News
Tesla Model S, 3, X takes on Audi e-tron in Autobahn range and efficiency test
German electric vehicle rental company nextmove recently conducted what could only be described as the ultimate Autobahn efficiency and range test, pitting the Tesla Model S, 3, and X against the upstart Audi e-tron and the bang-for-your-buck Hyundai Kona Electric. Following the EV rental firm’s test, it was evident that veteran automakers such as Audi still have a long way to go before they catch up to Tesla’s experience in electric cars.
Eight vehicles were used for nextmove’s test: a Model S 100D (equipped with 19” winter tires), two Tesla Model X 100D (one fitted with 19” winter tires and the other fitted with 20” summer tires), one Tesla Model 3 Dual Motor AWD (equipped with 19” summer tires), two Audi e-tron (one with digital side mirrors and another with classic mirrors; both equipped with 21” summer tires), and two Hyundai Kona Electric (one fitted with 17” summer tires and the other fitted with 17” winter tires). Each vehicle’s tire pressure was set according to manufacturer specifications, and each was driven by an experienced electric car driver.
Several rules were observed to keep the Autobahn test as controlled as possible. Cruise control was only utilized once the target cruising speed of 130 kph (81 mph) and 150 kph (93 mph) was reached. Features such as Regenerative Braking were also avoided, and heating was largely disabled. Thet route was 85 km (52.8 miles) long, with the vehicles traveling 130 kph one way and 150 kph in the other.
The results of both the 130 kph (81 mph) and 150 kph (93 mph) tests revealed that the Tesla Model 3 was the most efficient vehicle among the eight that the EV rental company evaluated. Following the Model 3 was the Hyundai Kona Electric in summer tires, which is, in turn, followed by the Tesla Model S 100D. The largest vehicle in the group, the Tesla Model X, proved less efficient than the Model 3, Model S, and Kona Electric, but it proved notably more efficient than the Audi e-tron.
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- (Photo: nextmove.de)
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- (Photo: nextmove.de)
The Audi e-tron and the Tesla Model X had already gone head-to-head in a nextmove test in the past. During the previous test, the EV rental company utilized a pre-production version of the Audi e-tron, and it proved to be the electric equivalent of a gas-guzzler, being 23% less efficient than the larger, heavier Tesla Model X.
While the Audi e-tron performed much better against the Tesla Model X than its pre-production counterpart in the recent test, the all-electric SUV still proved less efficient than the Silicon Valley-made crossover. Quite interestingly, the difference in energy consumption between the Tesla Model X and Audi e-tron was more prominent at lower speeds than at higher speeds.
Tesla’s Model S, 3, and X cleared the house in terms of range. During the 130 kph test, the Model S 100D showed a range of 480 km (298 miles), the Model X 100D showed a range of 409 km (254 miles), and the Model 3 managed a range of 406 km (252 miles). The Hyundai Kona Electric turned in a respectable 322 km (200 miles), and the Audi e-tron, in last place, managed 301 km (187 miles).
The results of the 150 kph test were quite similar. The Model S, X and 3 proved superior once more with a range of 428 km (265 miles), 359 km (223 miles), and 358 km (222 miles). The Hyundai Kona Electric managed 283 km (176 miles), while the Audi e-tron achieved a range of 275 km (171 miles). With these results in mind, it appears that veteran automakers such as Audi still have their work cut out for them in terms of designing electric vehicles that offer a balance of power, efficiency, and range.
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- (Photo: nextmove.de)
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- (Photo: nextmove.de)
It should be noted that the Tesla Model X utilized by nextmove in its Autobahn efficiency test was a 100D unit, and thus, the vehicle was not yet equipped with the company’s updated high-efficiency drive units. With a “Raven” Model S and Model X in the equation, the German EV rental company’s test could very well have ended in a far more lopsided manner.
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The full results of nextmove‘s eight-way comparative test could be accessed here.
Watch nextmove’s Autobahn efficiency test in the video below. English subtitles are available.
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.
SpaceX’s next trillion dollar bet has nothing to do with rockets, Musk tells staff
Tesla has one big financial question to answer for investors: Morgan Stanley
