Q3 FY2024 Earnings Call
TSLA · Preprocessing Report
2024-10-23
Quality
100%
28
Turns
8
Speakers
4
Sections
2
Exchanges
354
Claims
Quality issues

Entities by group 20

equity analysts 2
Pierre FerragupersonAdam Jonasperson
driver assistance software 2
Full Self-DrivingproductAutopilottechnology
humanoid robots 1
Optimusproduct
battery cells 1
4680product
driver assistance features 1
Smart Summonproduct
grid energy storage 1
Megapackproduct
language models 3
GPT-3technologyGPT-4technologyGeminitechnology
autonomous ride-hailing 1
Robotaxiproduct
home energy storage 1
Powerwallproduct
autonomous driving software 1
Full autonomytechnology
Ungrouped 6
TeslacompanyElon MuskpersonVaibhav TanejapersonAshok ElluswamypersonxAIcompanyOpenAIcompany
REPORTING 56PROJECTING 39POSITIONING 146EXPLANATORY 49ANALYST 11

Topics 92

autonomy×27vehicle×22ride-hailing×19ai×18energy×12cybercab×10compute×10model×9battery×5optimus×5kardashev scale×5strategy×5margin×5cost×5partnership×5robot×4cell×4robotaxi×4training×4data×4

Themes 235

safety×8autonomous×5growth×5self-driving×5driving training×4miles between interventions improvement×3functionality×3energy×3real-world×3competitive advantage×3production milestone×2volume production×2production target×2cost competitiveness×2cost target×2performance improvement×2model scaling×2normal-looking design×2distinctive design×2full self-driving×2across vehicles×2training capacity×2selection challenge×2scale×2most valuable product×2launch timing×2capacity ramp×2civilization progress×2solar source×2automotive growth×2revenue contribution×2regional outperformance×2cost reduction×2rate tailwind×2affordability×2quarterly variability×2reduction×2deployment×2tesla-xai relationship×2in-car compute constraints×2automotive application×2industry declines×1record level×1ev industry×1ev divisions×1challenging automotive environment×1record q3 fy2024×1rapid growth and demand×1event demo×1no driver controls×1no manual intervention×1product launch×1affordable models×1production timing×1production outlook×1cell production×1competitive positioning×1lower cost×1supplier sourcing×1in-house production strategy×1vehicle and storage growth×1supporting higher output×1us competitiveness and supplier mix×1mile between interventions×1cybertruck release×1single stack×1neural nets×1actually smart summon×1version rollout×1miles between interventions trend×1fsd intervention interval×1future milestone×1technology drivers×1human benchmark×1internal estimate×1claims×1safer-than-human driving×1rapid improvements×1vehicle intelligence×1customer expansion×1trial rollout×1user adoption×1robo-taxi access×1existing vehicle line×1speed limits×1usage count×1employee capability×1employee app access×1bay area coverage×1software development×1shareholder deck×1testing progress×1development×1profile sharing and synchronization×1robotaxi readiness×1future use×1release timing×1cybersecurity for destination sending×1destination sending availability×1mobile app route progress feature×1mobile app functionality×1network functionality×1public rollout×1regulatory approval process×1california approval×1texas approval speed×1texas availability×1california launch×1california and texas rollout×1expansion outlook×1strategic transformation×1business model expansion×1training constraints×1improving performance×1mistake detection×1comparison speed×1evaluation difficulty×1multiple factors×1dexterity and movement×1hand design×1hand and forearm design×1tactile sensing×1humanoid robot leadership×1scaling advantage×1ai and production scale×1localized ai and scale×1business performance×1production capacity×1annualized capacity×1planned capacity×1stationary deployment×1long-term scale×1terawatt-scale deployment×1strategy detail×1analysis×1summary×1sustainability×1constraints×1sustainable civilization×1sustainable usage×1kardashev scale×1level 1 definition×1kardashev level progress×1solar energy×1galactic energy×1future of energy transport robotics and ai×1long-term focus×1company approach×1objective achievement×1market capitalization×1operating environment×1positive results×1record operating×1volume and pricing×1pricing pressure×1third-party funding×1upfront accounting×1sales×1adoption growth×1affordable and compelling×1inventory discipline×1financing options×1value proposition versus oems×1buyer awareness gap×1capabilities visibility×1automotive improvement×1volume growth×1lower duties×1challenging outlook×1payment sensitivity×1vehicle retention×1sequential growth×1project mix×1production slots×1lowest level×1ongoing reduction focus×1business improvement×1fleet growth×1cost decline×1restructuring×1ai efforts×1ai spending×1q3 fy2024 amount×1ai compute-driven increase×1full-year guidance×1future vision×1company vision×1regulatory and execution delays×1future outlook×1availability×1utilization×1training scale and reliability×1geographic expansion×1vehicle sensor setup for ai×1context capacity comparison×1low compute inference×1power efficiency×1volume received×1video sorting×1data prioritization difficulty×1training constraint×1training speed×1performance comparison×1validation×1simulation-based evaluation×1autonomy bottleneck×1scaling strategy×1regulatory compliance×1paid rides×1xai benefits to tesla×1competition for talent and technology×1long-term direction×1training improvements×1product focus×1differences×1not all equal×1broad spectrum×1internal workstreams×1collaboration with xai×1approach difference×1video and audio context×1efficiency leadership×1efficiency necessity×1available in-car electricity×1different strategic problems×1future cash burn×1compute capacity×1company formation×1truth-seeking digital superintelligence×1truthful company positioning×1truth-seeking aspiration×1truthfulness despite political incorrectness×1strategic support×1founding background×1from scratch×1

