News
Tesla Model X Range Impact When Towing
The Model X is a great tow vehicle — quiet, comfortable, and powerful. But its range is severely reduced when towing a heavy load. Actual range may be less than half that available in normal driving.
Tesla Model X owner Max Kennedy took full advantage of the optional tow package by towing his 4,850 lb. boat and trailer to Tampa Bay, FL on New Year’s Day. He reports his Model X makes an excellent tow vehicle — quiet, comfortable, and powerful as demonstrated in the last segment of the video (6:51 min. marker) where Kennedy effortlessly accelerates from 55 mph to 80 mph within seconds. However, the ability to tow a near 5,000 payload doesn’t come without a cost, and in this case it’s energy consumption.
With a full charge at the beginning of the trip, Kennedy observes the amount of energy consumption by comparing the Tesla’s Instant Range reading with the change in speed and surface street elevation. The Model X consumed an average of 575 watt-hours per mile while traveling at 55 mph in steady state cruising on level roads. Not surprisingly, the amount of energy used drastically increased when the 5,441 lb. Model X plus the additional 4,850 lb. boat and trailer combination was faced with an incline and a slight increase in speed, to the tune of 800 – 900 Wh/mi.
At that rate of energy consumption, the range impact when towing could be cut by 60% or more.
Model X consumed 922 Wh/mi at 60mph (5 mi avg) while towing a 4,850 up a slight incline [Source: Max Kennedy via YouTube]
Reaction to the video on Reddit was immediate. TheSpocker posted, “That’s a huge hit on range. Yikes. I mean, we all knew it would be this way. Aerodynamics are a huge part of Tesla design and that boat wasn’t designed with those concerns. It’s just unfortunate that towing hurts range so much. I hope that most owners of the X can still make it between superchargers while towing on their long-haul routes.”
He continued, “I love Tesla’s. I love electric cars. We still need to recognize that the range when towing on an electric is almost laughable. That’s not a big problem for most people who don’t tow, but it has to be overcome for electric vehicles to directly compete with ICE vehicles.”
The question then becomes, Can the Tesla Model X really compete with conventional trucks or SUVs as a tow vehicle? The answer really depends on a number of factors. If there is no charger available where you are going, your destination may need to be within 50 miles of home or a roundtrip of 100 miles from the originating charging facility. “The problem is it’s more or less irrelevant with an ICE. A truck might have half the range, but it takes a whole two minutes to fill up and keep going.”, writes another user.
In other words, if you are towing a heavy payload up into the mountains or in areas where there’s prolonged inclines (ie. Flagstaff, AZ to Moab, UT), the Model X may not have the range to get you there unless the distance between Supercharger stations are shortened. Some people will have no problem with frequent charging along the way, but for some, towing using an internal combustion engine might still be king.
News
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
