While the Tesla Model 3 Performance will not be able to beat the Porsche Taycan in a timed lap around a track, the midsize family sedan could outlast the German-made four-door sports car in an endurance race. This is according to Tesla CEO Elon Musk, who recently provided several updates on the electric car maker’s upcoming Model S Plaid Powertrain variant in a series of tweets.
While responding to a follower who inquired if the $56,000 Model 3 Performance will be able to beat the $150,000 Taycan around a closed circuit, Musk stated that Tesla’s most affordable vehicle will likely lose to the all-electric Porsche. Musk did explain that the race between the two all-electric vehicles will be “very close” nonetheless.
Seemingly as an afterthought, Musk soon added that the Model 3 Performance would actually be able to beat the Porsche Taycan in an endurance race, simply because it has more range. Musk even playfully hinted at a potential performance boost coming to the Model 3 series, responding with a cryptic “You never know…” to a follower who asked if Tesla could still squeeze out more performance out of the midsize sedan.
Musk’s statement about the Model 3 Performance’s capability to outlast the Taycan in an endurance race does hold some merit, considering its superior range and efficiency. The Model 3 Performance has an EPA rated range of 310 miles per charge, after all, which is a substantial lead over the Porsche Taycan’s WLTP range of 236.74-279.61 miles per charge. This is a key difference-maker between the two vehicles, especially since the WLTP is generally more generous with range estimates compared to the EPA. Thus, at least in theory, the Model 3 could go around a track more times than the Taycan before it needs to recharge its batteries.
Despite their massive price and range discrepancy, the Porsche Taycan Turbo and the Model 3 Performance actually have fairly comparable specs. The Taycan Turbo has a 0-60 mph time of 3.0 seconds, while the Model 3 Performance sprints to 60 mph in 3.2 seconds. In terms of top speed, the Taycan maxes out at 161 mph while the Model 3 Performance maxes out at 162 mph. Overall, a race between these two vehicles in a closed circuit will most definitely be a great match, as it will be a battle between a premium all-electric sports car that’s born and bred for the track and a family sedan that looks far too tame for its ferocity.
Perhaps the real difference-maker in the Model 3 vs Taycan battle would be Tesla’s capability to unlock more performance out of its vehicle. Musk’s recent playful response would suggest that Tesla has some options to explore on this front. And considering a 2016 tweet where Musk responded positively to the suggestion of introducing Ludicrous Mode for the Model 3, it appears that Tesla might have some more tricks up its sleeve for its resident bang-for-your-buck performance car.
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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.
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.
“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.”
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.
Elon Musk
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.
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.”
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.
Elon Musk
Elon Musk’s xAI closes upsized $20B Series E funding round
xAI announced the investment round in a post on its official website.
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.”
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.
Nvidia CEO Jensen Huang explains difference between Tesla FSD and Alpamayo
Elon Musk confirms xAI’s purchase of five 380 MW natural gas turbines