Key Metrics 65

cost×6miles between interventions×6compute×6power×5revenue×4margin×4capex×4profitability×3vehicle growth×3volume production×3regulatory approval×3crash rate×3run rate×3deployment×3cost per micro×3vehicle count×2units per year×2output×2miles between critical interventions×2unit volume×2credit sales×2cost per vehicle×2interest rates×2monthly payment×2operating expense×2context×2inference compute×2order volume×1deliveries×1production×1demand×1sales growth×1vehicle deliveries×1miles per critical intervention×1trial×1adoption×1take rate×1uses×1training capacity×1miles×1degrees of freedom×1production rate×1gigawatt hours×1terawatt hours×1kardashev level×1market capitalization×1operating cash flow×1average selling price×1factor×1automotive margin×1production and delivery volume×1freight and duties×1backlog×1costs×1gpu count×1cameras×1compute power×1petabytes×1training speed×1performance×1validation network×1miles driven×1evaluation metric×1data×1burn rate×1

Entities 496

Tesla×244Elon Musk×130Vaibhav Taneja×36Ashok Elluswamy×18xAI×16Full Self-Driving×8Optimus×84680×7Pierre Ferragu×6Smart Summon×5Adam Jonas×5Megapack×3Robotaxi×2Autopilot×2Powerwall×1Full autonomy×1GPT-3×1GPT-4×1Gemini×1OpenAI×1

Business Segments 176

Automotive×153Energy Generation And Storage×21Services And Other×2

Sectors 140

automotive×44artificial intelligence×41robotics×14ride hailing×8energy storage×7autonomous vehicles×7transportation services×5semiconductors×5electric vehicle×2navigation software×2mobile applications×2cybersecurity×1battery manufacturing×1financial services×1

Regions 36

California×7Texas×6U.S.×5Bay Area×5Shanghai×3North America×2United States×2China×2worldwide×1Earth×1Europe×1world×1

Metadata Distributions

Sentiment
positive 113negative 14neutral 174
Temporality
backward 59forward 69current 173
Certainty
definitive 64confident 88moderate 111tentative 33speculative 5
Magnitude
major 15moderate 157minor 129
Direction
improvement 33decline 2mixed 1none 265
Time Horizon
immediate 59near_term 85medium_term 22long_term 19unspecified 116
Verifiability
quantitative 49event 25qualitative 227
Analyst Intent
probing 1challenging 2confirming 1seeking_detail 5seeking_guidance 2

Speakers

Executives
AEAshok ElluswamyexecutiveEMElon MuskCEOLMLars MoravyexecutiveURUnidentified Company RepresentativeexecutiveVTVaibhav TanejaCFO
Analysts
AJAdam JonasanalystPFPierre Ferraguanalyst
Other
TATravis Axelrodir

Sections

TypeLabelSpeaker
preamblePreambleTravis Axelrod
prepared_remarksPrepared RemarksElon Musk, Vaibhav Taneja, Ashok Elluswamy, Unidentified Company Representative, Travis Axelrod
qa_sessionQ&A Session—
closing_remarksClosing RemarksTravis Axelrod

