My name is Martin Vieja, VP of Industrial Relations and I'm joined today by Elon Musk, Vibaf Danecia and a number of other executives. Our Q1 results were announced at about 3 PM 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 and results could differ materially due to a number of risk 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. But before we jump into Q&A, Elon has some opening remarks. Elon? Thanks, Martin. So to recap, in Q1, we navigated several unforeseen challenges, as well as the ramp for the updated Model 3 and Fremont. There was, as people have seen, the EV adoption rate globally is under pressure and a lot of other water manufacturers are pulling back on EVs and pursuing plug-in hybrids instead. We believe this is not the right strategy, and electric vehicles will ultimately dominate the market. Despite these challenges, the Tails team did a great job executing a tough environment and energy storage deployments for MegaPAT in particular, reaching all-time high in Q1, leading to record profitability for the energy business. And that looks likely to continue to increase in the quarters and years ahead. It will increase. We actually know that it will. So significantly faster than the car business, as we expected. We also continue to expand our AI training capacity in Q1 more than doubling our training compute, sequentially. In terms of the new product roadmap, there's been a lot of talk about our upcoming vehicle line in the past several weeks. We've updated our future vehicle line up to accelerate the launch of new models ahead, previously mentioned start of production in the second half of 2025.
We expect it to be more like the early 2025, if not late this year. These new vehicles, including more affordable models, will use aspects of the next generation platform as well as aspects of our current platforms, and will be able to produce on the same many factoring lines as our current vehicle lineup. So it's not contingent on any new factory or massive new production line. It'll be made on our current production lines much more efficiently. And we think this should allow us to get to over three million vehicles of capacity when realized the full extent. Regarding FSD version 12, which is the pure AI based self-driving, if you haven't experienced this, I strongly urge you to try it out. It's profound.
The rate of improvement is rapid. So we've now turned that on for all cars with the cameras and in first computer, everything from hardware three in North America. So it's been pushed out to around 1.8 million vehicles. And we're seeing about half of people use it so far. And that percentage is increasing with each passing week. So we now have over 300 billion miles that have been driven with FSD V12. Since the launch of full self-driving, supervised full self-driving, it's become very clear that the vision-based approach with end-to-end neural networks is the right solution for scalable autonomy. And it's really how humans drive. Our entire road network is designed for biological neural nets and eyes. So naturally, cameras and digital neural nets are the solution to our current road system. To make it more accessible, we've reduced the subscription price to $99 a month so it's easy to try out.
And as we've announced, we will be showcasing our purpose-built robot taxi or cybercap in August. Regarding AI compute, over the past few months, we've been actively working on expanding Tesla's core AI infrastructure. For a while there, we were training constrained in our progress. We are at this point no longer training constrained, and so we're making rapid progress. We've installed and commissioned, meaning they're actually working 35,000 H100 computers or GPUs. And GPU is wrong with, they need a new word. I always feel like a wince when I say GPU because not GPUs, that's G-central graphics, into new graphics. But roughly 35 plus H100 is proactive.
And we expect that to be probably 85,000 or they're about by the end of this year. And training, just for training. We are making sure that we're being as efficient as possible in our training. It's not just about the number of H100s but how efficiently they're used. So in conclusion, we're super excited about our autonomy road map and get it to be obvious to anyone who's driving version 12 and a Tesla that is only a matter of time before we exceed the reliability of humans and not much time at that. And we're really headed for an electric vehicle, an autonomous future. And I'll go back to something I said, so over years ago, that in the future, gasoline cars that are not autonomous will be like riding a horse and using a flip-boat. And that will become very obvious in hindsight. We continue to make the necessary investments that will drive the growth and profits will test in the future. And I wanted to thank the Tesla team for incredible execution during this period and look forward to everything that we have planned ahead. Thanks. Thank you very much. And I'll buy back to some comments as well. Thanks. You know, it's important to acknowledge what Elon said from our auto business perspective.
We did see a decline in revenues quarter over quarter. And those were primarily because of seasonality on certain macroeconomic environment and the other reasons which Elon had mentioned earlier. Auto margins declined from 18.9 to 18.5%, excluding the impact of Cybertruck. The impact of pricing actions was largely offset by reductions in per unit costs and the recognition of revenue from automotive feature for certain vehicles in the US that previously did not have that functionality. Additionally, while we did experience higher costs due to the ramp of Model 3 and Fremont and disruptions in Berlin. These costs were largely offset by cost reduction initiatives. In fact, if we exclude Cybertruck and Fremont and Fremont Model 3 ramp costs, the revenue from auto park auto margins improved slightly. Currently, normalized model by cost per vehicle in Austin and Berlin are already very close to that of Fremont. Our ability to reduce costs without sacrificing on quality was due to the amazing efforts of the team in executing Tesla's relentless pursuit of efficiency across the business.
我们确实看到了季度收入下降。主要是因为某些宏观经济环境的季节性和埃隆之前提到的其他原因。汽车利润率从18.9%下降到18.5%,不包括Cybertruck的影响。定价行动的影响主要被单位成本的降低和以前没有该功能的美国某些车辆的汽车功能收入的认可所抵消。此外,由于Model 3和Fremont的推出以及柏林的中断,我们确实经历了更高的成本。但这些成本在很大程度上被成本削减举措所抵消。事实上,如果我们排除Cybertruck和Fremont以及Fremont Model 3推出的成本,汽车利润率略有改善。目前,奥斯汀和柏林的车辆成本归一化模型已经非常接近Fremont的水平。我们在不牺牲质量的情况下降低成本的能力归功于团队在执行特斯拉对整个业务高效率不懈追求的惊人努力。
We've also witnessed that as other OEMs are pulling back on their investments in EV, there is increasing appetite for credits. And that means a steady stream of revenue for us. Obviously, seeing others pull back from EV is not the future we want. We would prefer it the whole industry went all in. On the demand front, we have undertaken a variety of initiatives, including lowering the price of both the purchase and subscription options for FSD, launching extremely attractive leasing specials for the Model 3 in the US for $2.99 a month and offering attracting financing options in certain markets. We believe that our awareness activities paired with attractive financing will go a long way in expanding our reach and driving demand for our products. That energy business continues to make meaningful progress with margins reaching a record of 24.6%.
We expect the energy storage deployments for 2024 to grow at least 75% higher from 2023. And accordingly, this business will begin contributing significantly to our overall profitability. Note that there is a bit of lumpiness in our storage deployments due to a variety of factors that are outside of our control, so deployments may fluctuate quarter over quarter. On the operating expense front, we saw a sequential increase from our AI initiatives, continued investment in future projects, marketing and other activities. We had negative free cash flow of $2.5 billion in the first quarter. The primary driver of this was an increase in inventory from a mismatch between bills and deliveries, as discussed before. And our elevated spend on capex across various initiatives, including AI compute. We expect the inventory built to reverse in the second quarter and free cash flow to return to positive again.
As we prepare the company for the next phase of growth, we had to make the heart, but necessary decision to reduce our head count by over 10%. The savings generated are expected to be well in excess of $1.1, excess of $1 billion on an annual London basis. We are also getting hyper-focus on capex efficiency and utilizing our install capacity in a more efficient manner. The savings from these initiatives, including our cost reductions, will help improve our overall profitability and ultimately enable us to increase the scale of our investments in AI. In conclusion, the future is extremely bright and the journey to get there while challenging will be extremely rewarding. Once again, I would like to thank the whole Tesla team for delivering great results and we can open it up to Keona. Thank you.
