interpreted as just a different version of Meta. So, we'll get some clarity on that. But Meta is up 3% right here. IBM looks like we got a good quarter from them as well. IBM up 6% after hours. The stock fell 40% a few months ago. EPS 2.95 versus 2.86. Revenue 17.1 billion versus 16.8. Gross margins at 56.8%. So, you got a triple beat on Mr. IBM. Operating EPS was 2.95 versus 2.86 expected. Third quarter revenue 7.8 billion versus 7.64. Tesla still at 393. So Lam Research with a double beat, but that stock's down. IBM also with a double beat. That stock is up 6%. Meta 3.5, did touch 733, now back to 722. Not seeing much on the deck about Muse yet. I imagine that's what they'll be talking about on the call, but the numbers themselves outside of the legal expense, seems like the market is happy with it.
SAP. Wow. Go ahead, Jose, then we'll do SAP.
I was going to say regarding Lam Research, I was just looking through their numbers. Nothing looked crazy. I think the only thing is there wasn't much of a sequential growth on that service maintenance like we saw from ASML. I don't know if the market was expecting some of that to be a lot stronger. But you still did see on their equipment there was still strong growth year-over-year. So the only thing I could flag right now was kind of the service revenue for them.
Okay. SAP looking like they had a pretty strong quarter as well. Beat by 1% on EPS 2.12 versus 2.09. EPS up 15% year-over-year, revenue up 10% year-over-year. Revenue 11.53 billion versus 11.35 billion. Meta is not providing the full year 2027 revenue outlook. Yeah.
So, we're probably not going to get that on the call. By the way, Zucks...
Zuck said, 'Our investments are paying off. The core business is strong, and we're seeing velocity across the board.'
But why would they give us 27 outlook since it's Q3?
I think maybe they're preparing people that they're not going to give it at all.
Yeah. How did you guys read that? To me, it's that they don't know. Maybe I'm just a little too much into the AI space, but it's like they don't know how much money they're going to be making out of these Muse solutions and some of these new AI solutions that they can't honestly give us a strong projection on what they see for revenue.
I just don't... they gave us before in Q3 numbers for the next fiscal year. Most companies...
They actually stated it on their press release, Neil, that they don't want... they're not going to give it. They were like, we're not giving... and I thought it was weird too, Neil. Normally they don't share anything on quarter 3, but they still stated that on their press release that they weren't going to give fiscal year 2027 outlook.
Yeah, and maybe we'll get some capex guidance, but if not, then shareholders will have to wait. Okay, so Tesla, let's get deeper into that. I'm trying to go through the deck and see if there's any information here. IBM is pumping ServiceNow, Salesforce, all the SaaS names getting some love after hours because of SAP and IBM together. So that's actually helping a ton if you are in SaaS. Let's read a little bit from the Tesla Q3 summary. So in Q3, we maintain strong momentum on many projects spanning super intelligence, robotics, and renewable energy that will be critical to building a future of amazing abundance. Strength in our core business also continued, and we achieved our second consecutive quarter of revenue TTM in excess of a hundred billion. FSD attach rate continues to grow, reaching over 75% of new vehicles in North America, our most mature market, a nearly 20 percentage point sequential increase. We believe that FSD is driving demand in markets where it is available, and we continue to work with regulators to get it approved in other markets. Put in the chat if you pay for FSD. I'm curious how many people here actually pay for it. I mean, this is a pretty healthy increase. I know it's only a couple million people in North America, but it is growing pretty nicely. We started providing robo taxi rides using Cybercabs on September 3 in Austin. Cumulative unsupervised robo taxi miles grew eightfold Q over Q, driven by sustained double-digit weekly growth. We ended the quarter with the largest backlog for our passenger vehicle in over four years. Wow, it looks like the Model Y L pre-orders also are increasing the backlog for Tesla. We rolled out the updated Tesla Semi that is produced on our high volume manufacturing line in Nevada and unveiled the next-gen Roadster on October 15th. While battery availability continues to be the limiting factor in increasing order volumes of the quarter, we have made additional progress in securing future supply. Demand for our energy storage business remains strong in the quarter with our highest ever order rate and backlog. Energy storage is the fastest way to add power to the existing grid and is critical to data center uptime. We expect rising data center demand to continue driving demand for our products. Megafactory Texas began production with planned capacity of 50 gigawatts. We continue to invest in the future through R&D and capex spend across our business including AI, Robotics, and Energy. Much hard work lies ahead, but we are as optimistic as ever. Thank you to our supporters, and we continue to execute on many challenging and important projects.
Optimus. Optimus production began in Fremont on our high volume lines. The bots coming off this line are the first production quality bots that we have manufactured. While we continue to iterate on the hardware and manufacturing process, we have proven that the current manufacturing process for Optimus is suitable for a commercial product. Energy. We began producing energy at Texas. Energy storage demand is increasingly aligned with AI infrastructure. We achieved record quarterly deliveries in several markets for the automotive business including Canada, Australia, Japan, and Taiwan. Given the strong demand we are seeing across various markets, we remain focused on increasing production across our factories and attained record production at Gigafactory Berlin. I mean, margins went up for Tesla by 2% this Q. So, Tanner, any thoughts on what you heard from that? And maybe that's why the stock's getting some love after hours.
Yeah, I'm interested to hear about the Optimus. Their production lines that they're making. Are these robots just for internal use right now? Are they even, you know, remotely thinking about trying to find customers to buy these, or are they just making enough for prototypes? Like that I thought was an interesting comment that they are doing production lines for something that they don't really have a version of that they feel comfortable showcasing.
Yeah, it seems like on the call they're probably going to try to give some deeper updates on Optimus, but the updates might be that it just might take some time. Seems like a lot of people here pay for FSD, so...
I mean, it definitely has adoption.
It's really not that expensive. You're paying $100 a month for a full-time driver.
Seems like a pretty good deal. Farzot says, 'I don't see them selling to customers until 2028.' Yeah, you know, I think it's going to take a couple years, and that's being very optimistic. So, that's just something that people are going to have to wait for. But nonetheless, I mean, stock's the closest it's been to 400 since the last quarter when it fell to 297. So, I know it's only up 1.5%, but it doesn't look like anything on this earnings call or anything on this earnings print is necessarily bad numbers-wise. I mean, you do have year-over-year growth in the business. Well, revenue is down year-over-year, but by like 1%, so it's not that bad. Meta: Zuckerberg may relocate from California if Prop 40 passes.
He's definitely going to Miami. He's not coming to New York. The fact that Meta had to disclose that is interesting.
Maybe he moves the headquarters as well.
Yeah. Yeah. Austin's another big one, I think, as well, right?
Yeah. I take that back. It's actually Austin. He'll probably go to Austin. UFC. Joe Rogan.
Miami, I think, is the finance one. Or is it the other way around?
No. No, you're right. You're right. Interesting that they have to disclose that. Jose, Neil, any thoughts on these Tesla numbers, or it is what it is. Nothing too crazy from there.
Okay, Jose, any thoughts on Lam Research as this one continues to fall?
Yeah, no, I'm trying to get more information of what they missed on expectations here. And it's not like it was a crazily traded stock. I was just looking at their forward PE ratio. It's like 27 prior to this drop. So, I haven't seen this. I haven't gotten the slideshow yet. Prime numbers though don't look anything scary. And I mean, from the commentary you heard from TSMC, capex is expected to continue to increase. So, if I was a Lam Research shareholder, I wouldn't be worried just yet.
Okay, let's get some more coverage on Tesla here. Auto gross margins x zero emission vehicle credits, which basically that has almost gone away completely, 18.1%. The street was expecting gross auto margins of 16.8%. So much better than what the street was looking for. 1.74 million full self-driving subscription members. That's FSD subscriptions. 1.74 million is the total. That's up 67% year-over-year. For point of reference, it was 1.48 million at the end of Q2. Optimus production has begun, though they don't give any details in terms of how many robots have been built so far. And 2 million unsupervised miles for the robo taxi network. That includes Cybercab. The release does not go into specifics in terms of number of Cybercabs that have been deployed in Austin or around Texas that have been licensed. That certainly will be coming up during the conference call. And again, that starts at 5:30. And the main question, guys, we've said it all day long, ever since he said on the SpaceX conference call that he thinks it's a good idea for SpaceX and Tesla to merge. You can bet he will be asked about that coming up at 5:30, guys. Back to you, Phil. Thanks.
I don't get why he would have to answer that. Like he talked about it on SpaceX. How is his answer going to be different on the other side of the call?
You know, someone tweeted today that a big fan of Elon and Tesla, Hans, that if Elon proposed the 420 split, he would vote no immediately. And I was kind of surprised because, you know, he's been a big Tesla supporter, but he was just like, 'Nope, Tesla's worth more than 420. I would.' And notice what Elon said yesterday. It's not a certainty the merger happens, and we have to get at least 50% of the Tesla shareholder base, retail and institutional, to agree to a quote-unquote 420 price. So there will be debate over what that price is, and it might not be as easy as just whatever Elon recommends initially.
There have been a lot of people who've been holding for a very long time. They're going to feel jaded that they're, you know, maybe they held out on the SpaceX IPO or didn't buy in private rounds, and now you're not getting a premium on Tesla, and you have to pay quite the premium on SpaceX. It's just a lot. Like, I understand why they would feel jaded.
Okay. So I just put the part from Meta's PR about the two-for-one split, and I asked ChatGPT, 'What does this mean?' And she said, 'If you currently own 100 shares of Meta, here's what will happen. You will get 200 shares now. 100 will be Class A, 100 will be Class C.' For those that have owned Google for a long time, is that basically what happened? Like if you owned a thousand shares of Google, it became 500 GOOG and then 500 GOOGL with the L.
She... because if that... what'd you say?
I'm asking you what you said. Did you call it a she?
All right. No, no, go ahead.
It's a toaster. It's an it.
Okay. It's a piece of software.
Anyway, anyway, so it seems like that's what's happening. It seems like that's what's happening. So, there'll be 200. That will be a two-for-one split. And...
Can you ask your she if that's what happens with Google?
Make sure to put, 'Please don't be right. Don't be wrong. Give me right answers only.'
'I make no mistakes.' Thank you.
Mitch just calls it a she. So then whenever he's replying he's like, 'Girl, these numbers are crazy.' Yes, Google did almost exactly the same thing in 2014. In fact, Meta's proposed structure is remarkably similar to Google's. Wow. So, we're getting an extra share of Meta, folks. But does that... So, that's not going to change the stock price. That's not going from like 700 to 350. That's just going from, if you have 100 shares, 50 shares of this version of Meta and then 50 shares of that version of Meta. So it's not... I don't know, it's not really...
But even that doesn't make sense. So like if I get equally split, then what my voting shares were before become non-voting shares? That doesn't make sense. How does this work?
