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Tesla Model 3 Performance takes on supercars, high-performance sedans in track battle

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When Elon Musk first announced the specs of the Tesla Model 3 Performance, he noted that the electric car would beat anything on its class inside a closed circuit. With its dual motors that produced a combined 450 hp and 471 lb-ft of torque, its 0-60 mph time of 3.5 seconds, and its top speed of 155 mph, Musk noted that the top variant of the Model 3 would cost roughly the same as a BMW M3, but be “15% quicker and with better handling.”  

It should be noted that Musk mentioned the Model 3 Performance’s comparison with the BMW M3 at a time when Tesla was yet to reveal that it was developing a dedicated Track Mode for the electric sedan. With Track Mode, which optimizes the car for intensive closed circuit driving, the Model 3 Performance becomes a very formidable car on the racetrack. Over the past months, videos of the Model 3 Performance that have been shared online have mostly featured the vehicle competing in drag races or going around race tracks on its own. Rarely has there been a test of the car competing on a closed circuit against other high-performance vehicles.

That is, until recently, when Chinese auto group Know the Car (credit to Tesla community member JayinShanghai for sharing the video) opted to test the Model 3 Performance against several notable competitors. The group selected three groups of vehicles that would compete against the electric car — Chinese-made EVs, the NIO ES8 and the BYD唐DM; high-performance sedans, the BMW M3 and the Mercedes-AMG C63; and supercars, the Nissan GT-R and the Ferrari 488 GTB. 

The tests were conducted at the Goldenport Park Circuit in Beijing, China in -5°C (23°F) weather. In its first test, the group opted to test the Model 3 Performance’s acceleration. Thanks to the instant torque from its dual electric motors, the electric sedan soundly dominated its competitors. After beating the competition on the straight line test, the group opted to call a professional driver to see just how well the Model 3 Performance stacked up against the six other vehicles on the track.

It should be noted that Beijing’s Goldenport Park Circuit is a location that is known to favor cornering and technical driving over high-speed, straight-line acceleration. Thus, during the tests, the Model 3 Performance, with its Track Mode enabled, was driven hard from one corner to the other. When the track times of the six vehicles were compared, it became evident that Elon Musk’s words about the electric car were accurate.

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At the bottom of the rankings were the two Chinese-made EVs, which is understandable considering that the NIO ES8 and the BYD唐DM were SUVs. Immediately following the two EVs was the BMW M3, which was able to complete a lap around the track in 01:22.67. The Mercedes-AMG C 63 fared better than the M3, finishing a lap in 01:20.23. True to Elon Musk’s words, the Tesla Model 3 Performance dominated its class, with its lap time of 01:18.62.

Only two vehicles proved faster than the Model 3 Performance around the track — the Ferrari 488 GTB, which finished a lap in 01:16.31, and the Nissan GT-R, which completed a lap in 01:15.23. As noted by the group that conducted the test, the Model 3 Performance was ultimately outgunned only by vehicles that are beyond its class and its price range (credit to David Jao for the translation).

“The data doesn’t lie. China’s new electric entrants compared to the Model 3  are still far behind. The cars that we previously worshipped as high-end sedans, regretfully defeated. Only the supercars, costing 3-5 times the Model 3 remain to defend the honor of the internal combustion engine (ICE). So the appearance of the Model 3 brings forth a new kind of performance — cheaper, quieter, and even faster.”

The group’s statement about the prices of the Model 3’s rivals in the Chinese market is no exaggeration. Tesla lists the Model 3 Performance with a price of 560,000 RMB (around $81,000) for the Chinese market. While higher than its $64,000 price in the United States, the Model 3 Performance is still considerably more affordable than its rival high-performance sedans in the country. The BMW M3, for one, sells for 998,000 RMB ($162,000), while the Mercedes-AMG C 63 Coupe costs 1,198,000 RMB ($173,623). With its price in the Chinese market, Tesla all but made the Model 3 Performance as the ultimate bang-for-your-buck high-performance sedan — quicker, cleaner, and cheaper than the competition.

Watch the Tesla Model 3 Performance battle local high-performance sedans and supercars on the track in the video below.

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Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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Nvidia CEO Jensen Huang explains difference between Tesla FSD and Alpamayo

“Tesla’s FSD stack is completely world-class,” the Nvidia CEO said.

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Credit: Grok Imagine

NVIDIA CEO Jensen Huang has offered high praise for Tesla’s Full Self-Driving (FSD) system during a Q&A at CES 2026, calling it “world-class” and “state-of-the-art” in design, training, and performance. 

More importantly, he also shared some insights about the key differences between FSD and Nvidia’s recently announced Alpamayo system. 

Jensen Huang’s praise for Tesla FSD

Nvidia made headlines at CES following its announcement of Alpamayo, which uses artificial intelligence to accelerate the development of autonomous driving solutions. Due to its focus on AI, many started speculating that Alpamayo would be a direct rival to FSD. This was somewhat addressed by Elon Musk, who predicted that “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.”