Okay. Let's start with the investor Keona name. The first question is, what is the status of 4680? What is the current output? Mars? Sure. 4680 production increased about 18-20% from Q4 reaching greater than 1K a week for cyber truck, which is about 7 gigawatt hours per year as we posted on X. We expect to stay ahead of the cyber truck ramp with the cell production throughout Q2 as we ramp the third of four lines in phase one while maintaining multiple weeks of cell inventory to make sure we're ahead of the ramp. Because we're ramping, colleagues continue to drop rapidly week over week, driven by yield improvements throughout the lines, and production volume increases. So our goal and we expect to do this is to beat supplier costs of nickel-based cells spending into here. Thank you.
The second question is on optimus. So what is the current status of optimus? Are they currently performing any factory tasks? When do you expect to start mass production? We are able to do simple factory tasks, or at least I should say factory tasks in the lab. The, in terms of actually, we do think we will have optimus in limited production in the factory, in the actual factory itself, doing useful tasks before the end of this year. And then I think we may be able to sell it externally by the end of next year. These are just gases. As I've said before, I think optimus will be more valuable than everything else combined. Because if you've got a sentient humanoid robot that is able to navigate reality and do tasks at request, there is no meaningful limit to the size of the economy. So that's what's going to happen. And I think Tesla is best positioned of any humanoid robot maker to be able to reach volume production with efficient inference on the robot itself. I mean, this perhaps is a point that is worth emphasizing. Tesla's inference, AI inference efficiency is vastly better than anyone, any other company. There's no company even close to the inference efficiency of Tesla. We've had to do that because we've constrained by the inference hardware in the car. We'd never choice. But that will pay dividends in many ways. Thank you.
The third question is, what is the first current assessment of the pathway towards regulatory approval for unsupervised FSD in the US? And how should we think about the appropriate safety threshold compared to human drivers? Sure, I can start. There are a handful of states that already have adopted autonomous vehicle laws. These states are paving the way for operations. Well, the data for such operations guides a broader adoption of driverless vehicles, I think a show can talk a little bit about our safety methodology, but expect that these states and the work ongoing, as well as the data that we're providing, will pave a way for a broad-based regulatory approval. In the US, at least in other countries, as well. Yeah. It's actually been pretty helpful that other autonomous car companies have been cutting a path through the regulatory jungle. But that's actually quite helpful. And they have obviously been operating in the temperatures go for a while. I think they got approval for City of LA. So these approvals are happening rapidly. I think if you've got at scale, it's a statistically significant amount of data that shows conclusively that the autonomous car has, let's say, half the accident rate of a human-driven car.
I think that's difficult to ignore because at that point, you're stopping autonomy means killing people. So I actually do not think that there will be significant regulatory barriers provided there's conclusive data that the autonomous car is safer than a human-driven car. And in my view, this would be much like elevators. Elevators used to be operated by a guy with a relay switch. But sometimes a guy would get tired or drunk or just make a mistake and share somebody in half between floors. So now we just get an elevator and press button. We don't think about it. In fact, it's kind of weird if somebody is standing there with a relay switch. That'll be how cars work. You just summon a car using your phone. You get in. It takes you to your destination. You get out. You don't even think about it. You don't even think about it. Just like an elevator. It takes you to your floor. That's it. Think about how the elevator is working or anything like that.
And something I should clarify is that Tesla will be operating the fleet. So you can think of how Tesla, I think it has an un-resum combination of Airbnb and Uber, meaning that there will be some number of cars that Tesla owns itself and operates in the fleet. There'll be some number of cars and then there'll be a bunch of cars where they're owned by the end user. But that end user can out or subtract their car to the fleet whenever they want. And they can decide if they want to only let the car be used by friends and family or only by five-star users or by anyone. At any time they could have the car come back to them and be exclusively theirs, like an Airbnb. You could rent out your guest room or not anytime you want. So as our fleet grows, we have 9 million cars going to eventually 10s of millions of cars worldwide. With a constant feedback loop, every time something goes wrong, that gets added to the training data and you get this training flywheel happening in the same way that Google Search has the flywheel. It's very difficult to compete with Google because people are constantly doing searches and clicking and Google's getting that feedback loop. It's the same with with Tesla. But at a scale that is maybe difficult to comprehend, but ultimately it would be 10s I think there's also some potential here for an AWS element down the road where if we've got very powerful inference, because we've got a hardware 3 in the cars, but now all cars are being made with hardware 4. 5 is pretty much designed and should be in cars, hopefully towards the end of the next year.
And there's a potential to run when the car is not moving to actually run distributed inference. So kind of like AWS, but distributed inference. It takes a lot of computers to train an AI model, but many orders of magnitude less compute to run it. So if you can imagine a future path where there's a fleet of 100 million Teslas and on average they've got like maybe a kilowatt of inference compute that's 100 gigawatts of inference compute distributed all around the world. It's pretty hard to put together 100 gigawatts of AI compute. And even in an autonomous future where the car is path used instead of being used 10 hours a week is used 50 hours a week. That still leaves over 100 hours a week where the car inference computer could be doing something else. And it seems like it will be a waste not to use it.
Actually, do you want to try on the process in safety? Yeah, we are with multiple tier stop validating the safety. For like in any given week between hundreds of neural networks that can produce, you know, different trajectories for how to drive the car, they pay them through the millions of clips that we have already collected from our users and our own QA. Those are like critical events, you know, like someone jumping out in front or like other critical events that we have gathered database over many, many years. And we deeply through all of them to make sure that we are net improving safety. And then of it, we have simulation systems that also try to recreate this and test this in close to fashion. Once all of this is evaluated, we give it to our own QA records. We have hundreds of them in different cities in San Francisco, Los Angeles, Austin, New York, a lot of different locations.
They are also driving this collecting real world miles and we have an estimate of what are the critical events. Are they net improvement compared to the previous weeks bills? And once we have confidence that the bill is a net improvement, then we start shipping to early users like 2000 employees initially that they would like get the bill, they will give feedback on like if it's an improvement or they're noting some new issues that we did not capture in our own QA process. And only after all of this is validated, then we go to external customers. And even when we go external, we have like live dashboards of monitoring every critical event that's happening in the fleet, sorted by the criticality of it. So we are having a constant pulse on the bill's quality and the safety improvement along the way.
And then any failures like you don't want to get the data back added to the training and that improves the model in the next cycle. So we have this like constant feedback loop of issues, fixes, evaluations, and then it rinse and repeat. And especially with the new virtual architecture, all of this is automatically improving without requiring much engineering interventions in the sense that people, engineers don't have to be creative in like how they code the algorithms. It's mostly learning on its own based on data. So you see that, okay, we failure or like this is how a person chooses how you drive this intersection or something like that. They get the data back. We add it to the new network and it learns from that training that automatically instead of some engineers saying that, oh, here you must rotate the steering wheel by the smart engine or something like that.
There's no hardy first ambitions. It's everything is a neural network. It's very soft. It's probabilistic. And so it's probably a problem distribution based on the new data that it's getting. Yeah. And we do have some insight into how good the things will be and like let's say three or four months because we have advanced models that are former capable than what is in the car but have some issues with them that we need to fix. So they're like there'll be a step change improvement in the capabilities of the car but it'll have some quirks that need to be addressed in order to release it. As I was saying, we have to be very careful in what we release the fleet or to customers in general.
So like we're looking to say 12.4 and 12.5 which are really could arguably even be version 13 and version 14 because it's pretty close to a total retrain of the neural nets in each case or substantially different. So we have good insight into where the models, how well the car will perform in say three or four months. I'm sorry, scaling in the air community. We're going to talk about model scaling in the model size a lot and then they have corresponding gains in performance but we have also figured out scaling loss and other access in addition to the model size scaling. You can also data scaling.