Your voting shares still stay voting shares, just the other ticker has no voting power.
Right. But I don't get split into that.
I don't know. It's the stock going up. That's the only thing that matters. Yeah, it's a little... I think they'll clarify on the call, but it feels like it's very similar to... that just wasn't around. No, it doesn't have to change the stock price though, right? Because if you have 100 shares, you just get 50 of the same price of a different class. Just like if you had a hundred of the same class.
But isn't that not what happened with Google? With Google, if you had 100, you got a hundred of both, right?
Oh, no, no, you're right. You're right. I'm dividing by two. You're multiplying. Yeah. So, then it has to change the stock price then, right? It's half. Yeah. Yeah. You're right. So, this thing's going to 350.
I mean, it'll be easier. Chat, want to chime in here.
Someone's saying no, it's 700.
Girl, what is going on? And then...
Never mind. Go ahead. Continue.
So, let's say we've got 100 shares of Meta. I get 100 shares, and they both become 350 or whatever the price is.
I don't know, bro. This is confusing. I feel like it's so simple. But...
Can we call an investor, please?
Can we get an investor on this call?
Jeez, I've never felt stupider.
Everyone's disagreeing. Everyone's disagreeing with each other in the chat, too. So, it's not like there's a consensus here.
Wait, let me just... Okay, let's look at IBM, and then let me ask ChatGPT some more about this.
Just 6% now, up about four. It's a beat on the top and bottom lines for Q3. Revenue came in at 17.1 billion versus 16.82 billion expected. EPS was at $2.95 adjusted versus $2.86 expected. If there's one nit to pick here, it's probably operating gross margin. Consulting strength hurts because software and infrastructure are more profitable. Pre-tax operating margin actually grew for them. But software and infrastructure did both beat expectations. That's going to be a big part of the reason for excitement here. Software is the star because you might remember that there was a pre-announce, a hiccup last quarter. Red Hat, which is usually a standout in the software segment, stumbled. In Q3, we're seeing a big comeback here with IBM closing two-thirds of the deals that had been lagging. Now, free cash flow guide here from IBM was raised to more than a billion from about a billion before, but the fiscal year 2026 revenue guide is maintained at 4 to 5%. Now, I did speak to CEO Arvind Krishna about several things including the guidance. He told me, 'I want to give numbers on which we have extremely high confidence and not lean in because we've got to rebuild credibility is the way I would put it.' Referring to last quarter on software, he said, 'Last time was minus 7. This time is plus 10. Let's even it out to flat to slight growth.' So on Red Hat, he went on to say, 'We are pretty comfortable leaning in and saying that we expect double-digit performance to continue.' That should...
So that's helping all the software stocks after hours as IBM continues to be green. I asked ChatGPT. I understand too now.
Well, this is what I initially said, and then you guys said no. But that's what it is. It's 350 a share.
Yeah, but okay. But that part doesn't matter. This is the important part that got me confused. Your voting share of the 350, it will get cut in half, but the voting share of the 350 is not going to change, and it's not going to impact your ability to vote for the company, and it won't change the outstanding percentage of the voting pie. You know, your percentage of ownership stays the same. Your percentage of ownership of voting shares stays the same. It's just half the shares won't matter, and you're only going to vote from the other half.
And then you're going to get higher... which ones you want to sell. So it's... so we all get double the amount of shares now. We can all run more...
At half... Well, yeah, basically. And theoretically, he could run more calls. But Zuck is not doing this out of like a... the stock's too high.
Yeah. He's not doing it to like do a seven-for-one, 10-for-one split. Usually he's doing it to dilute. I mean, that's the real takeaway from this. It's just a question of when they're going to announce that dilution because you have to increase... if you're going to dilute, you need to make sure your voting class share stays the same so he doesn't lose control, but that there's physically more shares that are out there to sell to the public.
Yeah. And so it seems like that's the point of all this as well.
He wants to raise, but he still wants to hold the scepter. He doesn't want people coming in to be able to change the vote. He's still king.
The annoying part about that is, and I know the stock's up after hours and maybe Zuck pumps it some more, but inevitably they're not doing this if they were not going to dilute. Like it literally makes no sense for them to do this without a plan to offer more equity to the public. So at some point, either in the next couple of weeks or maybe they do it in 2027, there will be an equity raise like Google did. Now Google did 85 billion. The question is how much is Meta willing to do it? Maybe it pumps to 800 by December and that's when they do it. But it looks like it will happen now.
We have the call in about a minute on Tesla. We did not get to 400. That call is 392. That call will be at 530.
Yeah. This inherently is not dilutive. It's what comes after this. They're setting the stage for future dilutions because they realize that they're going to have to raise a bunch and they don't want to change
who owns the voting share, which is Zuck.
Yeah, we didn't get a lot of information on Capex or Muse, so I think that's what the call will focus on and maybe that could send the stock even higher, but
Tanner, they want to dilute the non-voting shares. That's the one that they're going to now. They have the upright. They're splitting it up. So then later on they can be like, this is the one we want to dilute so I can still hold the crown.
And I mean you got to ask yourself, do you care about holding Google L or Google or GG?
I don't think many people care. And I don't think that, like, without looking at it, could you tell me which one has the voting shares?
No. I have no idea. I have no idea.
You know, and sometimes you can get ever so slightly in arbitrage on Google because it doesn't have that voting share and some institutions might care.
Palantir just announced they're expanding their sovereign AI deployments with Nvidia, L3 Harris, and just now. So, you got that headline right here. After hours.
Okay, the call is still not live yet. Should be getting started very soon. So, we'll have Meta for the next hour. Then, we'll have Tesla. Again, I think the big thing for everyone is, you know, the market is not upset at these earnings even with the big miss. The market knew it was kind of going to happen. Muse capex. I mean, he's probably going to get some questions on the equity raise, but he'll probably won't give an official answer. If the call can go well, this thing probably holds, you know, the 4% move. And if it dumps, then it's got to be something he says that the street's just not going to be happy about, but it is up. Bloom is also up after hours. And then Lam Research, as Jose said, looks like the services revenue was down, which is why that thing is taking a 6% hit right now.
Okay. Meta's still not live yet.
The call's on. Zuck's on.
Do you have it on your side? You want to share it?
and engagement on both Facebook and Instagram driven by strong growth in video. Threads has now overtaken X in monthly actives and continues to grow quickly. WhatsApp is hitting all-time highs in messaging and is becoming an increasingly important platform for agents as well. In the last few months, we have had several major milestones towards our goal of delivering personal super intelligence to everyone. We had one of our most successful launches ever with the Muse personal agent. We shipped Museful
launches ever with the Muse personal agent. We shipped Muse Wonder as our first frontier model and we shipped several new glasses and gadgets with Muse integration, including coming soon to our new audio glasses.
We've been discussing our vision for personal super intelligence for more than a year now. We want to help every person have an extremely capable personal agent that understands your goals and can help you achieve them and improve your life in whatever ways you want. Whether that's improving your relationships, helping you save time, save money, build a business, create new things, or anything else that you can dream of. Muse is the product form of this vision. So now we have the foundational technology in place to deliver this. There is still a lot of work ahead, but our initial position is very strong. In just a month and a half, more than 10 million people in the US and Canada have set up Muse Personal Agents. Growth continues to be strong, and we have been number one in the app store almost every day. Engagement and retention are also off to a strong start. About 25% of people who have set up Muse use it on any given day. For our earliest adopters, the longer that they use Muse, the better that retention seems to get. So to put this in perspective, this is more than twice the level that Threads started at, or where we believe that other AI apps started at as well. The most common use case for Muse is shopping. With more than a quarter of people who are using Muse engaging in this with an average purchase size of over $200,
Plaid told us that they hadn't seen activity like they're seeing with their connector on any other service before. And in the first week, we had to work with Stripe to raise credit limits since the volumes were above what any of us expected. Beyond shopping, the most common connectors are for personal productivity and connecting Muse to your other services like email and calendar. Now, this shows the importance of the Muse Secure VM that we've built to provide state-of-the-art privacy and security, and we are looking forward to following up soon with the Muse confidential VM, which will make it so that even Meta cannot see your content. We've also seen that Muse Wonder improves quality, engagement, and retention further, which suggests that as we continue to improve intelligence, Muse will perform better and better over time.
Now that Muse has clear product market fit, we are entering a new phase and a more operational phase that is focused on scaling it. The goals for this next phase play to many of Meta's strengths. We need to do three things. Scale the product, grow revenue, and optimize compute costs.
We expect to grow Muse to serve billions of people. This is both our mission and our strategy. It's our mission in that we believe in putting the power of personal super intelligence in everyone's hands. We believe that that is the path to ensuring a positive future for everyone with individual empowerment as the source of prosperity and balance of power as the foundation for safety. On a values level, we believe that delivering this capability widely is the best thing that we can be doing.
This is also our strategy because we think that billions of Muses in a network at scale will be able to get more done for people and businesses by working together. So, we'd like to create a large-scale Muse network as quickly as possible. From a business perspective, the average revenue per American user for our existing family of apps users is several hundreds of dollars annually. And we expect that Muse will reach an even higher level over time due to the amount of commerce that we already see taking place. This will take some time, but we're starting to work on this now. Our business model will have a few components. For most people the product should be free and we will build commerce tools. So we get paid a fee based on the transactions that we help facilitate. We expect this will be paid for by businesses. For people who want the most advanced models or to use extra tokens, they subscribe directly and pay. For business owners who want additional features to use Muse to grow their businesses or for companies that want people to use Muse for work, they will be able to subscribe directly and pay as well. And for those who want Muse to help improve the personalization and quality of their content and ads across Meta, they will be able to connect to those experiences as well. Just to clarify, the average revenue that I was talking about before is the family of apps revenue for our existing Muse users.
On the compute side, we are building out the capacity to serve more than a billion people over the next few years. In the near term, Muse is very compute intensive to run, but we expect to improve its cost efficiency by more than 10x in the next year which will enable it to be profitable once the revenue lines are at scale. If compute efficiency continues improving quickly for another few years, which we think is highly likely, then Muse will be highly profitable over multiple years. In the near term the strength of our core business enables us to scale the Muse network before then and we believe that we are the best positioned company to pursue this strategy.
One other note on compute economics is that since training is a large fixed cost, now that we have leading models we want to serve as much high margin inference demand as possible. That is why we are building the Meta enterprise platform led by CJ Desai. Muse Wonder and even more advanced models that we're training can serve additional high margin services beyond the Muse network including our API, Muse Code, and other enterprise services.
A fundamental feature of our business is that we have many good uses for this compute. It is difficult to forecast the exact growth rates for the Muse network, for our enterprise platform, and for how Muse Wonder and beyond will accelerate our core business. But through building up multiple ways to deploy these advanced models, we increase the chances that one or more of them significantly outperforms our expectations.