During his Q&A, Nvidia CEO Jensen Huang was asked about the difference between FSD and Alpamayo. His response was extensive:

“Tesla’s FSD stack is completely world-class. They’ve been working on it for quite some time. It’s world-class not only in the number of miles it’s accumulated, but in the way it’s designed, the way they do training, data collection, curation, synthetic data generation, and all of their simulation technologies. 

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“Of course, the latest generation is end-to-end Full Self-Driving—meaning it’s one large model trained end to end. And so… Elon’s AD system is, in every way, 100% state-of-the-art. I’m really quite impressed by the technology. I have it, and I drive it in our house, and it works incredibly well,” the Nvidia CEO said. 

Nvidia’s platform approach vs Tesla’s integration

Huang also stated that Nvidia’s Alpamayo system was built around a fundamentally different philosophy from Tesla’s. Rather than developing self-driving cars itself, Nvidia supplies the full autonomous technology stack for other companies to use.

“Nvidia doesn’t build self-driving cars. We build the full stack so others can,” Huang said, explaining that Nvidia provides separate systems for training, simulation, and in-vehicle computing, all supported by shared software.

He added that customers can adopt as much or as little of the platform as they need, noting that Nvidia works across the industry, including with Tesla on training systems and companies like Waymo, XPeng, and Nuro on vehicle computing.

“So our system is really quite pervasive because we’re a technology platform provider. That’s the primary difference. There’s no question in our mind that, of the billion cars on the road today, in another 10 years’ time, hundreds of millions of them will have great autonomous capability. This is likely one of the largest, fastest-growing technology industries over the next decade.”

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He also emphasized Nvidia’s open approach, saying the company open-sources its models and helps partners train their own systems. “We’re not a self-driving car company. We’re enabling the autonomous industry,” Huang said.

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Elon Musk confirms xAI’s purchase of five 380 MW natural gas turbines

The deal, which was confirmed by Musk on X, highlights xAI’s effort to aggressively scale its operations.

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Credit: xAI/X

xAI, Elon Musk’s artificial intelligence startup, has purchased five additional 380 MW natural gas turbines from South Korea’s Doosan Enerbility to power its growing supercomputer clusters. 

The deal, which was confirmed by Musk on X, highlights xAI’s effort to aggressively scale its operations.

xAI’s turbine deal details

News of xAI’s new turbines was shared on social media platform X, with user @SemiAnalysis_ stating that the turbines were produced by South Korea’s Doosan Enerbility. As noted in an Asian Business Daily report, Doosan Enerbility announced last October that it signed a contract to supply two 380 MW gas turbines for a major U.S. tech company. Doosan later noted in December that it secured an order for three more 380 MW gas turbines.

As per the X user, the gas turbines would power an additional 600,000+ GB200 NVL72 equivalent size cluster. This should make xAI’s facilities among the largest in the world. In a reply, Elon Musk confirmed that xAI did purchase the turbines. “True,” Musk wrote in a post on X. 

xAI’s ambitions 

Recent reports have indicated that xAI closed an upsized $20 billion Series E funding round, exceeding the initial $15 billion target to fuel rapid infrastructure scaling and AI product development. The funding, as per the AI startup, “will accelerate our world-leading infrastructure buildout, enable the rapid development and deployment of transformative AI products.”

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The company also teased the rollout of its upcoming frontier AI model. “Looking ahead, Grok 5 is currently in training, and we are focused on launching innovative new consumer and enterprise products that harness the power of Grok, Colossus, and 𝕏 to transform how we live, work, and play,” xAI wrote in a post on its website. 

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Elon Musk’s xAI closes upsized $20B Series E funding round

xAI announced the investment round in a post on its official website. 

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Credit: xAI

xAI has closed an upsized $20 billion Series E funding round, exceeding the initial $15 billion target to fuel rapid infrastructure scaling and AI product development. 

xAI announced the investment round in a post on its official website. 

A $20 billion Series E round

As noted by the artificial intelligence startup in its post, the Series E funding round attracted a diverse group of investors, including Valor Equity Partners, Stepstone Group, Fidelity Management & Research Company, Qatar Investment Authority, MGX, and Baron Capital Group, among others. 

Strategic partners NVIDIA and Cisco Investments also continued support for building the world’s largest GPU clusters.

As xAI stated, “This financing will accelerate our world-leading infrastructure buildout, enable the rapid development and deployment of transformative AI products reaching billions of users, and fuel groundbreaking research advancing xAI’s core mission: Understanding the Universe.”

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xAI’s core mission

Th Series E funding builds on xAI’s previous rounds, powering Grok advancements and massive compute expansions like the Memphis supercluster. The upsized demand reflects growing recognition of xAI’s potential in frontier AI.

xAI also highlighted several of its breakthroughs in 2025, from the buildout of Colossus I and II, which ended with over 1 million H100 GPU equivalents, and the rollout of the Grok 4 Series, Grok Voice, and Grok Imagine, among others. The company also confirmed that work is already underway to train the flagship large language model’s next iteration, Grok 5. 

“Looking ahead, Grok 5 is currently in training, and we are focused on launching innovative new consumer and enterprise products that harness the power of Grok, Colossus, and 𝕏 to transform how we live, work, and play,” xAI wrote. 

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