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BMW i4 M50 range tested on the Autobahn

Credit: BMW

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Bjorn Nyland has completed yet another one of his infamous range tests, but this time, the BMW i4 M50 was taken to its home turf and tested to its limits on the autobahn.

The BMW i4 came to market earlier this year as BMW’s answer to the Tesla Model 3. With it, BMW promised a superior interior cabin, classic BMW styling, and a competitive price tag. Now it has been tested to its absolute limits on the German autobahn to see if the Bavarian engineers made something that can compete with the likes of the Tesla Model 3 Performance.

In Mr. Nyland’s testing, the BMW is taken to what he calls “V-max,” or the fastest it will go, on an unrestricted section of the German autobahn. For those unfamiliar, speed limits are removed on these sections of highway.

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The car being tested is the BMW i4 M50. The car boasts some impressive specs; 270 miles of range from an 83.9kWh battery, 536 horsepower and 586 pound-feet of torque from a dual motor all-wheel-drive system, and a shocking 0-60 of 3.7 seconds. All for a measly $67,300 starting price. BMW also offers lower vehicle trims with a single-motor rear-wheel-drive system, starting at $51,400.

During the test, the i4 is held at a near-constant 200kph (124mph), with short bursts up to 230kph (142mph). And while this would be a formidable task for any vehicle, it may be particularly difficult for an electric vehicle as it gains no added efficiency at higher speeds and suffers from the high temperatures produced by the battery’s discharge. This effect is most profoundly seen in the range the EV is capable of while holding such high speeds, but it can also be seen, in the case of the BMW, in decreased performance as the vehicle struggles with heat in the battery.

During the video, the BMW quickly jumps to the 200kph testing speed, and Mr. Nyland applauds the sedan’s jumpy acceleration. After that, the car settles down and produces a smooth and reasonably quiet ride; something Mr. Nyland could not say about the Model 3 he tested.

Finally, as the car hits 3% battery, the test is concluded, and some exciting calculations are revealed. Foremost, the BMW was close to the efficiency of the Tesla Model 3 Performance Mr. Nyland tested previously. The i4 used between 475/503 watt-hours per kilometer, whereas the Model 3 used between 464/502 watt-hours per kilometer. However, it should be noted that the Model 3 averaged a slightly higher speed during its autobahn run.

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As battery technology, motor technology, and aerodynamics improve in the coming years, it will be amazing to see how fast and efficient EVs can become. Nonetheless, BMW performed admirably, showing that the German luxury brand may finally be nearing Tesla’s technological prowess.

What do you think of the article? Do you have any comments, questions, or concerns? Shoot me an email at william@teslarati.com. You can also reach me on Twitter @WilliamWritin. If you have news tips, email us at tips@teslarati.com!

Will is an auto enthusiast, a gear head, and an EV enthusiast above all. From racing, to industry data, to the most advanced EV tech on earth, he now covers it at Teslarati.

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Tesla isn’t joking about building Optimus at an industrial scale: Here we go

Tesla’s Optimus factory in Texas targets 10 million robots yearly, with 5.2 million square feet under construction.

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Tesla’s Q1 2026 Update Letter, released today, confirms that first generation Optimus production lines are now well underway at its Fremont, California factory, with a pilot line targeting one million robots per year to start. Of bigger note is a shared aerial image of a large piece of land adjacent to Gigafactory Texas, that Tesla has prominently labeled “Optimus factory site preparation.”

Permit documents show Tesla is seeking to add over 5.2 million square feet of new building space to the Giga Texas North Campus by the end of 2026, at an estimated construction investment of $5 billion to $10 billion. The longer term production target for that facility is 10 million Optimus units per year. Giga Texas already sits on 2,500 acres with over 10 million square feet of existing factory floor, and the North Campus expansion is being built to support multiple projects, including the dedicated Optimus factory, the Terafab chip fabrication facility (a joint Tesla/SpaceX/xAI venture), a Cybercab test track, road infrastructure, and supporting facilities.

Credit: TESLA

Texas makes strategic sense beyond the existing infrastructure. The state’s tax structure, lower labor costs relative to California, and the proximity to Tesla’s AI training cluster Cortex 1 and 2, both located at Giga Texas and now totaling over 230,000 H100 equivalent GPUs, means the Optimus software stack and the factory producing the hardware will share the same campus. Tesla’s Q1 report also confirmed completion of the AI5 chip tape out in April, the inference processor designed specifically to power Optimus units in the field.

As Teslarati reported, the Texas facility is intended to house Optimus V4 production at full scale. Musk told the World Economic Forum in January that Tesla plans to sell Optimus to the public by end of 2027 at a price between $20,000 and $30,000, stating, “I think everyone on earth is going to have one and want one.” He has previously pegged long term demand for general purpose humanoid robots at over 20 billion units globally, citing both consumer and industrial use cases.

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Investor's Corner

Tesla (TSLA) Q1 2026 earnings results: beat on EPS and revenues

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Credit: Tesla

Tesla (NASDAQ: TSLA) reported its earnings for the first quarter of 2026 on Wednesday afternoon. Here’s what the company reported compared to what Wall Street analysts expected.

The earnings results come after Tesla reported a miss on vehicle deliveries for the first quarter, delivering 358,023 vehicles and building 408,386 cars during the three-month span.

As Tesla transitions more toward AI and sees itself as less of a car company, expectations for deliveries will begin to become less of a central point in the consensus of how the quarter is perceived.

Nevertheless, Tesla is leaning on its strong foundation as a car company to carry forward its AI ambitions. The first quarter is a good ground layer for the rest of the year.