Q&A Exchanges 2

#AnalystFirmTurns
1
PFPierre Ferragu
New Street6
2
AJAdam Jonas
Morgan Stanley5

Claim Taxonomy 301

REPORTING56
resultFinancial outcome for a completed period22
metricNon-financial quantitative fact22
operationalDiscrete completed event12
PROJECTING39
guidanceQuantitative expectation with number + time9
commitmentPromise with binary verifiable outcome21
targetLong-term aspirational quantitative goal9
POSITIONING146
strategyPriority, direction, or initiative121
competitiveCompany's position or advantages13
opportunityMarket condition framed as growth driver3
riskHeadwind, constraint, or uncertainty9
EXPLANATORY49
attributionWhy a specific outcome happened6
contextNon-company macro/industry fact43
FRAMING0
thesisFalsifiable belief about how the world works0
ANALYST11
questionInterrogative seeking information8
observationRestates a fact or data point1
concernFlags a risk or challenge2
estimateAnalyst's own projection or calculation0
sentimentOpinion, praise, or critique0

Transcript

Preamble
TA
Travis AxelrodirTesla
Good afternoon, everyone, and welcome to Tesla's Third Quarter 2024 Q&A webcast. My name is Travis Axelrod, Head of Investor Relations, and I am joined today by Elon Musk, Vaibhav Taneja 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 forward-looking statements. These comments are based on our predictions and expectations as of today. Actual events or results could differ materially due to a number of risks and uncertainties, including those mentioned in our most recent filings with the SEC. 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, Elon has some opening remarks. Elon?
Prepared Remarks
EM
Elon MuskCEOTesla
Thank you. So to recap, something that [inaudible] the industry I've seen year-over-year declines in order volumes in Q3. Tesla at the same time has achieved record deliveries.
In fact, I think if you look at EV companies worldwide to the best of my knowledge, no EV company is even profitable. And I'm not - to the best of my knowledge, there was no EV division of any company, of any existing auto company that is profitable. So it is notable that Tesla is profitable despite a very challenging automotive environment.
And this quarter actually is a record Q3 for us. So we produced our 7-millionth vehicle actually just yesterday. So congratulations to the teams that made it happen in Tesla. That's staggeringly immense amount of work to make 7million cars. So, let's see. And we also have the energy storage business is growing like wildfire, with strong demand for both Megapack and Powerwall. And as people know, on October 10th, we laid out a vision for an autonomous future that I think is very compelling. So, the Tesla team did a phenomenal job there with actually giving people an opportunity to experience the future, where you have humanoid robots walking among the crowd, not with a canned video presentation or anything, but literally walking among the crowd, serving drinks and whatnot. And we had 50 autonomous vehicles. There were 20 Cybercabs, but there were an additional 30 Model Ys operating fully autonomously the entire night, carrying thousands of peoples [inaudible] with no incidents, the entire night. So — and for those who went there that — it's worth emphasizing that these the Cybercab had no steering wheel or brake or accelerator pedals. Meaning, there was no — there's no — there was no way for anyone to intervene manually even if they wanted to. And the whole night went very smoothly. So, regarding the vehicle business, we are still on-track to deliver more affordable models starting in the first half of 2025. This is I think probably people are wondering what should they assume for vehicle sales growth next year. And at the risk of - to take a bit of risk here, I do want to give some rough estimate, which is I think it's 20% to 30% vehicle growth next year. Notwithstanding negative external events, like if there's some force majeure events, like some big war breaks out or interest rates go sky high or something like that, then we can't overcome massive force majeure events. But I think with our lower cost vehicles with the advent of autonomy something like a 20% to 30% growth next year is my best guess.
And then Cybercab reaching volume production in '26. I do feel confident of Cybercab reaching volume production in '26. So just starting production, reaching volume production in '26. And that's — that should be substantial.
And we're aiming for at least 2 million units a year of Cybercab. That'll be in more than one factory, but I think it's at least 2 million units a year, maybe 4 million ultimately. So, yeah, these are just my best guesses, but if you ask me my best guesses, that those are my best guesses. The cell 4680 lines, the team is actually doing great work there. The 4680 is rapidly approaching the point where it is the most competitive set. So when you consider the fully landed - the cost of a battery pack, fully landed in the U.S. net of incentives and duties, the 4680 is tracking to be the most competitive. Meaning lower cost [inaudible] considered than any other alternative. We're not quite there yet, but we're close to being there, which I think is, extremely exciting. And we've got several - a lot of ideas to go well beyond that. So if I think there's — if we execute well, the 4680 will have the — Tesla internally produced cell will be the most cost competitive cell in North America, a testament to a tremendous amount of hard work there by the team. So