Beyond serving other businesses, we have not yet found the limit of how effectively we can apply compute to accelerating our own core business. We have implemented an eval with Muse Wonder to improve how effectively it can autonomously improve our recommendations and ad systems. And as our upcoming models get even more advanced, I expect that we're going to see an increasing rate of improvement in these systems.
All right, let's talk about the models now. Muse Wonder is state-of-the-art across many dimensions that matter for personal super intelligence. This validates the importance of training models ourselves to deliver the best experience. In addition to Muse, we have also seen that engagement per person in Meta AI has more than doubled since April when we started rolling out our new models. While Muse Wonder has been our most important release, I've been very pleased with our pace of execution here. In the last few months, we've shipped Muse Spark 1.2 and 1.3, Muse Code, two open weights models with Muse Glimmer and Muse Spark Open, and also Muse Voice.
Going forward with the field advancing quickly, we plan to focus on both pushing the frontier of intelligence and distilling those models into much smaller and more efficient product models that will be optimized for personal agents. My view is that we will be able to build super intelligence through scaling. So we are methodically working our way up the ladder there. We are already working on larger models after Muse Wonder and they're going to be very impressive and capable. We are also working on new smaller models that are coming out soon that will deliver Muse Wonder-level intelligence more efficiently.
Moving on, our work on personal super intelligence is now also the focus of Reality Labs. Muse is coming to Meta glasses starting next month and that will be an important step towards this. People already love many features of the glasses already, music, calling, capturing moments, hearing assistance, and more, but over time, we expect Muse and having your personal super intelligence with you throughout the day will be the most important part of the experience.
Muse is also central to the business model for the glasses. Again, our mission and strategy are to serve everyone here. We believe in putting the power of this technology in everyone's hands. So we have priced our devices not to make a large profit on the hardware but to build a large software and super intelligence business on top of them over time. Glasses sales continue to grow rapidly. And now with Muse, we expect that paid subscriptions will increase and that this business will begin improving meaningfully from here.
I also shared at Connect that we are changing our approach to virtual reality to only ship new devices when we have major breakthroughs like we had with the Meta VR glasses this year which of course are the first VR experience ever in a pair of glasses. I continue to believe that the path to delivering holographic experience of bringing together the physical and digital worlds in everyday glasses will come through VR first. But we will pace this aspect of our investment more to focus on delivering personal super intelligence first. So with these factors combined, we expect that the P&L of Reality Labs to improve from here with operating loss coming down to around 15 billion next year and trending towards profitability from there. Before we conclude, I want to spend a moment on the sheer velocity that we are seeing. An important part of our approach has always been to move fast so we can learn quickly and serve people better at scale. But recently things have accelerated. In the last year, we shipped Edits and it has already passed 50 million actives. New apps like Forum and Seller were built by small teams and are scaling quickly to serve power users. Muse went from an idea on a whiteboard to a successful product in just about eight months. And we're about to ship Muse Charm, which will have gone from concept to a hardware device in people's pockets in less than a year. I am proud of what we are building. People have all kinds of different opinions about the future, but at Meta, we believe that the future is for everyone and that putting power in people's hands is how we get there. I think that this matters. There needs to be a company out there that represents these ideas. But this isn't just about ideas. It's also about execution. So, I am grateful for everyone who is working so hard to deliver all of this to billions of people around the world. And as always, thank you to everyone who is on this journey with us. And now, here's Susan.
Thanks, Mark, and good afternoon, everyone. Let's begin with our segment results. All comparisons are on a year-over-year basis unless otherwise noted. Q3 total family of apps revenue was $64.22 billion up 26%. Q3 family of apps ad revenue was $63.1 billion up 26% on both a reported and constant currency basis. In Q3 the total number of ad impressions served across our services increased 10%
load optimizations. The global average price per ad increased 14% year-over-year, driven by ad performance gains and improvements in macro conditions relative to Q3 of last year. This was partially offset by strong impression growth, particularly from lower monetizing surfaces and regions.
Family of Apps other revenue was $1.1 billion and grew 59% driven primarily by WhatsApp paid messaging and subscriptions revenue. Within our Reality Labs segment, Q3 revenue was $443 million, down 6% due to lower Quest headset sales, which were partially offset by continued strong growth in AI glasses revenue.
Moving now to our consolidated results. Q3 total revenue was $64.6 billion, up 26% on both a reported and constant currency basis. Q3 total expenses were $51.6 billion, up 68% compared to last year, and included a $9.9 billion charge related to the August 2026 multi-state attorneys general agreement. Year-over-year growth was primarily driven by legal related costs, infrastructure costs, and third-party AI token costs. The growth in infrastructure costs was driven by higher third-party cloud spend, depreciation, and data center operating costs.
We ended Q3 with over 66,000 employees, down 12% from Q2 following the May 2026 headcount reduction. Third quarter GAAP operating income was $13 billion, representing a 37% decline year-over-year and a 20% operating margin. Excluding the Q3 legal charges related to the aforementioned legal settlement, our third quarter operating income would have increased 11% year-over-year. Our tax rate for the quarter was 24% above our outlook range, primarily driven by the non-deductible portion of legal expenses. Net income was $9.9 billion or $3.83 per share. Capital expenditures, including principal payments on finance leases, were $34.9 billion, driven by investments in servers, data centers, and network infrastructure. Free cash flow was -$2.1 billion. We ended the quarter with $82.4 billion in cash and marketable securities and $83.7 billion in debt.
Turning now to the business performance, there are two primary factors that drive our revenue performance. Our ability to deliver engaging experiences for our community and our effectiveness at monetizing that engagement over time. On the first, we continue to see significant gains from our content recommendation initiatives.
On Instagram, global time spent per user reached an all-time high and grew double digits year-over-year in Q3 with strength across both Reels and feed. On Facebook, Reels time spent reached all-time highs both globally and in the US with both growing double digits year-over-year. Threads also continued to scale with time spent per user growing over 20% year-over-year. Engagement gains across our services continue to be driven by improvements we're making to the relevance, personalization, and timeliness of the content we recommend.
Investments into our recommendations engine across retrieval and ranking have continued to yield positive results on Instagram and Facebook. For instance, on Instagram Reels, our relevance launches in Q3 increased Reels time spent by over 4%, driven in part by our upgraded model architecture that ranks sequences of Reels at a time instead of evaluating each reel independently as well as improvements we made to add richer watch time signals.
On Facebook feed and Reels, we completed the global launch of a new generative retrieval architecture which, inspired by LLMs, labels pieces of content with semantic representations and generates potential recommendations helping our systems surface relevant new posts before they've accumulated significant engagement. This new architecture is now rolled out to roughly one quarter of unconnected feed views and half of Reels views and increased Reels watch time by 1%. Our recommendations work is also helping us deliver fresher and more personalized content. Nearly 45% of recommended Instagram Reels are now less than 1 day old, up more than 11 percentage points from Q2. On Facebook Reels, we doubled the amount of history our ranking model can consider, driving a 1% increase in Reels watch time in the US.
LLMs are also helping us understand content more deeply. We continue to process public Instagram posts each day through LLM-based content understanding systems. These signals have improved the engagement with Instagram search results by 1% through the end of this quarter. This quarter we also began moving our content understanding models onto our first-party Muse model family. In offline evaluations, these models are outperforming our prior production models and are reducing per unit content processing costs by more than 80% across Instagram, Threads, Facebook, and ads. Beyond improving quality, owning more of this stack gives us greater flexibility to develop models around the signals that matter the most for personalization.
Turning to the second driver of our revenue performance, increasing monetization efficiency. We see significant opportunity to continue improving performance for the businesses who use our services within our ad systems. We are continuing to drive performance gains as we deploy more predictive models that understand users more deeply and deliver ad experiences better aligned with their unique preferences while also making our infrastructure more efficient.
Last quarter we introduced Meta generative recommender which uses LLM to reason across ad content and user preferences to predict the best ad for each person. In Q3, we launched this approach to generative retrieval on Facebook feed, driving a nearly 2% increase in conversions across targeted segments. In addition, we expanded our GEM model for ads ranking to additional services surfaces, driving a 1.7% increase in conversions for off-site conversion campaigns and a 9.6% increase in app ad conversions. And we continue to scale our retrieval systems efficiently. In Q3, improvements to Andromeda, such as scaling model complexity and throughput, increased conversions by 1.4% on Facebook.
We're also leveraging AI to make it easier for businesses to manage campaigns, develop creative, and act on performance opportunities. Meta AI Business Assistant is becoming a more proactive and capable partner for advertisers. We estimate that advertisers who adopted its recommendations drove almost 5% more conversions at the same cost per conversion and increased their advertising investment by 9% compared with similar non-adopters. We are rolling out additional capabilities including creative insights, stronger business context, and more agentic actions.
These features will allow marketers to plan, create, and optimize campaigns as well as schedule tasks and alerts through a conversational experience with approvals and previews that keep them in control.
I'll share one example of how Meta AI Business Assistant is empowering our advertisers. Simply Organic Maple, a family-run maple syrup producer in Vermont, used Meta AI Business Assistant to improve its campaign messaging. After the business assistant recommended testing longer, more descriptive advertising copy, the business saw a 57% increase in purchases and a 36% reduction in cost per purchase. Its strongest revised ad delivered a 3x return on ad spend, a 52% improvement from the original.
Adoption of our generative AI ad creative tools also continues to scale. In Q3, nearly 10 million advertisers used at least one of these tools. Advertiser adoption of our video generation features grew 25% quarter-over-quarter, driven in part by ready-made videos that reduce generation time to just a few seconds from a single image upload. We're also expanding the opportunity at the intersection of creators and advertising. Partnership ads, which allow advertisers to run ads with creators, brands, and other businesses, continued to scale rapidly in Q3. Our partnership ads product grew over 97% year-over-year and surpassed $15 billion in annual revenue run rate.
In Q3, we also completed the global rollout of Creator Marketing Hub to all advertisers, bringing creator discovery, content organization, and partnership ad activation into one place. With more than 10 million creators now discoverable, we are integrating Meta AI Business Assistant into the hub so advertisers can conversationally search for creators, identify content to use in partnership ads, and get guidance across their creator marketing workflows.
Outside of ads, we are also building out additional ways to monetize engagement across our ecosystem. In September, we announced the global expansion of Meta 1, our unified subscription service for consumers, creators, and businesses. Meta 1 is rolling out gradually with more than 50 features across Instagram, Facebook, and WhatsApp, including Meta Business Agent and Meta AI, and has surpassed 15 million subscriptions and trials to date. The core experience across our apps and Meta will remain free, while subscriptions offer more specialized capabilities and expanded AI usage. And beyond monetizing engagement across our existing services, we are building new experiences and revenue streams around consumer agents. Mark highlighted the impressive early momentum with Muse. Users have found many reasons to use Muse with the top three categories being shopping, personal productivity, and creativity. We're encouraged by the breadth of use cases with shopping in particular being used by over 25% of Muse weekly actives.