You can increase the amount of data you use to train the neural network and that also gives similar gains and you can also scale up by training compute. You can train it for much longer and got more GPUs or more dojo notes and that also gives better performance and you can also have architecture scaling where you come with better architectures that for the same amount of compute produce better results. So a combination of model size scaling, data scaling, training compute scaling and the architecture scaling.
We can basically extract like okay, if the country is scaling based on this ratio we can sort of predict future performance. Obviously it takes time to do the experiments because it takes few weeks to train. It takes few weeks to collect tens of millions of video clips and process all of them but you can estimate what is going to be the future progress based on the trends that we have seen in the past and they've generally helped through based on the past data. Okay, thank you very much.
Let's go to the next question which is can we get an official announcement of the timeline for the $25,000 vehicle? I think we, Elon mentioned it in the opening remarks but as you mentioned we're updating our future vehicle line up to accelerate the launch of our low-cost vehicles in a more cap, a sufficient way. That's our mission to get the most affordable cars to customers as fast as possible. These new vehicles we built on our existing lines and open capacity and that's a major shift to utilize all our capacity with marginal cap X before we go spend high cap X to do this.
Yeah, we'll talk about this more and I'll just say so. I mean really the way to think of Tesla is almost entirely in terms of solving autonomy and being able to turn on that autonomy for a gigantic fleet. And I think it might be the biggest asset value appreciation in history when that thing happens, when you can do unsupervised, full self-driving. High-million cars? Yeah. A little less. As long as I'm going, it'll be 7 million cars. You know, in a year or so. And then 10 million and then, you know, eventually we're talking about 10 to millions of cars.
I'm not eventually, it's like, the point of this decade, it's several times the money to cars. Thank you. The next question is, what is the progress of Cybertruck round? I can take that one too. I can take it one day a week, just a couple weeks ago. This happened in the first four to five months since we SOP late last year. Of course, volume production is what matters. That's what drives costs and so our costs are dropping. But the ramp still faces like a lot of challenges with so many new technologies, some supplier limitations, et cetera, and will continue to ramp this year just focusing on cost efficiency and quality. Okay. Thank you.
The next question, have any of the legacy automakers contacted Tesla about possibly licensing FSD in the future? We're in conversations with one major or to make a regarding licensing FSD. Thank you. The next question is about the robot taxi and Vail Elon already talked about that. So we'll have to wait till August. The following question is about the next generation vehicle. We already talked about that. So let's go to the semi. What is the timeline for scaling semi? I think it's awesome.
So we're finalizing the engineering of the semi to enable a super cost-effective high-volume production with our learnings from our fleet and pilot fleet and Pepsi's fleet, which we're expanding this year marginally. In parallel, as we showed in the shareholders' deck, we have started construction on the factory in Reno. Our first vehicles are planned for late 2025 with external customers starting in 2026. Couple more questions. So our favorites. Can we make FSD transfer permanent until FSD is fully delivered with level five? No. Okay. Next question. What is the getting the production ramp at Lathrop?
Where do you see the megabec run rate at the end of the year? Mike? Yeah. Yeah, Lathrop is ramping as planned. We have our second GA line allowing us to increase our exit rate from 20 gigawatt hours per year to at the start of this year to 40 gigawatt hours per year by the end of the year. That line's commissioned. There's really nothing limiting the ramp. So it's, you know, given the longer sales cycles for these large projects, we typically have order visibility 12 to 24 months prior to ship date.
So we're able to plan, to build plan several quarters in advance. So this allows us to ramp the factory to align with the business and order growth. Lastly, we'd like to thank our customers globally for their trust and Tesla as a partner for these incredible projects. Okay. Thank you very much. Let's go to Annalise questions. The first question comes from Tony Sakunagi from Bernstein. Tony, please go ahead and unmute. Thank you for taking the question. I was just wondering if you could elaborate a little bit more on kind of the new vehicles that you talked about today. Are these like tweaks on existing models, giving that they're going to be running on the same lines or these like new models? And how should we think about them, you know, in the context of like the Model 3 Highland update?
What will these models be like relative to that? And given the quick timeframe, you know, Model 3 Highland is required a lot of work and a lot of retooling. Maybe you can help put that all in context. Thank you. And I have a follow up, please. I think we've said all we well on that front. So what's your follow up? It's a more personal one for you, Elon, which is that you're leading many important companies right now. Maybe you can just talk about where your heart is at in terms of your interests and to expect to lessen your involvement with Tesla at any point over the next three years. Well, as a constitutional majority of my work time and I work pretty much every day of the week, it's for me to take a study off and you're not after noon.
So I can make sure Tesla is quite prosperous and it is like it is prosperous and it will be very much so in the future. Okay, thank you. Let's go to Adam Jonas from Morgan Stanley. Adam, please go ahead and unmute. Okay, great. Hey, Elon, so you and your team on volume expect a 2020 growth rate notably lower than that achieved in 2023. But what's your team's degree of confidence on growth above 0% or in other words, does that statement leave room for potentially lower sales year on year?
No, I think we'll have higher sales this year than last year. Okay. My follow up, Elon, on future product, if you had nailed execution, assuming that you nail execution on your next gen, cheaper vehicles, more aggressive gigacastings, I don't want to say one piece, but getting closer to one piece, structural pack, unboxed, three-mile range, $25,000 price point, putting aside Robotaxi, those features unique to you.
How long would it take your best Chinese competitors to copy a cheaper and better vehicle that you could offer a couple of years from now? How long would it take your best Chinese competitors to copy that? Thanks. I mean, I don't know what our competitors could do except we've done relatively better than they have. If you look at the drop in our competitors in China sales versus our drop in sales, our drop is less than theirs. So we're doing well.
But I think, you know, Kathy would set it best, like, really, we should be thought of as an AI robotics company. If your value tells us just like an order company, you would just have to fundamentally, is just the wrong framework. It will count to be. If you ask the wrong question, then the right answer isn't possible. So I mean, if somebody doesn't believe tells us it's going to solve autonomy, I think they should not be an investor in the company. That is, but we will, and we are. And then you have a car that goes from 10 hours a week, like an hour and a half a day to probably 50.
But it costs the same. I think that's the key thing to remember, like, especially if you look at FSD supervised, if you didn't believe in autonomy, they should give you a review that this is coming. It's actually getting better day by day. Yeah, if you've not tried the FSD, 4.3, and like I said, 4.4 is going to be significantly better and 4.5 even better than that. And we have a visibility into those things.
Then you really don't understand what's going on. It's not possible. Yeah, and that's why we can't just look at just as a car company because a car company would just have a car. But here we have more than a car company because the cars can be autonomous. And like I said, it's happening. Yeah, this is all an addition to Tesla, Sorkin. The oral AI community is just increasing, like, improving rapidly. Yeah, yeah, and we're putting the actual auto in automobile.