that's - we'll continue to buy a lot of cells from our competitors. Our intent is not to make to provide to make cells just internally. So I don't want to set off any alarm bells here. We're also increasing substantially our vehicle output and our stationary storage output. So we need a lot of cells. And most of them will still come from suppliers, but I think it is some good news that the Tesla internal cell is likely - is tracking to be the most competitive in the U.S. So with respect to autonomy, as people are experiencing in the cars, really from week-to-week, there are significant improvements in the miles between interventions. So with the new version 12.5, release of full self-driving in Cybertruck, combining the code into a single stack so that the, city driving and the entering the highway driving are one stack, which is a bigger burden for the highway driving. So it's just all neural nets. And the release of Actually Smart Summon. We're trying to have a sense of humor here. And we're also — so that that's 12.5. Version 13 of FSD is going out soon.
Ashok will elaborate more on that later in the call. We expect to see some roughly a 5 or 6 fold improvement in miles between interventions compared to 12.5. And looking at the year as a whole, the improvement in miles between interventions, we think will be at least three orders of magnitude. So that's a very dramatic improvement in the course of the year. And we expect that trend to continue next year. So, the current internal expectation for the Tesla FSD having longer miles between intervention than human is the second quarter of next year, which means it may end up being the third quarter, but it's next - it seems extremely likely to be next year. Ashok. Do you want to add anything?
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AE
Ashok ElluswamyexecutiveTesla
Yeah. miles between critical interventions, yep, like you mentioned, Elon, we already made a 100x improvement with 12.5 from starting of this year. And then with v13 release, we expect to be a 1000x from the beginning - from January of this year on production [inaudible] software. And this came in because technology improvements going to end-to-end, having higher frame rate, partly also helped by hardware force, more capabilities, so on. And we hope that we continue to scale the neural network, the data, the training compute, et cetera. By Q2 next year, we should cross over the average human miles per critical intervention, call it collision in that case.
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EM
Elon MuskCEOTesla
I mean, that that's just unvarnishing our internal estimate.
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AE
Ashok ElluswamyexecutiveTesla
Yes. Yeah.
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EM
Elon MuskCEOTesla
So, that's not sandbagging or anything else. Our internal estimate is Q2 of next year to be safer than human and then to continue with rapid improvements, thereafter. So, a vast majority of humanity has no idea that Teslas drive themselves.
So especially for something like a Model 3 or Model Y, it looks like a normal car. So you don't expect normal car to be able to be intelligent enough to drive itself. The Cybercab looks different. Cybertruck looks different. But Model Y and Model 3 look, they're good looking cars, but look, I think, look fairly normal. You don't expect a fairly normal looking car to have the intelligence enough AI to be able to drive itself, but it does.
So we do want to expose that to more people. And so we're doing every time we have, a significant improvement in the software, we'll roll out another sort of 30 day trial. So to encourage people to try it again. And we are seeing a significant improvement in adoption. So the take rate for FSD has improved substantially especially after the 10/10 event. So there's no need to wait for a robo-taxi or Cybercab to experience full autonomy. We expect to achieve that next year with the — with our existing vehicle line.
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AE
Ashok ElluswamyexecutiveTesla
One point Actually Smart Summon gives a small taste of what it's going to look like, the car able to drive itself to the user within private parking lots. Currently, it's speed limited, but then it's going to quickly be increased. And we already had more than 1 million usage [inaudible] of Smart Summon.
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EM
Elon MuskCEOTesla
Yep. So, and we actually we have, for Tesla employees in the Bay Area, we already are offering a ride-hailing capability. So you can actually with the development app, you can request a ride, and it'll take you anywhere in the Bay Area. We do have a safety driver for now, but the software required to do that, we've developed and I mean, David, do you want to elaborate on that?
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UR
Unidentified Company RepresentativeexecutiveTesla
Yeah. Sure. David, we showed some screenshots of this in the Q1 shareholder deck. And, yeah, this is real.