While our near-term priority is to grow adoption and expand Muse's reach, we see multiple paths to monetization beginning with subscriptions. We also see a significant opportunity to extend Muse to small businesses. Based on a recent user survey, we estimate that at least 500 million self-identified small businesses use Meta's family of apps to reach customers and generate revenue. Muse could help these businesses acquire customers and operate more efficiently while helping people complete transactions. Over time, consumer and business agents could connect and transact directly, creating opportunities around paid usage, commerce, and business services.
Alongside growth, we are focused on building sustainable unit economics. Muse's computing intensity means that expanding its user base will require significant investment and we expect total serving costs to rise. At the same time, we expect to improve compute efficiency over the next year driven by better utilization of off-peak capacity, more efficient models and inference optimization. As revenue scales, these efficiency gains give us confidence in our ability to build a highly profitable business over time.
Moving now to our financial outlook, we expect fourth quarter 2026 total revenue to be in the range of 73 to 76 billion. Our guidance assumes foreign currency is an approximately 1% headwind to year-over-year total revenue growth based on current exchange rates. Turning to the expense and capex outlooks, we are raising our expense outlook to incorporate the $9.9 billion charge related to legal proceedings recognized in Q3. We now expect full year 2026 total expenses to be in the range of 175 to 179 billion.
Excluding the Q3 legal charge, we continue to expect 2026 operating income to be above 2025 operating income. At a segment level, we now expect Reality Labs losses to decline compared to 2025 to a range of 18 to 19 billion. We anticipate 2026 capital expenditures, including principal payments on finance leases, to be in the range of 135 to 145 billion, narrowed from our prior outlook of 130 to 145 billion. Absent any changes to our tax landscape, we expect our fourth quarter 2026 tax rate to be between 15 and 17%.
Additionally, we continue to monitor active legal and regulatory matters that could significantly impact our business and financial results. For example, we continue to see scrutiny on youth related issues in several markets and have a number of youth related trials scheduled in the coming months in the United States. Looking beyond 2026, we are still developing our budget and capacity plans for next year, but we expect to continue investing aggressively to support both our core business and emerging AI initiatives.
Our current capacity and what is scheduled to come online gives us the flexibility to allocate resources across model training, core business growth, and the development and support of new products. Our AI investments are already delivering substantial incremental advertising revenue through stronger engagement, better recommendations, and more efficient monetization. Building on this progress, our MSL investments are creating the technology and infrastructure needed to unlock significant new revenue opportunities and strengthen capabilities across the business. While these investments will take longer to generate returns than those in our core business, the breadth of monetization opportunities and internal efficiencies gives us confidence in their long-term potential.
Looking ahead, although we are not providing a full-year 2027 revenue outlook, the benefits our AI investments are delivering to the core business combined with emerging opportunities from model advances and product launches position us to sustain strong overall revenue growth throughout 2027.
Separately, we remain focused on improving Reality Labs profitability. As Mark mentioned, we expect losses to narrow next year to around $15 billion as we reallocate investment towards other priority areas, primarily AI.
Finally, today we announced plans to create a new class of non-voting capital stock, which will be distributed to all existing shareholders through a stock dividend. For each existing share held, stockholders will receive one share of the new non-voting stock, effectively resulting in a two-for-one stock split. We expect trading to begin in late January 2027.
In closing, our business momentum continued in Q3 with strong execution across our core ads and engagement initiatives. And we're also excited by our progress towards bringing personal super intelligence to everyone. With that, Christa, let's open up the call for questions.
Thank you. We will now open the lines for question and answer session. To ask a question, please press star one on your touchtone phone. To withdraw your question, you may press star one again. Please limit yourself to one question. Please pick up your handset before asking your question to ensure clarity. If you are streaming today's call, please mute your computer speakers. And your first question comes from the line of Brian Nowak with Morgan Stanley. Please go ahead.
Thanks for taking my questions. I have two, one on Muse, one on Enterprise. Maybe first, congrats on the success of Muse. But as you analyze the user behavior in the product, can you talk with us a little bit about any of the constraints to the slope of forward user growth that you're most focused on addressing, whether it's capabilities, model efficiency, capacity, etc., just so we understand what are the limiting factors to forward user growth that you want to address. And the second one is on enterprise. Mark, can you just sort of walk us through your vision for the Meta enterprise product offering and the key value drivers you hope to provide for the enterprises adopting the service?
Yeah, I think I can talk about both of those. And then Susan can jump in with anything else. All right, so right now for Muse, we are, and one of the things I pointed out is, you know, we have more than 10 million people in the US and Canada who have set it up, but I think one of the biggest constraints so far is that because this is a compute-intensive service to run, we have not launched it globally yet. That's partially because of wanting to optimize it for each place and there's some workaround connectors for that, but it's partially that we want to make sure that we do this efficiently. So I mean there's pros and cons there. The pro of course is that that just makes it even more impressive that you have 10 million people using it and signing up to use it in the first six weeks because those are all kind of Americans and Canadians in a small number of markets. So if we actually did roll it out more broadly then you would expect that number to be significantly larger than what we're seeing today. But then on the flip side, we actually have to go do the work to bring the efficiency in line to make that make sense. And so that's a big part of it that we need to do. The compute efficiency work is going to be important on this also because, you know, we want to make sure that we've built enough compute to be able to serve what we think is going to be a billion plus people if we can achieve certain compute efficiency targets, but we obviously have a lot of work to do there as well and that'll be one of the limiting factors over the next year. We want to build out the business around it, so I mean I talked about that and I think doing that in tandem with bringing down the compute or increasing the compute efficiency is going to be important for getting this to work from a business perspective, which I'm optimistic about, but I think that that's one of the things that we need to do. And then there's just continuing to increase the value in the product, which I think we will largely do by continuing to develop new models. That's why I mentioned that, you know, we launched Muse first on Muse Spark and that's what is currently the default across the free tier, and we rolled out Muse Wonder and people can access that in the paid tier today. And we know that it performs a lot better. We're working on getting a more efficient version of Muse Wonder that we'll be able to roll out more broadly. But you can imagine just as we iterate forward and, you know, two, three models into the future when you have significantly higher intelligence and capability to solve many more problems for people and the ability to deliver that at a much more affordable price point, I think that that's going to just unlock a lot more value to people. So we're very excited about that.
Transitioning, talking about the enterprise piece, because I think that these two pieces are, there is some connection here in that, you know, the main enterprise offering in the near term is going to be the model API and Muse Code, and we have business agents that we've been scaling for a while and each of those three things is growing quite quickly. So we're excited about that. Over time we would like to make it so that we have a whole kind of business network of Muse agents as well. And there's the business agent which we've talked about on previous earnings calls for businesses to help out with sales and customer support. But what we see is a lot of people are actually using Muse today to help run especially small businesses. And we think that there's both an opportunity to help create an agent that people use to really enable them to automate and do a lot of the parts of spinning up a small business that are just kind of difficult and time consuming but aren't the core thing that a person is trying to do. So we think that's a big deal and then making a version of Muse that people can bring into different corporate environments and work there we think is going to be a big deal. And then beyond that, building what I refer to as the Muse network, which is making it so that Muse is not just a kind of single-player game where you have your Muse, but making it so that your Muses can work with your friends and your families and if you want to buy something, it's not just navigating to that business's website. It's talking to their agent. I think that getting that all to work well together is going to unlock tremendous value at scale. So I'm very excited about all of that. I think the enterprise use is going to be a big part of it, but it's also going to kind of have this very valuable boost in the utility for consumers, too. So I'm very excited about both of those.
I would add on to Mark's comments on enterprise. AI is creating huge amounts of disruption in enterprise today. And, you know, from what we can see, we really don't believe that traditional enterprise companies have this locked down. In fact, you know, some of the leading companies in this space today didn't exist a few years ago. Those companies made large investments in model development and we've done the same and we have increasingly competitive models to bring to bear for the benefit of all of our users, including small businesses and including enterprises. And already today, we have 500 million businesses using our product. So, we really believe that AI is going to reshape how businesses operate. We expect that businesses of all sizes are going to use AI agents across software development and productivity, sales, marketing, consumer, customer service, etc. We have differentiated assets to serve this market, bringing together models, infrastructure, global distribution, and long-standing relationships with businesses. And it's our hope that this will be able to be a new diversified recurring revenue stream for us that will be able to support multiple business models including subscriptions and usage-based API and messaging and other revenue lines. So we expect that this will be an opportunity that will develop over multiple years and we intend to scale our investment behind demonstrated customer demand and product market fit in this area.
Your next question comes from the line of Eric Sheridan with Goldman Sachs. Please go ahead.
Thanks so much for taking the questions. Maybe just the first one building on Brian's question. When you think about the friction points around agentic commerce, how do you guys as a company think about solving for friction that's rising where there are aggregators or suppliers that don't want agents to interact with their platforms or their services? And how you think about lowering that friction or creating the right balance between the existing services that consumers access today relative to how this might all be changed or altered by agentic behavior over the medium to long term. And the second one would be with the announcement of the new class of shares tonight with earnings, any updated thoughts broadly about how you think about sources of capital and optimizing your capital structure to make sure you invest the proper amounts to capitalize on the opportunities that AI are presenting in the next couple of years. Thanks so much.
I can answer the first one. So okay, so the question, sorry, what was the first question there?
Friction points around agent commerce.
Got it. All right. Yeah, so right now what we're seeing is that overwhelmingly businesses are very excited about enabling this because they recognize that it's going to be a new opportunity for them not only to increase the sales and the quality of the experience for existing customers but also potentially to bring in new customers. So now I mean across the whole business ecosystem different people will kind of adopt this at different paces and how our strategy evolves on that to develop the ecosystem will depend on how that goes. But overall, I would say we've been very positively surprised by how quickly I think a huge amount of businesses have wanted to, you know, not only figure out how to make it so that Muse can use their services more effectively, but have reached out to us to integrate around it. So I view that as a very good sign and, you know, obviously not everyone wants to be an early adopter. That's fine. We'll work with folks on the terms that make sense for them. But I do think that over time this is going to be quite valuable for everyone to make this work well and I think we're on a good trajectory on that so far.