So, you know, we're like, well, sort of like, tell us about future horse carriages you're making. Well, actually, it doesn't need a horse. That's the whole point. That's really the whole point. OK, thank you. The next question comes from Alex Potter from Piper Sandler. Alex, please go ahead and unmute. Great. Thanks. Yeah, so couldn't agree more. The thesis hinges completely on AI, the future of AI, also of driving, you know, neural net training, all of these things. In that context, Elon, you've spoken about your desire to obtain 25% voting control of the company. And I understand completely why that would be. So I'm not necessarily asking about that. I'm asking if you've come up with any mechanism by which you can ensure that you'll obtain that level of voting control because if not, then the core part of the thesis could potentially be at risk. So any additional commentary you might have on that topic? Well, I think no matter what, even if I cannot buy aliens tomorrow, Tesla will solve autonomy, maybe a little slower, but it would solve autonomy for vehicles at least. I don't know if it would win it on with respect to optimists or with respect to future products, but it would, that there's not momentum for Tesla to solve autonomy, even if I disappeared for vehicles. Now, this is a whole range of things we can do in the future beyond that. I'd be more reticent with respect to optimists. If we have a super sentient humanoid robot that can follow indoors and that you can't escape, you know, to a terminator level risk, then yeah, I'd be uncomfortable with, you know, if there's not some meaningful level of influence over how that is deployed. And you know, if there's, you know, shareholders have an opportunity to ratify or re-ratify the sort of competition, I guess I can't say that. But that is a fact, they have an opportunity.
Okay. Very good. And yeah, we'll see. If the company generates a lot of positive cash flow, we get up to see buyback shares. All right, that's actually all very helpful context. Thank you. Maybe one final question, I'll pass it on. Op-ex reductions, thank you for quantifying the impact there. I'd be interested also in potentially more qualitative discussion of what the implications are for these headcount reductions. What are the types of activities that you're presumably sacrificing as a result of parting ways with these folks? Thanks very much. So, you know, like we said, we've done these headcount reductions across the board. And you know, as companies grow over time, you know, there are certain redundancies, there's some duplication of efforts which happens in certain areas. So you need to go back and look at where all these pockets are, get rid of it. So we're basically going through that exercise wherein we're like, hey, how do we set this company right for the next phase of growth? And the way to think about it is, you know, any tree which grows, it needs pruning. This is the pruning exercise which we went through. And at the end of it, we'll be much stronger and much more resilient to deal with the future because the future is really bright. Like I said in my remarks, we just have to get through this period and get there. Yeah, we're not giving up anything that is significant that I'm aware of.
So we've had a long period of prosperity from 2019 to now. And you know, so if a company sort of organizationally is 5% wrong per year, you know, that accumulates to 25, 30% of inefficiency. We've made some corrections along the way, but it is time to reorganize the company for the next phase of growth. And you really need to reorganize it just like a human when we start off with one cell and come as I go and blast assist and you start growing arms and legs and briefly you have a tail. And so. But you shut the tail. Shut the tail, hopefully. And then your baby, you know, you have to be different. The organism, a company is kind of like a creature growing. And if you don't reorganize it for different phases of growth, it will fail. You can't have the same organizational structure if you're, you know, 10 cells versus 100 versus a million versus a billion versus a trillion. You know, where humans are like around 35 trillion cells, it doesn't feel like it feels like, you know, like one person, but you know, you're basically a walking cell colony of roughly 35 trillion depending on your body mass. And about three times that number in bacteria. So anyway, you've got to reorganize the company for a new phase of growth or it will fail to achieve that growth. Thank you. Let's go to Mark Delaney from Goldman Sachs.
Mark, please go ahead and unmute. Yes, good afternoon. Thanks very much for taking the question. The company had previously characterized potential FSD licensing discussions as in the early phase and some OEMs had not really been believing in it. Can you elaborate on how much the licensing business opportunity you mentioned today has progressed? And is there anything Tesla needs to achieve with the technology in terms of product milestones in order to be successful at reaching a licensing agreement in your view?
But I think we just need to, it just needs to be obvious that our approach is the right approach. And I think it is, I think we're now with 12.3, if you just have the car drive you around, it is obvious that our solution with a relatively low cost inference computer and standard cameras can achieve self-driving. No LiDARs, no radar, no ultrasonic, nothing. No having integration work for vehicle manufacturers. Yeah, so really just be a case of having them use the same cameras and inference computer and licensing our software. And it's once it becomes obvious that if you don't have this in a car, nobody wants your car.
Yeah, it's like it's a smart car. I mean, I just remember like the fact that Nokia was King of the Hill, yeah, and self-driving and self-driving and I sort of come out with a smartphone that was basically a brick with limited functionality. And then the iPhone and Android, if people sold it not to understand that all the phones are going to be that way. There's not going to be any flip phones, if they'll be in each product or home phones. Yeah, not even exactly. It was the last time you saw a home phone. I've no idea. Yeah, in a hotel, sometimes in a hotel. Yeah, the hotels have them.
So the people don't understand all cars will need to be smart cars or you will not sell. This car will not, nobody will buy it. Once that becomes obvious, I think licensing becomes not optional. It becomes a method of survival. Yeah, it's licensed at order to buy your car. I mean, one other thing which I'll add is in the conversations that you have had with some of these OEMs. I just want to also point out that they take a lot of time in the product lifecycle. Yeah. They're talking about years before they will put it in their product. We might have a licensing deal earlier than that, but it takes a while. So this is where the big difference between us and them is.
Yeah, I mean, really, a deal sign now would result in it being in a car in probably three years. Yeah, that's like lightning. So that's being eager. Oh, yeah. So I would be surprised if we do sign a deal. I think we're good chance we do sign a deal this year. Maybe more than one. But yeah, it would be probably three years before it's integrated with a car, even though all you need is cameras and our first computer. So it's like not a massive design change.
Yeah. And again, just to clarify, it's not the work which we have to do. It's the work which they have to do with the time. Mark, very helpful. Yeah, yeah. Yeah, very helpful. Thank you. My follow up was to better understand Tesla's approach to pricing going forward. Previously, the company had said that the price reductions were driving a criminal demand with how affordable the cars have become, especially for vehicles that have access to their rate credits and some of the leasing offers that Tesla has in place. You still see meaningful incremental price reductions as making sense from here for the existing products. And can the company immediately lower prices from here and also stay free cash or positive on an annual basis with the current products? Thanks.
Yeah, I think we can be free cash or positive, meaningfully. Yeah. The things I've offset it is opening remarks. Like our cost down efforts, we basically were offsetting the price kind of thing. So it's going to go like we're trying to give it back to the customers. Yeah, I mean, the other day, like for any given company, if you sell a great product at a great price, if you have a great product at a great price, the sales will be excellent. That's true of any arena. So over time, we do need to keep making sure that it's a great product at a great price. And moreover, that price is accessible to people. So you have to solve both the value for money and the fundamental affordability question.
The fundamental affordability question is sometimes overlooked. If somebody's earning several hundred thousand dollars a year, they don't think of a car from a fundamental affordability standpoint. For the vast majority of people are living paycheck to paycheck. So it actually makes a difference if the cost per month for lease or financing is $10 one way or the other. So it is important to keep improving the affordability and to keep making the price more accessible. Yeah, exactly. The price more accessible, the value for money better, and to keep improving out of a time. But also the main kick-ass coach. The people want to buy? Yeah, it's going to be a great product at a great price. And the standards for what costs to a great product at a great price keep increasing. So you can't just be static. You have to keep making the car better, improving the price of it, improving the cost of production. And that's what we're doing.