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Tesla Q1 2026 Earnings Results

Tesla’s Earnings Results are as follows:

  • Non-GAAP EPS – $0.41 Reported vs. $0.36 Expected
  • Revenues – $22.387 billion vs. $22.35 billion Expected
  • Free Cash Flow – $1.444 billion
  • Profit – $4.72 billion

Tesla beat analyst expectations, so it will be interesting to see how the stock responds. IN the past, we’ve seen Tesla beat analyst expectations considerably, followed by a sharp drop in stock price.

On the same token, we’ve seen Tesla miss and the stock price go up the following trading session.

Tesla will hold its Q1 2026 Earnings Call in about 90 minutes at 5:30 p.m. on the East Coast. Remarks will be made by CEO Elon Musk and other executives, who will shed some light on the investor questions that we covered earlier this week.

You can stream it below. Additionally, we will be doing our Live Blog on X and Facebook.

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SpaceX is following in Tesla’s footsteps in a way nobody expected

In the span of just months in early 2026, SpaceX has transformed itself into one of the world’s most ambitious AI companies. The catalyst: its February acquisition of xAI.

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Credit: Grok

When Elon Musk founded Tesla in 2003, it was a plucky electric car startup betting everything on lithium-ion batteries and a niche luxury Roadster.

Two decades later, Tesla is far more than a car company. Its valuation increasingly hinges on Full Self-Driving software, the Optimus humanoid robot, the Robotaxi program, and the Dojo supercomputer cluster purpose-built for AI training.

Musk has repeatedly described Tesla as an AI and robotics company that happens to sell vehicles. The cars, in this view, are merely the first scalable platform for real-world AI.

Now, SpaceX is tracing an eerily similar path, only faster and in a direction almost no one anticipated. Founded in 2002 to make spaceflight routine and eventually multiplanetary, SpaceX spent its first two decades perfecting reusable rockets, landing Falcon 9 boosters, and building the Starlink megaconstellation.

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Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry

It was an engineering and manufacturing powerhouse, not a software play. Yet, in the span of just months in early 2026, SpaceX has transformed itself into one of the world’s most ambitious AI companies. The catalyst: its February acquisition of xAI.

The xAI deal, announced on February 2, was structured as an all-stock transaction that valued the combined entity at roughly $1.25 trillion—SpaceX at $1 trillion and xAI at $250 billion. In a memo to employees, Musk framed the merger as the creation of “the most ambitious, vertically-integrated innovation engine on (and off) Earth.”

The new SpaceX now owns Grok, the large language model family that powers the chatbot of the same name, along with xAI’s massive training infrastructure. More importantly, it has a declared mission to move AI compute off-planet.

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Earth-based data centers are hitting hard limits on power, cooling, and land. Musk’s solution is orbital data centers, or constellations of solar-powered satellites that act as supercomputers in the sky.

SpaceX has already asked regulators for permission to launch up to one million such satellites. Starship, the company’s fully reusable heavy-lift vehicle, is the only rocket capable of delivering the necessary mass at the required cadence.

Each orbital node would enjoy near-constant sunlight, vast radiator surfaces for passive cooling, and zero terrestrial real-estate costs. Musk has predicted that within two to three years, space-based AI inference and training could become cheaper than anything possible on the ground.

This is not a side project; it is the strategic centerpiece Musk has envisioned for SpaceX. Starlink already provides the global low-latency backbone; next-generation V3 satellites will carry onboard AI accelerators. Rockets deliver the hardware, while AI optimizes every aspect of launch, landing, and constellation management.

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The feedback loop is self-reinforcing, too. Better AI makes better rockets, which launch more AI infrastructure.

Just yesterday, on April 21, SpaceX doubled down.

It secured an option to acquire Cursor—the fast-growing AI coding tool beloved by software engineers—for $60 billion later this year, or pay a $10 billion partnership fee if the full deal does not close.

Cursor’s models already help engineers write code at superhuman speed. Pairing that technology with SpaceX’s Colossus-scale training clusters (the same ones powering Grok) positions the company to dominate AI developer tools, much as Tesla dominates autonomous driving software.

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Why SpaceX just made a $60 billion bet on AI coding ahead of historic IPO

The parallels with Tesla are striking. Both companies began in a single, capital-intensive sector: Tesla with EVs, SpaceX with launch vehicles. Both used early hardware success to fund AI at scale. Tesla’s Dojo supercomputers train neural nets on billions of miles of real-world driving data; SpaceX now trains on telemetry from thousands of orbital assets and re-entries.

Tesla’s FSD chip runs inference on cars; SpaceX’s future satellites will run inference in orbit.

Tesla’s Optimus robot will work in factories; SpaceX envisions lunar factories manufacturing more AI satellites, eventually using electromagnetic mass drivers to fling them into deep space.

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Critics once dismissed Musk’s multi-company empire as unfocused. The 2026 moves reveal the opposite: deliberate convergence.

SpaceX is no longer merely a rocket company that sells internet from space. It is an AI company whose competitive moat is literal orbital infrastructure and the only vehicle that can service it at scale. The forthcoming IPO, expected later this year, will almost certainly be pitched not as a space play but as the purest bet on AI infrastructure the public market has ever seen.

Whether the orbital data-center vision survives regulatory scrutiny, astronomical concerns about light pollution, or the sheer engineering challenge remains to be seen.

Yet the strategic direction is unmistakable. Just as Tesla proved that software and AI could redefine the century-old automobile, SpaceX is proving that rockets are merely the delivery mechanism for the next great computing platform—one that floats above the clouds, powered by the sun, and limited only by the physics of orbit.

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In that unexpected sense, history is repeating. Tesla stopped being “just a car company” years ago. SpaceX has now stopped being “just a rocket company.” Both are becoming something far larger: AI powerhouses with hardware moats so deep that competitors will need their own reusable megaconstellations to keep up.

The age of terrestrial AI is ending. The age of space-based AI is beginning—and SpaceX is building the launchpad.

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