Yeah, I would add to that and I will also answer your second question and just say, you know, I think agents are going to be an important part of, you know, how reality evolves and I think everyone is going to have to adapt to what that means, the new age of agentic commerce. We obviously have had a lot of businesses who are very excited to partner with us. There are also businesses that are understandably focused on protecting customer relationships and we expect the market, you know, I think ultimately to evolve away from agents attempting to navigate every digital experience like a human and I think over the long run this will move towards more permissioned structured interactions and that will include authenticated APIs, approved agent partnerships or direct communications between a consumer's personal agent and a business's own agent.
And we're helping establish the standards needed to support that model. Earlier this month, we previewed the personal agent protocol, an open standard across Muse and Meta business agents that we are developing with industry partners like Sierra, Walmart, Stripe, Shopify, etc. The protocol is intended to define how a consumer's personal agent can interact securely and reliably with the business's agent and preserve appropriate controls for both the business and customer. So again, you know, I think adoption will likely be uneven and will take time and in the near term, we expect many experiences will remain AI-assisted rather than fully autonomous. But, you know, as trusted integrations develop and agents demonstrate that they can generate incremental value and demand and operate safely, we expect that more
and more businesses will be excited to participate. Your second question was about the announcement of the new class of shares. So I should say, you know, we created this new class of shares with the purpose of creating a publicly traded non-voting stock usable for, you know, capital raising, employee compensation, acquisitions, other general corporate purposes, while preserving the voting power of existing Class A and B shareholders.
We believe the share class will maintain our founder-led structure. It will expand our funding tools and give us flexibility to invest behind the unprecedented momentum we're seeing across every part of our business, driven by AI. We don't have any specific financing plans to announce at this time, but we thought it was prudent to establish the appropriate capital structure framework to ensure that we have access to a diverse pool of funding sources.
Your next question comes from the line of Doug and Moose with JP Morgan. Please go ahead.
Great. Thanks for taking the questions. I have two. First, just wanted to follow up on your last comment, Susan, just around as Muse evolves and more businesses adopt agents. Just wanted to get your sense of how things kind of change and shift as you go to more permission-based and agent-to-agent transactions, and like what does that really unlock over time? And then secondly, just on kind of expenses and capex, thinking about '27. I know you're not really there yet, but if I go back to some previous comments, you've talked about maximizing compute in '26 and '27, and then having more flexibility in '28. A year ago you talked about kind of notably larger dollar increase in '26 than '25, and then you've also used kind of growing operating income on an annual basis as well. So just curious if there's any of those that you can kind of tie or to help us think about '27. Thanks.
Thanks, Doug. So on your first question about how the agentic ecosystem evolves, you know, I wish I could sort of predict that more perfectly. You know, and I think it will take some time, and again, I think it will be a little uneven. But I definitely think that, you know, when I use Muse today, it's clear that there are a lot of parts of the experience that would be even better if Muse was able to interact more seamlessly with business agents on the other side. For example, when, you know, if Muse has to call a business on my behalf, I think it would be easier for the business if that call was handled by business agents that were representing it. And I think also one of the things that is really distinctive about Muse, and one of the things that makes the product experience so great, is the degree of proactivity that it exhibits on my behalf. Right? I can give it a task, and Muse is going to go execute against that task for me, even as it encounters some obstacles or, you know, can't quite find the right thing and needs to chart a new path to helping me look for the thing I want. And so I think that sort of dimension of proactivity exhibited by either consumer agents or business agents, I think, are going to enable more transactions to happen or more activity to happen broadly than happens today, where, you know, when things are, when more actions are taken primarily, you know, when like the latent demand expresses itself versus, you know, things where I can have Muse searching for things for me on an ongoing basis, giving me regular updates, you know, on things I'm looking for, sending me 10 new books a month, and agents should be doing similar things for businesses. And I think that creates sort of opportunities again for a new, more proactive sort of framework for what agent-to-agent interactions look like over time.
On your second question, which is about 2027, you know, we are quite early in developing our budget and capacity plans for next year. So, you know, we are, I would say, at the point where we are both investing, sorry, evaluating a lot of investment proposals, you know, that have attractive return profiles over different time horizons, and we want to figure out how we can fund as many of those as possible within, you know, the construct of our overall budget and financial goals. But it's very dynamic and it's still pretty early, and so we don't have anything more specific or quantitative to share until we get to the Q4 call, which is typically when we share guidance for the next year.
Your next question comes from the line of Justin Post with Bank of America. Please go ahead.
Great. Thanks. One for Mark, one for Susan. Mark, you've got this powerful new model on your hands, and it seems like there's a lot you could do internally besides externally. But specifically to the ad business, you rearchitected your systems around AI. How much room is there for improvement as you deploy that new model? How are you thinking about that? And then for Susan, you mentioned strong revenue growth next year. Just wondering if that's advertising or does that incorporate some incremental AI revenues hitting next year? Thank you.
I'm happy to take both of those. Go for it. Great. On your first question, you know, I think our ads business has been benefiting for now many years from our ongoing investments in, you know, both kind of what we would have called traditional AI machine learning models, and then of course from the sort of more recent generation of models. I would say that there are three themes there that I think are worth outlining. The first is just, you know, the kind of traditional roadmap of performance improvements that we have in the pipeline, that is what I would describe more as business as usual machine learning work that continues to be a robust and healthy pipeline. And as we are looking into, you know, into 2027, again, we're not providing an outlook, but I would say that our investments in product improvements across both engagement and ads initiatives give us confidence that we have meaningful runway to grow our core business throughout 2027. That also gets to your second question, but I should say basically I think the ranking and recommendations pipeline is healthy.
The second theme I would say is that, you know, we are excited about some of the new research bets that we have as we move into sort of a more LLM-oriented AI infrastructure to help us more deeply reason about people's preferences, what they're interested in, both across organic content and recommendations, and we expect that we will be able to unlock benefits to our ranking and recommendations engine from that research too. And then the third thing is that we expect that generative AI tools, which have already been very valuable for advertisers, will continue to grow in terms of the features that we make available to advertisers, primarily through the Advantage+ suite, but features that make it easier for advertisers to quickly and seamlessly generate, whether it is, you know, creative or take an image and generate video or generate sound, all I think in service of making the ads increasingly personalized for the person that they're being served to. So I would say we feel like there is, you know, meaningful runway across all three of those things.
Your second question was about revenue growth next year. And so as I mentioned, I think we're both, you know, feeling good about the budget investments that we expect we will make in both core ads and engagement initiatives next year. We're also, you know, building several new AI businesses, and we expect that those can begin contributing incremental revenue in 2027, but more importantly can scale meaningfully over time. And those will include monetizing, you know, our AI products through subscriptions, transactions, advertising, developing enterprise offerings, as we talked about in one of the earlier questions. So I would say while many of these opportunities remain early and our near-term focus is really on building high-quality products and achieving product-market fit and scaled product-market fit, I think our track record of reaching, you know, billions of people and building businesses at scale makes us feel good that AI is going to become a meaningful source of revenue diversification over time.
Your next question comes from the line of Mark Schmoolik with Bernstein. Please go ahead.
Yes, thanks for taking my questions. Mark, coming out of Connect, you know, it kind of felt like we were ushering in the next era of the company, you know, and the business reorienting around kind of Muse at the center of everything. You know, is that a fair assessment of kind of how things are going internally? And, you know, and if so, can you talk a little bit more about how some of the business mandates and outcomes may have changed? And then Susan, you know, it was interesting to kind of see the launch cadence where enterprise announcements kind of preceded some of the small business ones. And, you know, appreciate your comments on, you know, some of what's going on there around the SMB agent opportunity, but can you just share more details on kind of the work required to serve and scale the offerings to SMBs? Thank you.
Yeah, I mean, I can talk briefly about the first one. I mean, look, it was more than a year ago that I think I wrote the letter about personal superintelligence as the north star for the work that we're doing here. And it basically fits with this line of work that we've done for more than 20 years at the company that is focused on empowering individuals, giving people a voice, giving people the tools to connect in the ways that they want. And when you extend that to the work around AI now, we think that the most important thing that we can be building for this next generation of technology is basically putting the power of this technology in everyone's hands, which is the personal superintelligence vision. So we've been working on this for a while, and this is when we did the reboot around MSL and building the lab.
A lot of it was this idea that we need to build models specifically to be good as personal agents, that we'd be able to build the best experience by owning and building and designing ourselves the end-to-end technology. So that includes the models and then the agents, and this has kind of been in the works for a while. I mean, the vision around the glasses has also been this. I mean, we've wanted to build the next generation of hardware platforms so that we can deliver the best end-to-end experiences to people. And I think that's starting to come together as well, and I think will even more over the coming years. So I mean, these are long-term bets. I feel like this is what we're here to do is make long-term technology bets and design the best experiences end to end that we can for billions of people around the world. And I think as long as we continue to do that, then, you know, over time the business takes care of itself as long as, you know, we continue executing well, which I'm really proud of the team for how we're doing on that.
Thanks, Mark. Your second question was around Muse for small business. So we launched that, which you can think of as an expansion for Muse, in late September. And, you know, rather than a separate product, it's kind of a set of new skills and connectors inside the existing Muse app aimed at helping SMB owners run operations, you know, find new customers. It connects to a business's, you know, for example, Instagram account analytics or Facebook pages or Meta ad accounts in a few clicks, along with dozens of third-party connectors that businesses already run on like Shopify, QuickBooks, Canva, etc. It already understands what businesses sell, its brand voice, what customers are asking for, and Muse can take actions including analyze ad and content performance, draft campaigns, customer responses, flag issues, you know, and we are actively listening to our SMB users to understand what their top use cases are.
You know, we are seeing them use it for ads optimization, for direct message organizing, use it to expand their sales footprint, to keep their website current based on, you know, things like inventory and new products, to deal with employee load balancing. So we're pretty closely following how businesses use Muse to make sure that we are being thoughtful about new features that we release in Muse to make it maximally useful and productive for SMBs. I'd also say, you know, we have unique touch points to again, you know, I mentioned in my opening remarks 500 million self-identified small businesses, and, you know, we think that many of the investments that we make in consumer products are going to carry over to help power those businesses. Also, we have multiple excellent channels to surface those opportunities to small businesses globally. So, you know, this is a place where we feel like we have an existing extremely strong platform, and we're very excited about it, and we also, you know, believe the transition to AI has broadly unlocked enterprise as a new opportunity for us as well.
Our next question comes from the line of Ross Sandler with Berkeleys. Please go ahead.
Great. Mark, you touched on this earlier, but could you elaborate a little bit on maybe some high-level metrics around the per-user cost structure of Muse today, and then how you kind of see that cost curve coming down as you go forward? And what are some of the things you're doing to bring that cost curve down? Thank you.