Yeah, and in fact, like I said in my opening remarks also, the updated Model 3 is a fantastic card. I don't think people fully even understand that a lot of engineering effort which has gone in larger than team have actually put out videos explaining how much the car is different. When it looks and feels different, not only looks and feels different, we've added so much value to it. But you can lease it for as low as $2.99 a month. Yeah. Without gas. Yeah. All right, the next question, Councillor George from Canacorte. George, please go on and unmute. Hi, thank you for taking my question. First, can you please help us understand some of the timing of launching FSD in additional geographies including maybe clarifying your recent comment about China? Thank you. I mean, like new markets, yeah, we are. There are a bunch of mocks where we don't currently sell cars that we should be selling cars in. We'll see some acceleration of that. And FSD in new markets? Yeah, so the thing about the old, the anti-end neural net based autonomy is that just like a human, it actually works pretty well without modification in almost any market. So we plan on with the approval of the regulators releasing it as a supervised autonomy system in any market that will get regulatory approval for that, which I think includes China. So yeah, it's just like a human. You can go rent a car in a foreign country and you can drive pretty well. Obviously, if you're living in that country, you'll drive better. And so we'll make the car drive better in these other countries with countries specific training. But it can drive quite well almost everywhere. The basics of driving are basically the same everywhere. Not car is a car. It's a traffic, like road is a nice thing.
Yeah, I don't understand that it shouldn't have things normally. There are some road rules that you need to follow in China. It's you shouldn't cross over a solid line tool and change. New versus recommendation, I think. China, you get fine heavily if you do that. We have to do some reductions, but it's mostly smaller reductions, not like the entire change of stack or something like that. Yeah. Hey, George, do you have a follow-up? So my follow-up has to do with the first quarter deliveries. I'm curious as to whether or not you feel that supply constraints that you mentioned throughout the release impacted the results. Can you help us quantify that? Is that why you have some confidence in unit growth in 2024?
Yeah. I think we did cover this a little bit in the opening remarks too. Q1 had a lot of different things which were happening. So now, she was a big one, continuing pressure from the macroeconomic environment. We had attacks at our factory. We had let's see attacks. We're ramping model three, ramping model cybertruck. All these things are happening. It almost feels like a culmination of all those activities in a constrained period. And that gives us that confidence that, hey, we don't expect. These things to record. Yeah. We think Q2 will be a lot better. Yeah. It was just one thing after another. Yeah, it's crazy.
Yeah, exactly. It's just if you've got cars that are sitting on ships, they obviously cannot be delivered to people. And if you've got excess demand for model three and model one in one market, but you don't have it there, it's quite a little. It's a really complex logistics situation. So I'd say also we did overcomplicate the sales process, which we've just in the past a week or so have greatly simplified. So it just became far too complex to buy a Tesla. Whereas it should just be you can buy the car in under a minute. So we're getting back to that you can buy a Tesla in under a minute interface from what was quite complex. Okay. Thank you.
Let's go to Colin Rush from Oppenheimer. Colin, go ahead on mute, please. Thanks so much, guys. You know, given the pursuit of Tesla, it really is the leader in AI for the physical world. And your comments are around distributed inference. Can you talk about what that approach is unlocking beyond what's happening in the vehicle right now?
Do you want to say something? Yeah, I can't imagine like the car even when it's a full robot, actually, that's 40 gonna be used on 50 hours a week. That's my guess, like a third of the hours a week. Yeah, it could be more or less. But then there's certainly going to be some hours left for charging and cleaning and maintenance in that world. You can do a lot of other workloads. Even right now, we are seeing, for example, these alone companies have this bad workloads where they send much of documents and those are run through pretty large neural networks and take a lot of, you know, compute to chunk through those workloads.
And now that we already paid for this compute in these cars, it might be wise to use them and not let them be like buying a lot of expensive machinery and building them be like we don't want that. We'd want to use the compute as much as possible and close to like basically 100% of the time make it the use of it. That's right. I think it's analogous to Amazon Web Services where, you know, people don't expect that AWS would be the most valuable part of Amazon when it started out as a bookstore. So that was on nobody's radar. They found that they had excess compute because the compute needs would spike to extreme levels for brief periods of the year and then they had idle compute for the rest of the year. So then what should they do with all that excess compute for the rest of the year? That's kind of, yeah, monetizing. So it seems like kind of a no-brainer to say, okay, we've got millions and then tens of millions of vehicl...
...es out there where the computers are out almost the time that we might as well have them do something useful. Exactly. And then I mean, if you get like to the 100 million vehicle level, which I think we will at some point get to, then you've got a kilowatt of usable compute and maybe your own hardware 6 or 7 by that time, then you really, I think you did have on the order of 100 gigawatts of usable compute, which might be more than anyone, more than any company, probably more than any company.
Probably because it takes a lot of intelligence to drive the car anyway and when it's not driving the car, you just put this intelligence to other users to solving the scientific problems that you've given. Or answering them for some reason. We've already learned a lot of deploying workloads to these nodes. Yeah. And unlike laptops and our cell phones, it is totally under test as control. So it's easier to miss you with the work from across different nodes as opposed to, you know, asking users for permission on their own cell phones to be very tedious.
Well, you're just drained the battery on the phone. Yeah, exactly. The battery is also loaded. Like technically, I suppose like Apple would have the most amount of distributed compute, but you can't use it because you can't just run the phone at full power and drain the battery. Yeah. So whereas for the car, even if you're a kilowatt level inference computer, which is crazy power compared to a phone, you know, if you've got a 15 or 60 kilowatt hour pack, it's still not a big deal to run.
Right. With you plug in or not, you could run for 10 hours and use 10 kilowatt hours, a few kilowatt of compute forever. Yeah. We're going to build in liquid cold thermal management. Yeah, it's exactly the best for data centers. So it's already there in the car. Exactly. Yeah, it's distributed power generation. It's distributed access to power and distributed cooling. And it's already faithful. Yeah, I mean, that's distributed power and cooling people underestimate that cost a lot of money.
Absolutely. Yeah. And the capex is shad by the enter. Well, yes, sort of everyone wants to smell chunk and they get a small profit out of it. Yeah. Thanks so much, guys. And just my fault was a little bit more mundane. Looking at the 4680 ramp, can you talk about how close you are to target yields and when you might start to accelerate incremental capacity expansions on that technology? You know, we're making good progress on that. But I don't think it's super important for at least in the near term.
As Lars said, we think it will exceed the competitiveness of suppliers by the end of this year. And then we'll continue to improve it. Yeah, I mean, I think it's important to note also that the ramp right now is relevant to the cyber truck ramp. Yeah. And so we're not going to just randomly build 4680s, unless we have a place to put them. And so we're going to make sure we're prudent about that. But we also have a lot of investments with all our self suppliers and vendors. They're great partners and they've done great development work with us and a lot of the advancements in technology and chemistry we found in 4680, they're also putting into their cells. Yeah. I mean, big part of the 4680, what it tells us during the federal sales was a hedge against what would happen with suppliers. Because for a while there, it was very difficult because every big car maker put in massive battery orders. And so the price per kilowatt hour of lithium-ion batteries went to crazy numbers, to crazy levels. Bonkers.
Yeah, just bonkers. So like, okay, we've got to have some hedge here to deal with, you know, cost per kilowatt hours numbers that were double what we anticipated. If we have an internal cell production, then we have that hedge against a demand shocks, you know, with too much demand. That's really where you think about it. It's not like we want to take on a whole bunch of problems just for the hell of it. We did the cell program in order to address the crazy increase in cost per kilowatt hour from our suppliers due to gigantic orders placed by every car maker on Earth. So. Okay. Thank you. And the last question comes from Ben Calo from Baird. Ben, go ahead and unmute. And you're still muted. Well, I want to say again, we'd just like to strongly recommend that anyone who is, I guess, thinking about the Tesla stock should really drive FSD 12.3. You really, you can't, it's impossible to understand the company if you do not do this. All right. So since Ben is not unmuting, let's try Shre Espatil from Wealth Research. Final question.