We've been testing it for the better part of the year and, the building blocks that we needed in order to build this functionality and deliver it to production, we've been thinking about working on for years. It just so happens that we've used those building blocks to deliver great features for our customers in the meantime, such as sharing your profile, synchronizing it across cars, so that every single car that you jump into, whether it's another car that you own or a car that somebody's loaned to you or a rental car that you jump into, it looks exactly like yours. Everything's synchronized, seat mirror positions, media navigation, everything is the same. Just what you would expect from, one of our robotaxis. But we gave that functionality to our customers right now because we built it intending for it to be used in the future. We're releasing that functionality now. All the — and then cybersecurity that we knew we were going to need to deliver that functionality, sending a navigation to destination from your phone to the vehicle, and so we're doing that now with the ride-hailing app, but it's something that we've made available to customers for years. Seeing the progress on route in the mobile app, that's something you'll need for the ride-hailing app. But again, we released it in the meantime. So it's not like we're just starting to think about this stuff right now while we're building out the early stages of our ride-hailing network. We've been thinking about this for quite a long time, and we're excited to get the functionality out there.
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EM
Elon MuskCEOTesla
Yeah.
And we do expect to roll out ride-hailing in California, Texas next year to the public. But not the California is somewhat there's quite a long regulatory approval process. I think we should get approval next year, but it's contingent upon regulatory approval. Texas is a lot faster. So it's, I'd say, like, we're — we'll definitely have available at Texas, and probably have it available in California subject to regulatory approval. And then — and maybe some other states actually, next year as well, but at least California and Texas. So that'd be very exciting. There's really a profound change.
Tesla becomes more than a sort of vehicle and battery manufacturing company, at that point. So we published our Q3 vehicle safety report, which shows one impact for every 7 million miles of autopilot, that compares to the U.S. average of one crash roughly every 700,000 miles. So it's currently showing a 10x safety improvement relative to the U.S. average. And we continue to expand our AI training capacity to accommodate the needs of both FSD and Optimus. We're currently not a training compute constraint.
That's probably the biggest factors that the FSD is actually getting so good that it takes us a while to actually find mistakes. And when you start getting to where it could take 10,000 miles to find a mistake, it takes a while to actually figure out which it is — is this soccer ball better than — is soccer ball A better than soccer ball B? It actually takes a while to figure it out because neither one of them are making mistakes, or takes take a long time to make mistakes. So that's actually the single [inaudible] based on many factors. How long does it take us to figure out which version is better? So that's sort of high class problem.
Obviously, having a giant fleet is very helpful for breaking this out. And then with Optimus, we show a massive improvement in Optimus's dexterity movement on October 10. And our next-gen, hand and forearm, which has 22 degrees of freedom double - which is double the prior hand and forearm, it's extremely human like. And also it's much better tactile sensing. It's really - I feel confident in saying that we have most advanced humanoid robot by long shot. And we're moreover the only company that really has all of the ingredients necessary to scale humanoid robots. Because the things that what other companies are missing is that they're missing the AI brain, and they're missing the ability to really scale to very high volume production. So some have seen some impressive video demos, but what but they're [lacking is] (ph) localized AI and the [going] (ph) to scale volume to very high numbers. As I've said on a few occasions before, I think Optimus will ultimately be the most valuable product. So I think it has a good chance of being the most valuable product ever made. For the energy business, that's doing extremely well. And there's the opportunity ahead is gigantic.
The Lathrop Megapack factory, reached 200 Megapacks a week, which is now a 40 gigawatt hour a year run rate. And, we have a second factory in Shanghai that will begin with a 20 gigawatt hour a year run rate in Q1 next year, so next quarter. And, that will also scale up. It won't be long before, we're shipping a 100 gigawatt hours a year, stationary storage at Tesla. And that'll ultimately grow I think to multiple terawatt hours per year. It has to actually in order to have a sustainable energy future. If you're not at the terawatt scale, you're not really moving the needle. So if you look at our admittedly very complicated last master plan, which I think actually is too much detail. I'll — maybe I'll ask [Vaibhav] (ph) to analyze it.
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UR
Unidentified Company RepresentativeexecutiveTesla
Sure Elon.
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EM
Elon MuskCEOTesla
Can give us the TLDR on the last master plan. But we showed in that last plan that it is possible to take all of us to a fully sustainable energy situation, using sustainable energy power generation and batteries and electric transport. And there are no fundamental material limitations. Like, there's not some very rare material that we don't have enough of on earth. We actually have enough of raw materials to, yeah, take all of human civilization make it fully sustainable. And even if civilization dramatically increased its electricity usage, it would still be fully sustainable.