I'm happy to answer that, and Mark, you should add anything that you feel like I'm missing. You know, we don't have sort of specific numbers to share around the cost structure of Muse today, but of course it is, as Mark said, pretty compute expensive, and making sure that we are focused on compute efficiency is going to be one of the key vectors towards being able to both scale Muse and grow it into the business that we want. I think there are a couple dimensions of achieving that efficiency. I think some of the more nearer-term pieces, you know, include things like leveraging, you know, off-peak or spare computing capacity, you know, to run some sets of jobs, using smaller models. There's a lot of work to be done across different inference efficiency initiatives, like all in service effectively of higher GPU utilization and other product efficiency work we can do also. And, you know, I think over the longer term, you know, I think this is a place where we expect that we're going to be able to over time, as LLMs scale, get more tasks, you know, done with fewer tokens, and also rely on AI models themselves to help us improve the efficiency of the software that we use to run the models. So I think it's a place where we both feel like there is a lot more work on our efficiency roadmap that is going to help us, you know, bend the curve here, and we also expect that the sort of arc of how the AI-driven technological advances are going to apply here will also help us achieve larger savings over time.
Your next question comes from the line of Mark Mahaney with Evercore ISI. Please go ahead.
Okay. Thanks. Two questions. You know, there's a bit of a playbook, or there has been at Meta over the years, when you surface new surfaces and, you know, you build up the user growth, engagement, then you layer in monetization. Do you think it's sort of a similar playbook here, or does it have to be a little bit faster with Muse, just given that the costs associated with it are materially greater, arguably, than launching those services in the past? And then just a clarification on that commerce data point that you provided about 25% of users and the $200 or greater ASP. Are you including in commerce travel purchases, or is that just a retail data point? Thank you.
My guess, I think that we are going to work on monetization somewhat sooner on this than our normal playbook for a couple of reasons. One is just the size of the numbers that we're talking about in terms of both the costs and the opportunity, I think make it kind of important to make progress on that in order to be able to scale it. The other is just that such a large part of what people are doing is commerce. And to your question, that does include travel too. I think we might consider travel a different case, but travel is actually one of the other top use cases for Muse, is basically people planning that out and planning different kinds of things that they would get than they might get through our family of apps. So I think that this is going to be an important thing for us to work on to deliver the consumer value that people want, and in doing so, I think we will be able to build a model where we get a percent of the value that we are helping to create for people.
So I think that's going to be very important to kind of get the math on all this to work out, so that way we can continue the compute buildout that we want to build in order to get this to reach everyone at scale. And in addition to everything that Susan said in response to the last answer, I would also just add that like we just see this trend that, you know, year-over-year, you know, I just expect that we will be able to deliver the same intelligence that we have now in Muse Wonder, or frankly any of the current frontier models, at a fraction of the cost in a smaller model a year from today. So to the extent that that represents some kind of baseline level that people, you know, seem to, you know, that kind of is sufficient for product-market fit for Muse, I think that we will just continue through kind of continued model development make progress on that efficiency.
The thing that is, and of course, less clear is that I don't think in a year from now most people are going to want to use the current model level of intelligence, because that's also going to make progress. So I think we're going to need to work on all of these things, both the revenue pieces of it and scaling the different aspects of that, as well as progressing on the model development and all the efficiency, in order to be able to, you know, both fund and support the compute buildout and reach billions of people, which again we want to get to that as soon as possible. Part of the reason why we're not, you know, just charging everyone up front to use this is we want to establish this Muse network, and we think that it's going to be more valuable for people at scale when there are a lot of people and businesses using Muse, so that way they can collaborate and work together. I think that that's really a very important state to get to, and one that we're quite excited about. And again, I don't think that there are many companies in the world that are well situated to be able to do that in the way that we are. I think we are very well situated to do that, and we plan to push on that quite aggressively.
And that does conclude our question and answer session. Mr. Bevadi, I would like to turn the call back over to you.
Thank you for joining us.
Okay, we are going to Tesla.
Good luck everyone.
Good afternoon everyone and welcome to Tesla's third quarter 2026 Q&A webcast. My name is Travis Axelro and a number of other executives. Our Q3 results were announced at about 3 p.m. Central time in the update deck we published at the same link as this webcast. During this call, we will discuss our business outlook and make difference. These comments are based on our predictions and expectations as of today.
Let me check the audio on this. But yeah, there is no video.
Yeah, this is the audio.
During the question and answer portion of today's call, please limit yourself to one question and one follow-up. Please use the raise hand button to join the question queue. Before we jump into Q&A,
I'll get a loud one. One sec,
Elon. Thank you. So the third quarter was very strong and I'd like to give a big congratulations to the whole Tesla team for working hard to make it happen. Demand is growing rapidly for our vehicles. It's exceeding our production by a significant margin. And obviously we're going to be ramping and we are ramping production meaningfully. The biggest driver for demand is full self-driving. And today there's really no competitor for FSD in any car that you can buy.
And to be clear, we are producing and delivering as many cars as we can, and we're pushing very hard for FSD approval in additional markets. We're now approved in many countries in Europe, and we're hoping for an EU-wide approval. It's hard to predict, but maybe, you know, within a few months, but I would be surprised if it takes longer than Q1. But obviously that's not a time frame we control, but we do anticipate being fully approved throughout Europe and many other countries. We also began production of the Tesla semi-truck in Q3 and did the new Roadster demo, which was I think one of the most exciting events. I mean, arguably the coolest demo of any product ever.
And that's testament to amazing work by the Tesla capacity. We're I think aiming for that louder.
Uh, yeah, it's a lot better million vehicles a year
by approximately 2030. And that's I think we've got a good shot of achieving that goal.
And yeah. So energy demand is very strong. We're actually almost sold out of all mega packs for 2027 and we're ramping production as quickly as possible to meet demand. We also expect gross margins on that to increase meaningfully.
So, in a nutshell, after many years of sort of grind and things being fairly flat, I think we're now headed for a lot of fun and significant growth.
Regarding robo taxi, we're seeing the robo taxi miles driven or fully autonomous miles driven scale exponentially, meaning scaling very rapidly.
And it would be hard to overstate this point. It really is an extremely fast week-over-week growth in autonomous miles. And I don't think there's any company in the world that can match our scale with autonomous vehicles as we continue to ramp the cyber cab fleet. In Austin, for example, has grown by a factor of 10 since launch about a month ago. And the cumulative mileage is really, when I look at the weekly chart, it's wow, I mean it looks like a, you know, rocket going to orbit basically, it's growing very.
And if I recommend, if you want to try it out, you know, come to Austin and you'll see cyber cabs in use at scale in Austin. As I think a lot of people saw with the Austin City Limits concert recently.
So, so this is really going to a very good place. And regarding Optimus, we've started like what I'd call early production on a high volume line in Fremont. Now I want to elaborate on this point because the and I have said this before that the growth of Optimus, it's an S-curve, but the initial part of the S-curve has a shallow slope and is somewhat bumpy because it is such a radically new product. So, you know, the way to think about it is there's like 10,000 things that have to go right for production of the robot and it'll move as fast as the slowest least lucky of the 10,000. But we do have the vast majority of a million unit per line production line landed in Fremont right now. But I would expect that it takes us probably at least a year, maybe a little longer to get to that annualized rate to get to 20,000 units a week. So this is just a fundamentally because there's, you know, there's still parts of the design that are changing.
Like a lot of people ask me about Optimus. That's why I think I've got to kind of sort of belabor this point. Because if people don't sort of understand like new technology that well or volume production of complex new hardware that well, it sort of seems like, well, can't you just make a whole bunch of these things immediately and send them out? And it's like, no, you've got to basically build up an entire gigantic global supply chain and have domestically a very very big factory and everything's got to work. And there's still some things we need to tweak about the design because you need to deliver a robot that is safe and reliable and has long duration. So it can't like wear out after a month. And there's still quite a lot of work to do with regard to the AI and the robot for it to be truly useful for open-ended tasks. But like I said, if I would expect that the AI, the electromechanical design and the reliability and duration, usage duration, like the usage life of the robot, I do expect these issues to be solved around the end of next year. So that's the time to expect when we're delivering Optimus to companies outside of Tesla.
And I remain convinced that Optimus will be the biggest product on Earth. And humanoid robots in general will be the biggest product on Earth. So it's Optimus a very big deal. But I don't want to temper expectations that we still have a lot to get through and it's about a year or so that it'll take us to get through all that stuff. But as to the best of my knowledge, there is no one that is even close to Tesla with respect to a general purpose humanoid robot.
Regarding the terapab, the Austin-based research lab is progressing quickly. We'll begin commissioning machinery in the first half of next year. And hopefully things go well, we'll make our first test chip just to see if we can make any chip at all around May or June. So that's I think pretty exciting. And then our aspiration is to be making some kind of useful chip at volume around Q3 of 2028.
So, and as I've said publicly on X, the terapab I think will be the most valuable building in the world and will probably have an economic value that will place it in the top 20 of countries. So it's an epic project. And this will be an incredibly important asset if not a necessary asset in order to scale especially Optimus as we can address bottlenecks in semiconductors whether it's memory, packaging, logic or whatever the case may be.
With regard to a potential merger with SpaceX, I think I said everything that should be said yesterday, kept dancing through a minefield there. And yeah, that's it.
In conclusion, we're super excited about our autonomy and robotics roadmap. There's a lot of incredibly awesome stuff coming and I'd like to once again thank the Tesla team for their strong execution and all of our supporters for joining us on this journey.
Great. Thanks very much Elon and VBA has opening remarks as well. VOV,
thanks Travis. We continued our progress on a lot of fronts in K3. Elon already covered a lot of them, additionally of which I'd like to add is we also started deliveries of megapacks with our in-house LFP batteries and for the first time two consecutive quarters of vehicle deliveries of over 480k. On the automotive business, we exited the quarter with our highest backlog in four years with deliveries constrained primarily by production. We're therefore focused on increasing production at all our factories to meet this growing demand. While we are actively working to increase production, it does take some time to get every aspect dialed in from supply chain to manufacturing to delivery logistics.
The Model Y continued to outperform in the quarter and set delivery records in several key markets. Based on the preliminary data which we've gathered, we believe that it was the number one selling BEV in Europe and the number one selling passenger car in South Korea. We also set new record in key markets including Australia, Japan, and Taiwan. As Elon said, FSD continues to be the key driver for demand. In Q3, over 75% of deliveries in North America included a sign up for paid FSD subscription at the time of delivery, which is approximately 20% higher than Q2. Overall, the FSD attached rate continued to improve reaching over 1.7 million paid customers globally of which for the first time more 50% is based on subscriptions.
Given the strength of FSD in the US, we are taking, you know, extra steps to sell certain cars in Europe with some benefits to try and get more fleet out there before broader FSD approval is obtained. On automotive margins, excluding credits, increase sequentially from 16.3% to 18.1%. The improvement in margins is driven by a higher mix of deliveries in APAC. While commodity price increases and interest rate changes continue to add to our cost and create further headwinds, we have adjusted the vehicle financing programs to partially offset for such cost.
