Investor's Corner
Tesla reveals Model 3 Performance “Dual Motor” badge and new pricing
Tesla has given the Model 3 Performance and Dual Motor AWD a considerable price cut. Now, a fully-loaded Model 3 Performance costs $72,000 without Autopilot and Full Self-Driving, $6,000 less than its initial price of $78,000. Buyers opting for the non-performance variant Model 3 with dual motors and a Long Range battery pack can expect to pay $53,000, $1000 less than before. Tesla’s pricing for Enhanced Autopilot and Full Self-Driving remains the same at $5,000 and $3000, respectively, though FSD will cost $5,000 when added after delivery.
Overall, Tesla was able to achieve a significant price drop for the Model 3 Performance by making some of its features (now dubbed as a $5,000 Premium Package) optional, such as its 20″ Performance Wheels, Michelin Pilot Sport 4S summer tires, carbon fiber rear spoiler, aluminum alloy pedals, and a top speed boost that enables the electric car to max out at 155 mph. White seats and premium paint choices are also optional at $1,500 each. Without these, the Model 3 Performance, with its 0-60 mph time of 3.5 seconds and 310-mile range, could be bought for $64,000.
Particularly notable in the screenshots above is Tesla’s inclusion of the company’s Premium Connectivity package, an update that the company announced earlier this week.
“All orders placed before July 1 will receive Premium Connectivity with satellite maps with live traffic visualization, in-car streaming media and over-the-air updates via Wi-Fi & cellular,” reads the description for the Select Interior option in Tesla’s Model 3 Design Studio.
An image in the configurator also reveals, for the first time, that Model 3 Performance Dual Motor will have a “Dual Motor” badge with a red underline that Tesla has made synonymous with performance.
With the price adjustments to the Model 3 Performance, Tesla has managed to make its compact electric car an even more compelling purchase than before. At its original price of $78,000, the Model 3 Performance was already reasonably priced compared to established leaders in the high-performance compact segment, such as the BMW M3, Mercedes AMG C63S, and the Audi RS5, all of which can approach the $100,000 mark when fully loaded (the C63S actually breaches the $100,000 mark). With its adjusted price, the Model 3 Performance, which Elon Musk claimed would be 15% faster around the track than a BMW M3, just became a bargain.
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The price drop trickled down to the Model 3 Dual Motor AWD as well. Prior to the recent adjustments, the additional motor for the vehicle cost an extra $5,000. Now, the Dual Motor variant costs only $4,000 more than the Long Range RWD version of the electric car. As of date, the delivery window for the Tesla Model 3 Performance is listed at 2-4 months. The Model 3 Dual Motor AWD, on the other hand, is listed with a 3-5-month delivery window, similar to the Long Range RWD variant of the compact electric car.
The Model 3 is Tesla’s first attempt at making a mass-market vehicle. Since starting production of the electric car in the middle of 2017, however, the production of the car has been beset with challenge after challenge, causing the company to miss its targets for the Model 3’s production numbers. As Q2 2018 ends, however, Tesla is closer than ever to attaining its goal of producing 5,000 Model 3 per week by the end of June, thanks in part to a new assembly line in a massive sprung structure on the grounds of the Fremont factory. In a recent tweet, Elon Musk noted that GA3, one of the Model 3 assembly lines inside the Fremont factory, is practically doing something miraculous. Sightings over the past weekend of lots filled to the brim with Model 3 were also spotted by Tesla fans, suggesting that the company has attained a production pace it has never reached before.
Elon Musk
SpaceX’s next trillion dollar bet has nothing to do with rockets, Musk tells staff
Elon Musk told SpaceX staff AI revenue will soon dwarf rockets and Starlink combined entirely.
Elon Musk told SpaceX employees this week that artificial intelligence, not rockets, will soon carry the company’s revenue. In a roughly 29 minute internal address posted on SpaceX’s X account on Tuesday, Musk said AI revenue will pass every other line of business at SpaceX “probably in September” and pull further ahead by the fourth quarter.
The numbers he gave are specific. SpaceX currently runs 1.4 gigawatts of AI compute capacity. Musk wants that at 10 gigawatts by the end of 2027, a jump he tied directly to revenue: “if we bring 10GW of AI online by the end of next year, it will be $300 billion to $500 billion a year in revenue.” He called those “big numbers,” which undersells a projection larger than what most countries produce in a year.
We made rockets reusable and are rebuilding the internet in space. The next challenge: making life multiplanetary and understanding the true nature of the universe
Watch @ElonMusk deliver a company update to @SpaceX employees pic.twitter.com/5c8rxoCQfu
— SpaceX (@SpaceX) August 11, 2026
Musk went further on where AI fits into SpaceX’s future. “Probably in four or five years, AI will be 99% of the value of SpaceX,” he told staff, adding that digital intelligence would eventually run “a trillion times” ahead of biological intelligence as computing scales. He tied that growth to the company’s founding mission, telling employees “we must win on AI, because the future is overwhelmingly AI and robots,” with the payoff meant to help fund Starship and a Mars program that increasingly runs through Terafab, the joint Tesla, SpaceX and xAI chip plant.
Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry
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None of this is entirely new territory. SpaceX told investors much the same story during its first earnings call as a public company on August 4, where Musk moved the company’s $1 trillion revenue target up a year to 2030 and said Starlink could someday carry a majority of the world’s internet. What the all hands video adds is a hard deadline and a specific power figure Musk had not given publicly before, along with a franker pitch to his own workforce that AI, not launch cadence, is now the thing SpaceX is betting its future on.
The AI revenue itself is not coming from SpaceX training its own models. It is largely Starlink acting as the network layer for xAI’s workloads, plus SpaceX renting out compute capacity directly, the same approach behind the roughly $16 billion the company spent on AI infrastructure in a single quarter.
Musk closed the video with a pitch aimed at recruiting and retention rather than investors, telling employees that anyone who helps SpaceX win the AI race will eventually get the chance to go to the moon or Mars themselves. Whether SpaceX can turn 1.4 gigawatts into 10 in seventeen months is the more immediate question, and one that will show up in quarterly numbers well before anyone leaves Earth.
In a new note to investors on Tuesday, Morgan Stanley analyst Andrew Percoco said that Tesla has one big financial question to answer for investors regarding its Robotaxi rollout, Full Self-Driving software, and Optimus.
Percoco said in the note that, for the most part, investors are still very positive about the direction the company is headed. However, there are some things the firm would like to see, and they have to do with financials.
Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue
Tesla bulls are more than convinced that the company’s Full Self-Driving software is proof it can develop physical AI. Financially, however, there are still some questions, especially on elevated spending, which CEO Elon Musk said would occur as the company works to roll out Robotaxi faster and continue developing its Optimus robot.
The latter two are where Tesla will have to prove progress to investors, as Percoco writes that both projects “will require clearer evidence that Robotaxi is scaling and more tangible Optimus proof points to support the ROI on elevated capex.”
Percoco said the second quarter earnings call did not change his long-term thesis of where Tesla is positioned in the AI race, which is out in front. However, there are concerns that weaker gross margins and higher R&D spend will stress financials, and that has “sharpened our (and investors’) focus on measurable progress across Robotaxi and Optimus.”
Additionally, Robotaxi still needs to be proven with more operation in existing cities while maintaining safety but improving how many rides it gives in any given time, he said. For Optimus, Percoco wrote that he is “still looking for evidence beyond commentary around SOP.”
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Morgan Stanley put Percoco in charge of covering Tesla after long-time analyst Adam Jonas transitioned to the automotive side.
Currently, Morgan Stanley has a $415 price target on Tesla and a ‘Hold’ rating on the stock. It is trading at around $330 at the time of publication, which was 2:30 P.M. on the East Coast.
SpaceX’s massive investment in AI will make it a big winner, Argus Research said after the company’s successful earnings call last week.
The firm also upgraded shares to a Buy from Hold and set a $160 price target.
SpaceX (NASDAQ: SPCX) is currently recovering from its heavy AI infrastructure investments, as it spent nearly $16 billion in Q2 alone. The company did this primarily by monetizing high-demand GPU compute capacity at a much faster pace than traditional data center economics would suggest.
Company CFO Bret Johnsen said that SpaceX would be able to pay back anything on new deployments within a year.
There are plenty of ways the company can do this:
Leasing excess compute capacity through contracts
SpaceX has already built Colossus and Colossus II, largely for its own model training. However, much of that capacity is already rented out to third parties. It already has major deals with Anthropic, Google, and Reflection AI. These partnerships are adding billions per month to SpaceX’s spreadsheet.
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High utilization driven by industry-wide scarcity
The demand for advanced AI training and inference capacity continues to exceed what is available for use. SpaceX can fill new racks quickly after they come online, so the capital deployed converts into revenue with minimal idle time.
Additionally, management and outside observers have described the new compute capital as behaving more like a cost-of-goods-sold than traditional multi-year capex, especially because of this rapid monetization pattern.
Capacity has already scaled from ~0.4 GW a year to 1.4 GW annually by the end of Q2. There are targets of more than 2 GW by year-end.
High incremental margins on the rental business once capacity is online
GPU cloud providers often operate at strong gross margins. SpaceX can monetize capacity that was already partially built or can be added efficiently. This means that incremental EBITDA margins on the rental revenue are usually high. This accelerates cash recovery relative to the gross capital outlay.
Parallel monetization of its own AI software and applications
Beyond pure infrastructure rental, SpaceX also generates revenue from Grok through subscriptions and usage, from X through ads, data, and other related services, enterprise APIs, and the planned integration of the Cursor coding tools acquisition.
These application layers ride on the same compute infrastructure and provide additional high-margin streams that could offset build-out costs. AI-segment revenue overall rose sharply to about $2.6 billion in Q2, according to Motley Fool. This was driven primarily by the infrastructure contracts, but the software side is also partially responsible.
Efficient, large-scale deployment and vertical integration advantages
SpaceX has emphasized the rapid construction of power and cooling infrastructure and favorable cost-per-megawatt economics relative to industry benchmarks in some disclosures.
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Combined with its ability to scale capacity aggressively and the fact that many contracts start generating revenue within months of capacity coming online, the effective payback compresses dramatically compared with more conventional multi-year data-center projects.
SpaceX’s dominant near-term recovery path will turn the AI clusters into a hyperscale-style compute rental business for other leading AI companies while still using a portion for internal models.
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