One way to think of the progress of a civilization, it's based out a little esoteric, but is percentage completion of Kardashev scale. So Kardashev Scale 1 would be you're using all the power of a planet. We were we're currently less than 1% on Kardashev Level 1. Level 2 would be using all the power of the sun. And level 3, all the power of the galaxy.
So we have a long way to go. Long way to go.
When you think in Kardashev terms, it becomes obvious that by far the biggest source of energy is the sun. Everything else is in the noise. So in conclusion, Tesla is focused on building the future of energy, transport, robotics, and AI. And this is a time when others are just focused on managing around near term trends. We think what we're doing is the right approach. And, if we execute on our objectives, then I think we will.
Tesla my prediction is Tesla will become the most valuable company in the world and probably by a long by a long shot. I want to thank the Tesla team once again for strong execution in a tough operating environment, and we're looking forward to building, an incredibly exciting future. Thank you.
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TA
Travis AxelrodirTesla
Great. Thank you very much, Elon. And I'll let Vaibhav pass some more big remarks as well.
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VT
Vaibhav TanejaCFOTesla
Yeah. Thanks. Our Q3 results were positive and once again, demonstrate the scale to which businesses evolved. What they use with the generation of record operating cash flows of $6.3 billion. Our automotive revenues grew both quarter-on-quarter, year-on-year. While we had unit volume growth, we did experience reduction in ASPs, primarily due to the impact of financing incentives. As a reminder, we are providing these incentives primarily using third-party banks and financial institution and recognize the cost of these incentives as an upfront reduction to them. We released FSD for Cybertruck and other features like Actually Smart Summon, like Elon talked about in North America, which contributed $326 million of revenues in the quarter. We continue to see elevated levels of regular 2 week credit sales with over $2 billion of revenues so far this year. To expand on this at an industrial level, China continues to outperform U.S. and Europe by a factor of three. And if there is something to be learned from that, this gives a signal of what is to come in other regions. As customers' acceptance of EV growth.
And we feel that is the right strategy to build affordable and more compelling leads. Our focus remains on growing unit volume, while avoiding a build-up of inventory. To support this strategy, we're continuing to offer extremely compelling vehicle financing options in every market. When you compare any vehicle in our lineup with other OEMs, believe our vehicles provide much better value, particularly when you consider the safety features, performance, and unparalleled software functionalities, like David also talked about, include also what, Ashok talked about around autonomy, music options, parental controls, and much more. While every vehicle in our lineup comes up with these capabilities, there is an awareness gap, not just with buyers, but at times, even with existing owners. We plan on making these more visible in our interactions with both existing and future customers. Automotive margins improved quarter over quarter as a result of a 50 features released discussed before. Increase in our overall production and delivery volume, albeit benefit from the marketing pricing, and more localized deliveries in region, which resulted in lower freight and duties. Sustaining these margins in Q4, however, will be challenging given the current economic environment. Note that we are focused on the cost per vehicle, and there are numerous work streams within the company to squeeze that cost without compromising on customer experience.
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EM
Elon MuskCEOTesla
Yes.
I'm assuming that's a helpful — hopefully, a helpful macro trend is if there's a decline in in interest rates, this has a massive effect on the, automotive demand. The vast majority of people is or the demand is driven by the monthly payment. Can they put monthly payment? So, like, most likely, we'll see continue to decline interest rates, which helps with affordability vehicles.
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VT
Vaibhav TanejaCFOTesla
Yeah. I mean, that is one trend which we observed in the industry that, because of affordability being impacted because of interest rates, People are willing to take cars longer, especially in the U.S. And that is actually having an impact on all our industry too. As we discussed, earlier, as we discussed impact orders, energy deployments fluctuate quarter over quarter due to customer readiness, location of orders being fulfilled, and not necessarily an indicator of demand or production within the quarter.