Oh, hey, thanks so much. Just, you know, Elon, during the investor day last year, you mentioned that auto cogs per unit for the next gen vehicle would decline by 50% versus the current three and why. I think that was implying something around $20,000 of cogs. About a third of that was coming from the unbox manufacturing process. But I'm curious if you see an opportunity that the other, some of the other drivers around powertrain cost reduction or material cost savings, would those be largely transferable to some of the new products that you're, that you're now talking about, about introducing? Yeah, sure. I mean, in short, yes. I mean, like, you know, the unbox manufacturing method is certainly great and revolutionary, like with it comes some risk because you know, it's new production lines, not. But all the subsystems we developed, whether it was power trains, that, you know, driving its battery improvements in manufacturing and automation, thermal systems, seating, integration of interior components and reduction of LV controllers, all that's transferable. And that's what we're doing, you know, trying to get it into products as fast as possible. So I, yeah, that engineering work, we're not trying to just throw it away and put it, you know, in coffin, we're going to take it and utilize it and utilize it for the best advantage of the cars we make and the future cars we make.
Okay, great. And then just on that topic of 4680 cells, I know you mentioned it, you really thought of it more as like a hedge against, against rising battery costs from other OEMs. It seems, you know, even today, you know, it seems like you would have a cost advantage against some of those other automakers. And I'm wondering, you know, given the rationalizing of your vehicle manufacturing plans that you're talking about now, if there's an opportunity to maybe, you know, convert the 4680 cells and maybe sell those to other automakers and really generate an additional revenue stream, I'm just curious if you have any thoughts about that.
Great. What seems to be happening is that the, I'm missing something, the orders for batteries from other automakers have declined dramatically. So we're seeing much more competitive prices for cells from suppliers dramatically more competitive than in the past. It is clear that a lot of our suppliers have excess capacity.
Yeah. And in addition to what Elon said, this is kind of the way. In addition to what Elon said about 4680s, what 4680 did for us from a supply chain perspective was help us understand the supply chain that's upstream of our cell suppliers. So a lot of the deals that we had struck for 4680, we can also supply those materials to our partners, help reducing the overall cost back to Tesla. So we're basically inserting ourselves in the upstream supply chain by doing that. So that's also been beneficial in reducing the overall pricing in addition to the excess capacity that these suppliers have. Yeah.
Now, I mean, this is going to wax and wane, obviously. So, you know, there's going to be a boom and bust in battery cell production, where production exceeds supply, and then supply exceeds production and back and forth, kind of like on a DRAM or something. But yeah, so it's like what is true today will not be true in the future. There's going to be somewhat of a boom and bust cycle here. And then there are additional complications by, you know, with government incentives, like the Inflation Reduction Act, the IRA, which always found like a funny name for a chemical name.
Yeah, this is like the Irish Republican Army, the Internet Research Agency from Russia. Independent retirement, too. Yeah, exactly. Roth IRA. That was like forest, vitamin situations, which the IRA wins. It is a complicated incentive structure, so that there is stronger demand for cells that are produced in the US than outside the US. But then how long does that the IRA last? I don't know. Which is why it's important that we have both internal cells and mineral cells that you get all of this.
Okay, thank you very much. That's all the time we have today. But at the same time, I would like to make a short announcement. And I wanted to let the investment community know that about a month ago, I met up with Elon and Beibath and announced that I'll be moving on from the world of investor relations. I'll be hanging around for another couple of months or so, so feel free to reach out anytime. But after this seven-year sprint, I'm going to be taking a break and spending some good quality time with my family. And I wanted to say that these seven years have been the greatest privilege of my professional life. I'll never forget the memories from.
I started literally at the beginning of production hell and just watching the company from the inside to see what it's become today. And I'm especially super thankful to the people in this room and dozens of people outside of this room that I've worked for over the years. I think that the team strength and teamwork at Tesla is unlike anything else I've seen in my career. Elon, thank you very much for this opportunity that I got back in 2017. Thank you for seeking investor feedback and regularly and debating it with me.
Yeah, well, I mean, the reason I reached out to you is because I thought your analysis of Tesla was the best that I'd seen. Thank you. Yeah, thank you for helping Tesla get to where it is today over seven years. It's been a pleasure working with you. Thank you so much. And yeah, thank you for all the thousands of shareholders that we've met over the years and walked around factories and loved all the interactions, even the tough ones. And yeah, looking forward to the call in the next three months, but I'll be on the other side listening in. Thank you very much. Thanks. One second, guys. All right. As we usually do, I will do a little recap in here, a little bit of a summary. Man. Tough, tough way to end it, Martin. Let me know if the volume is OK here, guys.
Yeah. So, I mean, exciting earnings reports, obviously, the move in the stock price is, you know, people like to see that more, more sometimes than what is actually being reported, but obviously Tesla up 10% right now, I think pretty good call. I think, you know, a lot of stuff that we can talk about, but I just want to also just start with Martin. Martin's been, I think, an amazing advocate. I would say for retail shareholders within the Tesla community for, like you said, the last seven years, it's very sad. Sad for me to hear that he's going to be moving on, but as we know, there's always a time that comes for everyone when that decision makes sense.
So, you know, I'm excited for Martin for his next chapter. And again, just very thankful for everything that he's done for Tesla, everything that he's done for the retail investor community, the investor community at large. There's a lot of stuff that goes on behind the scenes that, you know, needs to be taken care of. And Martin's been the guy that's done that for a long time now. It's been a very small team, certainly for the size of organization that Tesla has been during that period, probably the smallest. So, yeah, I just want to, you know, extend my gratitude and thank you to Martin for all those years. It'll be sad to see Martin go.
All right, but getting into the earnings call. All right, so interesting day for sure. I feel like we learned a lot. I think there's a lot to be excited about. We can kind of just go back and go through the notes here. But I think obviously that the highlight is the probably pretty significant change in strategy as it comes to, you know, where the next generation vehicles road map is going to be. Sounds like we're going to hear more about that on August 8th, even if that is sort of the Robo taxi announcement date, it sounds like we're going to, you know, even learn a little bit more about maybe what else is in the plans at that time. If they're really going to have vehicles out and I'm sure we've got the note here, but I think I think you said first half 2025, maybe even towards the end of this year. Now, it's Tesla time. So we can't necessarily count on that, but even the possibility of it is, I think, pretty extremely exciting. And I think, you know, a large part of what we are seeing in the stock after hours is the excitement for that. People realizing that maybe the next growth drivers aren't entirely tied to autonomy is maybe a little bit comforting. But should it be? I mean, I don't know. We talked a little bit earlier when the shareholder came out that having those things come a little bit faster for the long term of Tesla, for me personally, I don't think that's really all that important. I think what's more important is the development that's happening with autonomy. I mean, Elon said it on the skull. If you don't believe in that, then probably not the best idea to hold Tesla stock. And I think that has obviously become more of the case over the last 12 to 18 months as we've started to see that plateau within the Model 3 and the Model Y lineup. Now hopefully that plateau gets lifted a little bit higher as we move into some of these other products. But increasingly, it's looking like the value is really coming longer term, maybe not exclusively from autonomy, but it's we're getting close to that period where it's to continue growing. That needs to play a big role, especially if you want it to happen quickly and capital efficiently, which is part of what they had talked about here with this new roadmap. So I think there's a lot of excitement about that. And maybe some of that excitement is misplaced, but I think some of the negativity has also been misplaced. So I guess I'll take it a couple of misplacements offsetting each other and moving up a little bit here for the time being.