On the energy business, you know, we had our second best quarter of deployments of 13.7 gigawatt hour of energy storage. Energy gross margins improved from 20.4% to 33.1%. The sequential margin improvement is primarily attributed to tariff-free funds recognized in the quarter and warranty true-ups resulting from alignment with a vendor on certain cell related costs to be reimbursed by them. As Elon said, the business is witnessing extreme demand from data centers and we are doing our best to increase production and accordingly we'll see, you know, improvements in ASP and further improvements in margins as we move forward.
Services and other margins improved sequentially from 14.1% to 15.9%, an all-time high. This was the result of strength across several of the businesses and services and other including supercharging and insurance. The robot taxi business, which is part of services and others, continued to grow with the launch of cyber cab rides in Austin. Accumulative unsupervised miles 8x in the quarter as we had weekly double-digit growth throughout the quarter.
We're taking all the learnings from our Austin expansion to help us prepare for broader cyber cab launch in other markets. Our priority is progressing the density and expansion of the network through vehicles that provide the best experience like the cyber cab. We will also continue to augment the fleet with other variants over time to address the terrestrial transportation needs of the total population. I'd like to stress that, you know, what we are trying to do is literally take over every part of terrestrial transportation, not just getting people, we're starting with getting people from one place to the other, but we want to basically own this transportation of any kind on earth.
We are in a huge investment cycle to set us up for the future. Therefore, as previously guided, operating expenses continued to increase sequentially. Most of the increase came from significant research and development related activities, including SI development costs such as depreciation from additional compute, chip development, and pre-production ramp costs for new products like the Optimus, Megapac 3, and Simatra. This trend of growing opex would continue till we commercialize these new products.
Net income was impacted from a mark-to-market reduction of our SpaceX holding of 142 million, which was offset by a Bitcoin mark-to-market gain of approximately 290 million. We continued our efforts to manage cash efficiently and responsibly. We ended the quarter with positive free cash flow of over 1.5 billion and an overall cash and investment balance of over 45 billion. We're revising our capex guidance to be approximately 20 billion for the current year as a result of managing our capital deployment efficiently and plan to fund it primarily from our cash flows from operations.
Additionally, during the quarter we secured capacity to borrow up to 30 billion to support the expected growth in capex. A confidence in the cash generation capacity of our business and the investments we are making drove our belief to secure shorter term financing. We don't plan to make any draws under any of the new facilities in this calendar year. The money that we received from the tariff refunds is being reinvested to expand production capacity in the US. I like to stress on this that, you know, we like to do a lot of hardcore real grunt work to get production facilities up and running. And so, you know, our capex for the next few years would continue to expand as we add more robotaxi fleet. We expand our production capacity for Optimus, install manufacturing capacity for solar, purchase additional SI computer infrastructure, and build a semiconductor.
This strategy will position the company for the next era of growth and disrupt many existing markets while creating new ones. This is by far the most exciting time to be a Tesla. The foundation being laid around autonomy, robotics, and energy is setting us up for an extremely bright future. I would like to end by thanking the Tesla team, our customers, investors, and suppliers for the confidence in us on this journey.
Fantastic. Thank you, Vivof. Now we're going to go to questions from say.com. The first question is, how does the cyber cab fleet scale past Austin and what's the regulatory path outside Texas given Nitsa's open safety review? Ashoke, did you want to take that?
Yeah, I'll start here. First of all, we launched cyber cab this quarter, which is very exciting. We achieved that by mostly learning from data from the other vehicle platforms. For example, Model Y, Model 3, etc. All of the data help make the cyber cab without requiring a ridiculous amount of vehicles to produce the data. So we are seeing very good scaling in terms of cyber cab's capabilities. We launched in Austin, but that's only because, you know, we had some caps and we want to swarm Austin with cyber cabs everywhere. But there's no fundamental reason that we are limited to Austin. In fact, next month we'll be launching in Dallas and then the same software just scaled to lots of other cities along with the Model Y robot axis.
Great. Thanks very much. The next question is, what are your thoughts on crowdsourcing training data for Optimus versus your internal Optimus Academy approach? Is data currently the primary bottleneck? I think you covered this quite a bit, but any other color there?
Mostly talked about this already, but crowdsourcing is not the issue for Optimus. There's a lot of things we have to get right about the AI architecture.
That's we're still working on, we're making good progress, but that needs to be sorted out. And really in order for Optimus to get the training data we need, we actually need to make a lot of Optimus. So we need to make I think on the order of 10 or 20,000 bots and then have them do self-play. And we're building out an Optimus Academy where Optimus can practice doing a very wide range of tasks. And then we can use that data in sort of a flywheel to make it better and better at these various tasks. The, you know, a big difference with Optimus versus the cars is we don't have this vast fleet of cars from which we can gather training data. So with Optimus, we have to bootstrap it by making the robots and having them do self-play, which is really how a human learns to navigate the world. You know, it's that's you can see this when you have a toddler and they grow up and they initially are sort of wobbly and they don't know how to do things and they eventually, you know, they learn to wipe their own ass, which is a big milestone.
As anyone who's had kids knows, and then they learn to read and do all sorts of things and be able to do these things, and they learn this by playing. And we actually need Optimus to play at scale in order to have it be really good at tasks in the real world. And you want to add to that?
Yeah. Like you mentioned, alone for the car we actually have the data from the car's embodiment itself, but for Optimus there's no ex for humans to get into and like make Optimus into a puppet or something like that. Like we have to learn, Optimus has to learn by watching other people do tasks initially and then start practicing the task yourself. For example, you can imagine if you're watching a soccer game, just because you're watching it doesn't mean you'll be good at soccer yourself. You got to like start practicing and get good at the game and learn from the bot's own experience. And we are setting up this huge reinforcement learning cycle with initial base training done from humans to bootstrap and then put it on Optimus and do a lot of self-play both in simulation and in the real world to learn on the embodiment of Optimus itself. I think we're pretty close to having very good results in this big loop.
Yeah, I think we're maybe ready to release like an Optimus video in a month or so. I want to make sure that like when we release this video that it's not like a canned demo that, you know, like when you see these humanoid robot demonstrations, some of them look very impressive, but they're not really using any kind of advanced AI or SI. I mean, they're like pre-programmed deterministic tasks. And if you actually try to use that humanoid robot in the real world, you would have a lot of trouble. It wouldn't work basically. So I want to release a video where it's Optimus doing things that are not pre-programmed. And I think that's maybe a month or two for that to have a demo that's you can believe what you see type of thing.
And then there's another milestone that's I think important we want to get to, which is to integrate the Tesla AI5 chip into Optimus, which if things go according to plan will be in approximately April of next year. And that's a giant improvement in capability with an order of magnitude more operations per second, like it's an order of magnitude more compute, AI5 versus AI4. And that will help Optimus a lot because the degrees of freedom that a human robot has to deal with are far greater than what a car has to deal with. So it is a bit of a struggle to squeeze everything needed to operate with all the degrees of freedom of Optimus and the wide range of tasks, you know, because you think of like a humanoid robot, it's going to do like a thousand times more things than a car would do, some very big number basically. So I think the additional compute of AI5 will make a big difference, and that comes in hopefully in volume around April of next year.
And that's why I think like all the pieces, like the refinements in the electromechanical dexterity, making sure Optimus can operate for long periods of time without wearing out, you know, getting the AI software right, and the AI5 chip integrated, all of these things kind of come together. That's why I think about a year from now is when it's something that you could ship to customers. And it would also be reaching scale in production. So that's probably the right timing to think about.
In terms of the initial customers for Optimus, I think it probably would be things that are industrial applications at first. Things that are like dangerous repetitive tasks, things that people really don't want to do. So and that you want done basically 24/7. So like around the clock stuff that's going to be the highest value for Optimus in the beginning. As we scale production, of course, it would be something that people can buy, you know, for their home. But the initial high value use will be the highest value use I think will be kind of heavy industry, dangerous tasks, or things that may cause repetitive stress injuries, and that need you want done 24/7. So that's the way to think about it.
Great. Thank you guys. The next question is very similar. It's about Optimus scaling. So we can go past that one. Answer that one basically.
And the next question is when can we anticipate FSD unsupervised in customer
cars? Ashoke, did you want to kick that off?
Yeah, like I mentioned earlier, the software for Cybercab and Model Y is the same, and pretty soon we'll be able to release the same software as part of the V15 release to customers. So the only additional requirement is to make sure that, for example, the customer Model Ys can be part of the geofences and the fleet management that Tesla has for it to be fully autonomous. We suspect somewhere around Q2 next year is when we can turn on some of the first customer vehicles to be part of the robotaxi fleet.
Great, thank you. The next question is: when will the Cybercab be available for customer purchase ownership? Lars, did you want to kick this one off?
Sure, thanks, Travis. I think it builds a little bit on what Ashoke just said. But in short, we're trying to get Cybercabs to customers by the end of this year, 2026. Obviously we're producing them on our line in Texas, but all of those are currently going to our own internal robotaxi fleet. And as Tesla grows, we'll mainly deliver fully designed autonomous vehicles to our customers, and Cybercab will be the first. And so, as we start small this year and we learn about all the things that Ashoke mentioned about delivery and ownership and fleet management of autonomous vehicles in customer hands, we'll continue to scale that. Eli, I don't know if there's anything you want to add to that.
No, I mean, Cybercab is primarily going to be something that is offered as transport-as-a-service, whereas our other cars would be more the cars that you'd want to own, like the 3 and the Y and whatnot, and the Roadster obviously. But the vast majority of the Cybercab stuff will be essentially Tesla-owned and transport-as-a-service.
Great, thanks guys. The next two questions are quite similar, around unit economic costs. The first one is on per paid robotaxi mile, and the second one is cost per Optimus unit. And we already covered what the first paying customer looks like. So, did you want to get into the unit economics question here?
Yeah. So on the robotaxi side, the main geographies where we are operating, we're already seeing utilization improving week by week. As Elon was talking about, we look at the miles and how many paid rides are happening. So, are we at our goal of 30 cents today? No. But do we see a path to get to that? Very yes, we do. And it's all about scaling operations. And what you'll see over the next few months is that today Cybercab, which is the primary robotaxi product, is available only in Austin, but we do plan to bring it out in some other cities before the end of this year. And as we add more Cybercabs, we are also learning from the operational experience of managing the fleet, pickup and drop-off, cleaning, all those things. So all those costs are being dialed in, and that's why, like I said before, we definitely see a path to get to our 30-cent target.
And then did you want to cover the Optimus costs?