While we did see a decline in Q3, we expect to grow our deployment sequentially in Q4 to end the year with more than doubled of last year. Energy margins in Q3 were a record at more than 30%. This is a function of mix of projects being deployed in the quarter. Note that there will be fluctuation in margins as we manage through deployments and our inventory. Our pipeline and backlog continue to grow quarter over quarter as we fill our 2025 production slots, and we're doing our little best to keep up with the demand. Just coming back on automotive margins, I talked about — sorry. I talked about what is happening. One other thing which I want to also share is that we're — that we will continue to keep whatever we can to squeeze like I said before about squeezing out the cost. But this is something which we also are very capable of. I mean, just in Q3, we reached our lowest cost per micro. And that is a trend which we will keep focus on. Then going on to service and other, we continue to show improvements in Q3. This was a result of better performance, both in our service business, which includes collision part sales and merchandise, and continued growth in supercharging. These field based revenues will continue to grow as the overall fleet size increases. Our operating expenses declined quarter over quarter in a year on year basis. This is partially due to the restructuring we undertook in Q2. Cost savings from these initiatives were partially offset by increase in costs related to our AI efforts. We've started using the GPU cluster based out of our factory house and ahead of schedule, and are on track to get 50k GPUs deployed in Texas by the end of this month. One thing which I'd like to elaborate is that we're being very judicious on our AI compute spend too and saying how best we can utilize the existing infrastructure before making further investments. On the CapEx front, we had about $3.5 billion in the quarter. This was a sequential increase largely because of investments in AI compute. We now expect our CapEx for the year to be in excess of $11 billion.
We shared our vision for the future at the real world event at the beginning of the month. The Tesla team is hyper focused on delivering on that version, and all efforts are underway to make it a reality. While we've achieved significant progress this year, it will take time to get this as we find a new and incredibly complex technologies and navigate a fragmented regulatory landscape. Future is incredibly bright, and I want to thank the Tesla team once again for all their help.
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Q&A Session
Q&A 1/2
TA
Travis AxelrodirTesla
Great. In the last few minutes that we have left, we will try to get in some analyst questions. The first question will be coming from, Pierre Ferragu at New Street. Pierre, please feel free to unmute yourself.
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PF
Pierre FerraguanalystNew Street
Thanks a lot, guys, for taking my question.
I was wondering about, like, the compute you're, you're ramping up. So you gave, like, interesting statistics on how much you have, and you said you don't feel your compute's constrained. And I was wondering, how you are putting to work this additional compute. Is that a game for you of creating, like, larger and larger models, like next generation of models that are larger the way OpenAI go from GPT-3 to GPT-4, or is that more like you're set on your model and you need to throw more and more compute to accelerate the pace of learning to improve reliability. And then I had a quick follow-up really quick on your rollout in Texas and in California next year. The plan as you see today, is it to roll out, like, a fleet or two, with, cars that will start with, like, a supervisory, like, some soup onboard supervision, someone, sitting at the wheel just in case and removing the supervisors progressively, or are you aiming for going, free fledged without even a human super supervisor when you get started?
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EM
Elon MuskCEOTesla
Okay. Well, I guess we're going to I'll answer, yeah, the first part of the question.
The nature of real world AI is, different from, say, an LLM in that, you have a massive amount of context. So that, like, the you've got, case of Tesla 7 or 8 cameras, that, 9 up to 9 if you include the internal camera that that that so you got gigabytes of context, and that that is then distilled down into a small number of control outputs. Whereas it's like you don't really it's very rare to have in fact, I'm not sure any LLM out there who can do gigabytes of context. And then you've got to then process that in the car with a very small amount of compute power. So, it's all doable and it's happening, but it is a different problem than what, say, a Gemini or OpenAI is doing. And now part of the way you can make up for the fact that the inference computer is quite small is by spending a lot of effort on training.
And just like a human, like, you the more you train on something, the less mental workload it takes when you try to — when you do it, like when the first time like a driving it absolves your whole mind. But then as you train more and more on driving different than the driving becomes a background task. It doesn't — it only solves a small amount of your mental capacity because you have a lot of training.
So we can make up for the fact that the insurance computers — it's tiny compared to a 10-kilowatt bank of GPUs because you've got a few hundred watts of inference compute. We can make up that with heavy training. So yeah, that's — and then there's also vast amounts to the actual petabytes of data coming in tremendous. And then sorting out what training is important of the vast amounts of video training video data coming complete what is actually most important for trading. That's quite difficult. But as I said, we're not currently training compute constraint. — had you want levering