All right. So they talked about Q1 as we just kind of go through the notes here that'll jog our memories on points to talk about. As we can see, you know, Q1, I feel like people probably have not given enough credit to some of the challenges that Tesla has talked about. I think people read those words and just kind of write it off as, those are just excuses for poor demand or something like that. And I think there's probably a little bit of that, but I do think that some of what Tesla has mentioned, and you could kind of tell from Lars' exasperation when talking about Q1, just saying it really was one thing after another. And you're already in a seasonally challenging quarter. And you're coming off of a quarter that was quite strong in terms of delivery numbers. Of course, Tesla's strongest ever in Q4. So there's a lot of factors that go into one particular quarter. It's not the first time that we've seen challenging quarters for Tesla, you know, not even close to the first time. So I do think that there's something to be said for that. And I think it's good that they gave a little bit more detail on that.
Energy storage, we've talked about. Great to see that. Of course, they've got great visibility into how that continues to ramp. AI training capacity. So we've talked plenty about that today already during the shareholder letter. New product roadmap. So updated future lineup, accelerate a launch of new products, more likely early 2025, if not late this year. So hey, early 2025, that would be fantastic. In terms of what these new products are, I didn't expect them to answer anything. Probably a waste of a question to ask about it. But I do think if you're going to ask about it, it was framed well when the analysts to ask about, you know, how do we think about these new products relative to something like a Model 3 Highland? Would that be something that would be considered to be kind of a new product? Or is it going to be something more significantly different where maybe you're talking about like a van or something in a new category that maybe Tesla's not offering today? So of course, we didn't get any more information on that. I wouldn't expect that we would. But the possibilities of those things are pretty exciting, especially given the timeline here. Now who knows? This would just be the launch, right? It's still going to take time to ramp up. And I guess they maybe didn't specifically say this meant customer deliveries. I think it's sort of implied. But we could also be talking about more, you know, like announcements or unveiling. I'd have to go back and look at some other context on that. But to me, it seems more likely that they're talking about just like actual production of those new products produced on the current manufacturing lines much more efficiently.
Lars talked about that a little bit too on just some of the engineering plans that they have or that they had for the next generation vehicle, just implementing those kind of as they can versus waiting to do it all at once. With a new more capital intensive line, like seemed to be the original plan. FSD version 12. So we've talked a lot about that. As I've said earlier today, my experience with version 12 has been really good. You know, we know it's not solved yet, but this stepped forward. And I think Ashucks said it really well. There are, I think it was him that was speaking. He talked about four different areas. I'll probably get him wrong here. But model side scaling, architecture side scaling, training data scaling, and probably compute capacity scaling. Maybe there was one other one that I'm mixing up there, but you've got growth on all of those sort of vectors that's happening very quickly. And if scaling, not scaling laws, but scaling trends that they have seen before in those areas, if those trends continue, there's always a chance to kind of, you know, make them like run into an asymptote.
But if those trends continue on those sort of metrics, then we should see really rapid advancement. And I think that's what's so exciting. And I think Tesla sees that. That's what Elon's trying to tell people, like, Hey, we can see where this is going. Three to six months in advance. If that comes to fruition, and if we continue to see steps that are as significant as version 12 was from version 11, which again, there are a lot of good reasons to believe that that would be the case. If that materializes, I think the perception of where this is heading can change pretty quickly. And I think already has to an extent with version 12. So tons to be excited about on the AI front on the autonomous driving front.
I want to make sure I caught this correctly, but he did say for the August 8th event that they would showcase their their Robotaxi slash cyber cab. So I've been a little bit more skeptical that that would be cyber aesthetic, but it sounds like maybe that's going to be the case. So I guess we'll see on that, but that certainly sounds a little bit more like what we might be coming for the Robotaxi. So compute constraints. So no longer as much. There was a slide on this in the shareholder deck, but 35,000 H 100s. Expect that to be roughly 85,000 H 100s by the end of the year. So not quite tripling a little more than doubling.
And of course, this is already maybe not 10x, but maybe eight X where they were, you know, six months ago. So the amount of compute that is being brought online and installed and working and doing it very quickly and also training very efficiently with that compute capacity. Again, it's just it's one of those scalers that we talked about a second ago. That's advancing very rapidly. And what's nice about this is when you have more compute and you're not necessarily as constrained on it, you can test things out. You can train models very quickly. So hopefully we can see Tesla again, make those advancements, make those steps more more rapidly.
Now, as they talked about, there's still a QA component. So they kind of need to do the training. And then there's a period of time where they need to let's maybe not as again constrained on compute more constrained on just like time to make sure that that training and quality assurance stuff happens. That's also going to generate some lead time in there. But again, hopefully we're seeing more rapidity.
Then previously, gas cars, you know, not the first time we've heard those types of things. Let's see, cost of goods sold. So we've talked about most of the CFO type of updates previously from the shareholder letter. 75% growth in energy in 2024. So I don't know, we must have had what like 13 gigawatt hours last year, maybe. So I don't know what that is. Maybe just doing some quick math off my guess. So maybe we're looking at 2025 megawatt hours of energy storage this year, so this year.
So maybe, you know, five five ish gigawatt hours per quarter, not an incredibly higher run rate than what we're at right now, but still definitely very strong growth year over year. Hopefully there are continued economies of scale within that growth. And if we can see, you know, consistent 25, maybe even above 25% growth margins there, which of course, I think the inflation reduction act is boosting a little bit at the moment, but that definitely helps and raises Tesla's overall growth margin, of course, that's higher than automotive.
Free cash flow should return a positive in Q2. I think they give a little bit more context on that that I may have missed in the notes. Headcount reduction seems like actually some pretty significant savings, which they mentioned investing in AI. I think in general, you know, a lot of confidence in where things are headed for a lot of areas within the business, which is, which is nice to see. All right, 4680s. So it's well ahead of the Cybertruck ramp.
And that's kind of the goal. They want to continue to have sort of weeks levels of supply so that they can continue to support that ramp, but they also don't want to get too far ahead as then they're just going to have cells sitting around doing nothing. I wish they would just put that into the semi, but obviously that's not quite ready to go. And it sounds like they're still learning and implementing things from learnings with sort of the test fleet that they have out there now, which it makes a lot of sense.
I know we all want to see stuff happen faster, which given what they had talked about previously, there were faster targets at one point. But I think when we do get to that point, it's going to be, you know, the semi is a very exciting vehicle for when it does end up coming in volume. Goal of 4680s to beat nickel cells by the end of the year. A lot of bullish commentary around optimists. I think we've all kind of thought about those things previously.
Inference efficiency, though, I think that's important. And I think, you know, you see these other companies out there that are, they've got their little prototypes and I don't mean to be demeaning. They've got their prototypes and, you know, maybe they look interesting or maybe they'll go out or do something that maybe Tesla hasn't demonstrated doing yet. I mean, you just got to realize that it's not really any different than showing some sort of a concept car, right? It's Elon's common refrain.
Prototypes are easy. Production is hard. Same thing with this inference stuff is that even if you're mass producing this humanoid robot, you also have to do the inference extremely efficiently. Otherwise these things are going to be very power intensive and that reduces the battery, which reduces the functionality or you're adding weights and expense.
So a lot of the things that Tesla has already learned and iterated on and done within the vehicle business, those things carry over to optimists and any of these new companies, they don't have that skill set, that expertise, that year, you know, decades of pain of doing this in manufacturing that Tesla does. So to do that, plus what we're talking about with the inference where Elon said, you know, they've had to learn how to infer things very efficiently just because of the constraints that they've had on hardware and the vehicles, those learnings also carry through to optimists too. There's a lot of competitive advantages that Tesla has that don't really become apparent in this prototyping stage that everyone is in, but eventually they become very clear and it's kind of like you could look back and you could look at a, I don't know, a fair day, future 91 or whatever they called their car and maybe you look at the prototype and you say, oh yeah, this looks great. This could compete with Tesla and then when you get into reality, it's just there is no world where it could, you know. So not to say that that's exactly the same, but those things need to be considered and they're largely not considered at this type of an early stage, even though they need to be.