Yeah, I mean, I think Optimus cost internally we are tracking pretty well in terms of how the design has matured, but it would be a little too early to say that we have got there because, like Elon was saying, we're still making a lot of design iterations. The good thing is, when you look at it from a cost perspective, we're trending closer to where we would say our Cybercab costs would end up being.
Great, thank you very much. The next question is: when do you anticipate Optimus will be generating revenue? So we covered that in a prior question. The next one is: mapping for FSD continues to be a problem. The three biggest issues are recognizing proper speed limits, parking, and typical routes. I understand you use various third-party maps, but why not use your own maps? Authorize trusted and verified Tesla owners to provide the input. Ashoke, did you want to kick off here?
Yep. Yeah, you're totally right that we shouldn't be depending on external people's maps. So we are building our own maps, but not the same way as Waze maps. We're building an entirely new architecture with essentially AI-based mapping and navigation. It's going to be super awesome. It's going to be integrated with voice. You can talk to it, ask for different routes. It's going to learn your personalized preferences plus also the fleet preferences. The collective intelligence of all the cars is going to flow into making the maps and navigation be super cool. You'll see the start and end of trips already use this technology pretty soon as part of the V15 release. And over the next several months, it's just going to take over all of the navigation functions, clocking, destination handling, and we'll know you better than you know yourself in some regard for the driving task, and handle it fully.
Great, thank you, Ashoke. And then our last question is: what is the current production rate at your existing factories? Do you anticipate building new ones? Lars, do you want to kick that off?
Yeah, sure. I think Vibov kind of touched a little bit on this in his opening remarks. And I'll say our factories are operating at record rates this quarter, and of course they can only build at the rate of release like process or component, and mentioned that we are actively managing all the aspects of production. As we've spoken in our past calls, we've made strategic investments globally to increase rates of our current factories over the last year plus, and this quarter we are starting to see that, and we expect that to continue in coming quarters as those investments come to fruition. Beyond that, we're also working to ramp Cybercab, obviously in Giga Texas, and we applied for proper permits to expand the factories in Berlin, and as Elon mentioned, we just started our new semi factory in Reno. So in short, we are building new factories, and we're aiming to hit that 5 million goal by 2030, as Elon said.
Great, thank you very much. That's it for the Say.com questions. Now we will be going to analyst questions. As a reminder, as Elon said, we will not be addressing any questions today on a potential merger with SpaceX. With that, the first question comes from Tom from RBC. Tom, please unmute yourself when you're ready.
Yeah, thanks for taking the question. It's on FSD. So the attach rate, I think according to my math, is like 30 to 40% in North America on a paid basis. It's becoming a flywheel, as you said, for more car sales, and the attach rate exceeds other automakers' subscription-based autonomy by a lot. I guess in a weird way, could you guys be a victim of your own success and seeing other car makers noting the success and trying to aggressively come up with similar L2 Plus type products, maybe partnering with Nvidia or Qualcomm? And if that happens, could that be deflationary for FSD pricing?
I think people take this thing very simply, that if the software can be solved, it's there. It's not, because I mean, I'll let Ashoke get into it, but basically it's a very hard problem.
It's a super hard problem. Yeah, it's easy to get to the first 90% and make a cool-looking demo, but when you get in the long tail of this problem, it's so long that people don't realize anyone with their same mind should not attempt to solve this problem. It's so difficult and so long-tailed, and especially to get to a safety point where you can drive safely for millions of miles with no injuries and so on, that's going to be extremely hard. As we release unsupervised FSD to the broader customer fleet, it's just going to be, I don't think anyone can match it in several years. And one other thing which I'll say, if it wasn't clear, that especially in our showrooms here in the US, customers are now coming in and saying, can we get into an FSD drive? They're not asking for a 3 or a Cybertruck, they're saying, can we get an FSD drive? And that has become the key driver because what it does is it actually opens up a lot more flexibility for different parts of the population wherein they had issues driving conveniently before. Now they're getting their freedom back by being able to use FSD. And a lot of folks are just like, I mean, it's a game changer. I mean, if you haven't tried it, I keep saying it every time. If you do it, you won't be able to go back to driving any other car.
Yeah. Follow-up is similar to that question on China. I mean, there it seems like autonomy is table stakes. Is it the same kind of answer on that? That's question one, that they're not going to be able, those car makers aren't going to be able to develop the similar products that you guys have had on FSD, or do you see there that being definitely a different pricing dynamic?
I mean, at the beginning, definitely the leapfrog which we have in terms of this technology isn't there with any of the other Chinese OEMs today. And we're working very diligently to try and get broader, I mean, FSD approval in China. It is hard, but for certain cars we have been able to have FSD operating. And whoever has tried it there, they understand how much better it is as compared to any of the competition. And in fact, I don't know if you've seen this, there have been some competitor CEOs who have come and done FSD drives here in the US, and they themselves have been blown away as to what FSD is capable of doing. So it is a similar answer, and again, we're not taking it lightly. We're actively working with the regulators in China, because I don't know if you saw this, but we did release our safety report on FSD before, but we've also released our unsupervised or robotaxi safety report. We just think this is the right way to get people into a safe environment, because the amount of accidents which happen because of drivers not being alert, and this is the only way we can ensure that there are less casualties in the world. And any regulator who looks at the data, it would be very hard for them to refute it.
Great, thanks so much. Our next question comes from Emanuel from Wolfe. Emanuel, please unmute yourself.
Great, thank you. Hi team. So on robotaxi, you've talked about sustaining double-digit week-over-week growth in unsupervised miles. I'm curious if there's a way to triangulate that for us into revenue and maybe profitability of the robotaxi business. If you sustain, let's say, 15% week-over-week growth in these miles, you'll probably cross 10 million miles by the end of the year. How many of those, how many miles would you need to generate gross profit?
I mean, so I think Elon talked about this a little bit at the beginning that, you know, using exponential math, this would become a significant part of our revenue and profitability in '27.
Yeah. I wouldn't say it's like, it's not like it's going to move the needle this quarter, but if you say like maybe...
I think it starts to become noticeable probably in Q2, and then probably a big deal by Q3 or Q4 of next year.
Got it. And then if I think about it in terms of, you know, fleet size, so I think your Cybercab line capacity is listed at more than 125,000 units a year, production just recently started. How do you expect the ramp-up curve to be on the Cybercab line?
I mean, I'll kick it off, but then I'll also let Lars in. But you know, I would give kudos to the engineering team. They have designed a product because not only do I talk to the engineers, I also talk to the manufacturing guys. They think this is one of the easiest products for them to scale in terms of manufacturing, so scaling would not be that much of a challenge. I think the key thing which we're trying to make sure is that we have all the regulatory approvals where we can start deploying the Cybercabs as fast as we can produce them. And again, Lars, feel free to chime in.
Yeah, thanks, I appreciate the accolades. The team definitely crushed it on the Cybercab design and manufacturing. Just to your point, we have 50% less parts than any other vehicle we've ever built. So that's 50% less things to go wrong. We've definitely been bursting the Cybercab line to see how fast we can run it. I think the listed capacity is more of a rate at which we're capable of running today, but the actual capacity of that vehicle line is significantly higher. Right now we're building at the rate that the robotaxi service needs the vehicles. And I'll say Ashoke and I are in a bit of a race of who's going to stay ahead. He's got exponential growth coming on the miles month over month, and we're going to look to meet that as well with the vehicle production.
Great, thanks guys. The next question is going to come from Andrew from Morgan Stanley. Andrew, please unmute yourself.
Great, thanks so much for taking the question. So I want to start on your energy business. You're clearly seeing a lot of demand on the energy storage or Megapack side, and you've got some goals to bring on your own solar manufacturing, but I was just hoping to get a little bit more insight in terms of how you're thinking about Tesla's role in enabling both distributed power but also distributed compute. I think last quarter you alluded to a Megapod product. So just hoping to get a little bit more insight in terms of what you're envisioning there and ultimately how big this could be for Tesla.
I think it's still early days on that front. We don't know the full extent of how that'll unfold. I think we'll have a better sense for that probably in maybe a Q1 or Q2. But it does have a lot of potential. It's just hard to say how much potential right now.
Okay, understood. And then maybe just a follow-up on robotaxi. It does seem like you've kind of hit an inflection point here in Austin over the last month or so since you launched the Cybercab. So would you generally say the bottlenecks at this point to growth are more regulatory-driven as you think about expanding into new geographies, and that you've kind of gotten through most of the hurdles on the software side? Just kind of curious how you would generally categorize some of those growth hurdles in some of the incremental regions you're planning on scaling into over the next few months.
I think there are still certain software challenges which we are still working through. You know, talked about it. So maybe you can...
Sure. Yeah. For example, we initially had the robotaxi service from 6:00 a.m. to 9:00 p.m., and then we expanded to 10 p.m., 11 p.m. Now it's going to be pretty soon 2 a.m. So we're slowly expanding the availability of robotaxi, and that is driven by the capability of the AI software. And we just want to make sure that there's not a single safety incident. That is our operating principle. And even if there's the slightest possible risk at all, we don't take on the risk. And so we are very risk-averse in that sense, as in we want zero injuries or anything bad happening, and that is the driving principle. And we will see that over the rest of this year, we'll unlock 24/7 operation, go to higher speed roads, and we think all of that is necessary to sort of scale and offer a great product to a lot of users. And that's why we wanted to both do the breadth-first of doing multiple cities. We did six cities, we do six cities now. We are also doing the depth of having a lot of vehicles in a single city, which is in Austin, and we'll expand to more weather conditions, day and night conditions, highways and high speeds, and all of that will be done hopefully by the end of this year, at which point you will see a lot more scaling, a lot more cities being covered by robotaxi. So it's not purely regulatory or something like that. It is technology-driven, but we do see that pretty quickly become regulatory, perhaps in like Q1, Q2 time frames.
Great, thanks guys. The next question is going to come from Edison from Deutsche Bank. Edison, please unmute yourself.
Great, thank you for taking our questions. First, I want to ask about TerraFab. I know, Elon, you mentioned that you had an aspirational goal of 2Q28. Do you have a sense on how much capital needs to be invested to get there? And also, what kind of milestones should we be on the lookout for on the way there?
Well, it's going to be some pretty significant capital. It's certainly in the tens of billions for TerraFab. Although we've got to figure out what the sort of relative split is between SpaceX and Tesla in terms of who pays for what at TerraFab. But it's not going to be less than tens of billions in capital equipment, you know, up through early 2028, and then it will be a lot more. It'll probably be north of 100 billion long term.
Yeah, and I'll just add, you know, the first set of equipment for the fab which Tesla is building, we've actually already placed most of the orders, and that's why when Elon was talking about middle of next year, that is from the first fab which...
Yeah, we're just figuring out how to work the equipment type of thing.