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AE
Ashok ElluswamyexecutiveTesla
Like you mentioned, the training has both an large models, also the trend quicker. But in the end, we still got to take which models are performing better. So the validation network to picking the models because as mentioned this pretty large.
We had to drive a lot of miles going close to. We do have simulation and other ways to get those metrics. Those two help, but in the end, that's a big bottleneck. That's why we're not trying to compete constraint alone. And there's other access of scaling as well, which is a data figuring office as more useful. That is an important as focusing on that.
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UR
Unidentified Company RepresentativeexecutiveTesla
Yeah.
So as it relates to the second part of your question, Pierre, about safety drivers and rolling it out. Each state has different requirements in terms of how many miles and how much time you need to have a safety driver and not have a safety driver. We're going to follow all those were not regulations are out there. But safety is a priority. But the goal is obviously at when we're ready and safety is there, we'll address from the —
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EM
Elon MuskCEOTesla
Yeah. I mean, I guess like we think that we'll be able to have driverless Teslas during paid rides next year, sometime next year.
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Q&A 2/2
TA
Travis AxelrodirTesla
All right. Thank you. And our next question comes from Adam Jonas at Morgan Stanley. Adam, please feel free to unmute yourself.
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AJ
Adam JonasanalystMorgan Stanley
Okay, thanks, everybody.
I just had a question about the relationship between Tesla and xAI. Many investors are still not clear how the work at xAI is truly beneficial to Tesla. Some even take the view that the two companies may even be in competition with each other in terms of talent and tech and even your time, Elon. So what's your message to investors on that relationship between Tesla and xAI? And where do you see it going over time?
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EM
Elon MuskCEOTesla
Well, I should say that xAI has been helpful to Tesla AI quite a few times in terms of things like scaling it, bought it, like training, just even like recently in the last week or so, improvements in training, where if you're doing a big training one and it fails, be able to continue training and is to recover from a training on has been pretty helpful. But it but there are different problems. xAI is working on artificial general intelligence or artificial super intelligence. Tesla's trying to make autonomous cars and autonomous robots. They're different problems. So, yeah. I mean —
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AE
Ashok ElluswamyexecutiveTesla
I think we've said this before also. Like, all not all AI is equal. Right? I mean, there's AI is a broad spectrum. And we have our own swim lanes. Here, there are certain things which we can collaborate on if needed, but for the most part, we're solving different issues.
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EM
Elon MuskCEOTesla
Yeah. Tesla's focus on real world data. And like I said, saying it is quite a bit different from an element. Because, like, you have you have massive context in the form of video and some other audio, that's going to be distilled very like, with extremely efficient advanced compute. I do think Tesla's the most efficient, in the world in terms of inference compute. Like, because out of necessity, we have to we have to be very good at in in efficient inference. We can't pretend 10 kilowatts of GPUs in a car.
We've got a couple 100 watts. So, it's pretty well designed Tesla AI chip, but it's still a couple 100 ones. But there are different problems.
I mean, this is, like, the stuff that I said is, like, we're going to running in burns. I mean, it's it is running in burns. Like, answering persons, answering questions on a 10 kilowatt rack. It's like, yeah. Put that in the car. It's a different file. No. Exactly. So, xAI is because I felt there wasn't there wasn't a truth seeking digital super intelligence company out there. Like, that's what it came down to. Like, they needed to be a truth seeking like, an AI company that is very rigorous about, being truthful. So I'm not saying xAI is perfect, but that is but that is at least the explosive aspiration. Even if something is politically incorrect, it should still be truthful. I think this is very important for AI safety. So anyway, I think AI, xAI will it has been helpful to Tesla and will continue to be helpful to Tesla, but they are very different problems. Great.
And, I mean, like, if you it also thinking like, what is like, what other car company has that — has a world class trip design team? Like 0. What other car company has a world class AI team like Tesla does? 0. Those were all startups. They're created from scratch.
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Closing Remarks
TA
Travis AxelrodirTesla
Great.
Thank you, Elon. And I think that's unfortunately all the time that we have for today. We appreciate all of your questions, and we look forward to hearing you next quarter. Thank you very much and goodbye.
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