Regulatory approval, so some states allow this. We've talked about that. I think the regulatory approval stuff has always been pretty overblown. Elon's point of view basically just like get the data that shows that it's safer and then you know, there's not much of an argument to not allow it. Tesla operate the fleet. So of course they showed the sort of Tesla app render in the earnings stack. Hopefully everybody saw that already.
Interesting commentary around the value of the compute that could just be sitting idle in these vehicles and I think they did a good job of explaining it. It's not just the exact same as a phone sitting out there, right, where this is potentially very high powered computer that is, you know, liquid cooled potentially with a high power battery source that can go for a long time without needing to be plugged in. I think they didn't do the best job of explaining what that compute could be used for. So probably a good area to expand on, but I think they're thinking about it of like, there's clearly value here and that value is something that can be extracted and probably shared with owners of the vehicle that the computer's being used for.
So I wish I knew better how that value will be extracted, but like what Tesla has presented, I feel like there's just got to be some pretty good value there, which is I think very exciting. So training, again, I think they gave good context on just the strength of the feedback loop that they have gotten in place. And I think they made a good comment about a lot of the learning and a lot of this feedback loop happens without intervention by engineers. They don't need someone necessarily going in and, you know, necessarily like labeling everything. It's just feeding the data in and letting the probabilities of the neural network update with that new data.
Hopefully over time that improves the model and then you get new data that helps improve it more and that just keeps going. So that's pretty exciting. Talked about version 12.4 and 12.5. I wish we would have gotten an estimate on that, but it's just based on what you want to said, it sounds like they're kind of seeing three to six months out. So I don't know, maybe three months for 12.4 and six months for 12.5. You've kind of got that quality assurance piece in there too, which we don't know exactly how long that would take, but we can get an idea from how the release of models has gone for past versions. So there's those scaling. So model side, data side, training side, architecture scaling. I think that's what I said, but maybe not. All right.
Cyber truck. So I said this earlier today, but I'm actually very happy with where the cyber truck is at ramp wise, you know, 3900 vehicles delivered by mid April. That's well ahead of what I had projected by that point in the forecast that I had made back in, you know, the second half of 2023. So when cyber truck was kind of just launching, so I'm really happy with that for such a unique vehicle to already be a thousand per week. Although it's probably not a thousand per week every week to hit that milestone is is pretty encouraging, I think. And hopefully continue on that path throughout the rest of this year and kind of get to what would be known as quote unquote volume. Maybe end of this year, maybe early next year, which would be sort of that five K per week type of a number. I think the Tesla would be doing that, right? Or maybe it's more like 3K for. Cyber truck? Yeah, so probably more like 3K. So they're actually not really too far off of where they have the volume planned for this first iteration. So semi we kind of talked about that external customers in 2026.
I apologize. I was kind of laughing at the permanent FSD transfer situation. I've shared my comments on that before and I would actually benefit from that because I've got FSD on a 2021 model year model three. And of course there's a new model three right now, which is quite tempting. But I get both sides of it. From Elon's perspective, if they, especially from the permanent perspective, it doesn't make a lot of sense to make it permanent. The one time things since FSD hasn't really truly been delivered in its final form yet, although we're getting quite close, I think, to sort of what was initially promised depending on when things were purchased because earlier promises were more strong. But anyway, from Elon's perspective, if they were to make that permanent, then people would be getting $50,000 worth of value for $8,000 right now. It just doesn't really make a lot of sense. So that's why he's just kind of immediately shutting that down. But obviously there have been windows where they've opened that up. And hopefully that is acquiesced some of the people that have had frustrations with lack of FSD transferability. You know, hopefully you were able to take advantage of that if that was a big important point for you.
Megapack, so we've talked about that. Nothing too surprising. And then these get into analyst questions. Which I think a lot of stuff we have talked about before. Kind of interesting from Alex Potter's question on Elon's ownership of Tesla. He was kind of like, all right, what's the path, Elon, for you to actually get to that ownership percentage? And one of the ways that Elon answered it, and maybe this is just based on restrictions of what he can cannot say sounded like there are some of those when he started to bring up the shareholder vote. But his answer to how that would happen potentially could be through share buybacks, where if Elon is holding a fixed number of shares and Tesla is buying back shares that exist out there, the float, as those shares get bought back and essentially retired, then Elon's same number of shares would be a larger percentage of the outstanding shares.
So if Tesla were to do significant buybacks, then Elon's percentage could, maybe not easily, but it could grow over time to that 25%, which I think that would be the most preferred path from everybody. I wouldn't mind if there were another compensation plan, but if Elon can get to where he wants to be without that, obviously it's on a per share basis going to be potentially more rewarding for others. Now I still think Elon should have some sort of motivating thing out there other than just the current equity, the underlying equity, but it is what it is. All right, let's see, implication for headcounts, nothing too new. I mean, we've gone through these cycles a lot. I think it's encouraging to hear Elon talk about just making sure that things are reorganized for the next phase of growth.
So reiterating that he spends the majority of his time at Tesla in terms of work, I think they can be meaningfully free cash flow positive in the current market with their current lineup. They said they'll be, I believe, free cash flow positive next quarter. There was something to you about production versus demand and deliveries. I didn't quite catch the comments there, so I might have to go back to that. Other regions, so sounds like FSD. It's really subject to regulatory approval. Hopefully we'll see it in another market soon, but I know particularly in Europe that's been a challenge, perhaps less challenging in China. Simplifying the sales process. And for instance, we talked about 4680s, so I wish somebody would have asked about Dojo. I mean, it's literally in the slide deck. I don't think anyone asked about it. They're talking about all this AI compute. No one even asks about Dojo. It's frustrating. But 4680s, so less excited about their comments there, but good to see that 4680s are improving. Hopefully well ahead of the Cybertruck ramp. Cost competitive with other nickel cells this year. It doesn't sound like they really have intent to supply. Use them in the supply chain for others, at least at this time. But as Elon said, things cycle. So we'll see how things change over time. Then back to Martin.
Said. All right, guys. Well, it's been fun hanging out, talking Tesla. I'm glad we get a nice positive reaction in the stock here. I guess I've mentioned it a few times that, I don't know, it feels like it's just misstepping in both directions. And washing out. Again, to me, it doesn't really, the timeline of whether something happens six months earlier isn't super important. I think the market is liking that it maybe feels like Tesla's not as all-in on autonomy, but then at the same time, listen to Elon's comments. They're pretty all-in on autonomy. So that should also be recognized.
But I'm excited to see what Tesla's got on the works. And if we do see some new products in the next year, that's, I think, a positive surprise. And at least in terms of timing. And certainly always exciting to see what Tesla's coming up with. And then like I said, before deliveries came out this quarter, most important thing that's happened in the last few months is definitely the progress with FSD. We've talked about it enough, but I want to reiterate that because it's very critical to make sure that that's well understood. Greg, thank you. I really appreciate that. Can't pull it up on the screen on this one. But thank you. And then we'll wrap it up for today, guys. So I really appreciate you all hanging out with me here for earnings. It's been fun. I don't know when the next one will be at the latest it'll be next earnings. We'll see what happens in between now and then and what my availability is like. But like I said, it's been really busy, really good with the first principles group.