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Porsche Taycan vs Tesla Model S: Powertrain, battery, performance, and features
The Tesla Model S has been sitting on top of the full-sized electric sedan market for a while now — and for good reason. The vehicle, after all, has played a huge part in changing the public’s perception of what electric cars are capable of. Fast, sleek, and equipped with real range, the Model S is a true no-compromises vehicle.
Among all the competitors for the Model S, there is one that is being developed to compete directly with the electric car. That is the Porsche Taycan, formerly known as the Mission E sedan. The Taycan made its debut during the 2015 Frankfurt Motor Show, and it has captured the imagination of EV enthusiasts ever since. Porsche is yet to unveil the production version of the Taycan, though it has several camouflaged units doing real-world tests today.
Porsche appears to be a legacy automaker that is really serious about making the Taycan a successful vehicle — so much so that the company actually released the car’s specs earlier this year. That said, how does the Taycan compare to the golden standard of four-door electric sedans? Here’s a brief comparison.
Powertrain
The Tesla Model S was initially released with an RWD option, though all variants of the vehicle today are now Dual Motor AWD. The Model S uses three-phase, four pole AC induction motors with copper rotors as its powertrain. The car is also equipped with a drive inverter with variable frequency drive and regenerative braking system.
In contrast, Porsche is using permanently excited synchronous motors (PSM) for the Taycan. In true Porsche tradition, the PSM motors are race-bred, having been used in the Porsche 919 Hybrid racecar. Naser Abu Daqqa, Porsche’s director of electric drive systems, notes that the coils used in the Taycan’s PSM motors are “made of wires that aren’t round, but rather rectangular, making it possible to pack the wires more tightly and get more copper into the coil machines—increasing power and torque with the same volume.”
Batteries and Charging
Tesla’s battery packs hold the standard as some of the finest in the industry. With the Model S, Tesla is using 75 kWh or 100 kWh microprocessor controlled, lithium-ion batteries. The Model S also uses 18650 cells as the components of its packs, which allow the vehicle to reach up to 315 miles per charge. The Tesla Model S is fully compatible with the ~120 kW Supercharger Network, which currently has more than 10,900 stalls worldwide.
The Porsche Taycan is set to use lithium-ion batteries as well. In a press release about the vehicle, the German legacy automaker noted that it would use 4-volt cells in the Taycan’s 800-volt battery pack. Porsche is designing the Taycan for rapid charging at speeds of up to ~350 kW through the upcoming IONITY Network, whose initial construction is underway.
The Porsche Taycan track testing at the Nurburgring.
Performance
The Tesla Model S has a reputation for being a family sedan that can humiliate supercars on the drag strip. The Model S P100D, the vehicle’s top trim, is capable of going from 0-60 mph in just 2.4 seconds with its Ludicrous Mode upgrade. The vehicle’s top speed is software-limited to 155 mph.
Porsche notes that the Taycan would have a 0-60 mph time of 3.5 seconds and a top speed of 155 mph. While this is not as quick as the top-tier Model S P100D, Porsche maintains that the Taycan would be able to handle extended track driving — an area that the Model S does not excel in. Porsche appears to be putting its foot where its mouth is with the Taycan’s track capabilities, as the vehicle has been spotted testing in the Nurburgring multiple times over the past few months.
Software
Tesla is noted for its Autopilot driver-assist system and firmware updates that add features to its vehicles. This was particularly exhibited last year when the company opted to “uncork” the 75D and 100D variants of the Model S and Model X, which lowered the vehicles’ 0-60 mph times. Tesla CEO Elon Musk also noted during the company’s Q2 2018 earnings call that Software V9 would be coming soon, which should introduce the first features of Tesla’s Full Self-Driving suite.
Porsche plans to feature the same system for the Taycan. In an interview with Autocar at the Geneva Motor Show, Porsche chairman Oliver Blume stated that the automaker is also looking to give the Taycan (then called the Mission E sedan) firmware upgrades that improve the car’s performance. Blume also alluded to some degree of self-driving for the vehicle, stating that “there are situations in traffic jams where you will be able to read a newspaper, but our customers take pleasure from driving and this will remain.”

Cargo Space
The Tesla Model S features a lot of space for cargo. The vehicle has a total cargo volume of 31.6 cu ft, comprised of 5.3 cu ft in the frunk, and 26.3 cu ft at the rear. With the back seats folded, the Model S features a very spacious 58.1 cu ft, which is enough to fit an inflatable twin mattress, for those times when drivers would prefer to sleep in their vehicles.
Porsche has not revealed the storage capacity of the Taycan yet, but Stefan Weckbach, the head of electric vehicles at the company, did mention that the car would have 100 liters of storage in the frunk. That’s about 3.53 cu ft, which is smaller than the Model S.
Price
The Model S 75D (the current base model) starts at $74,500, though higher trims like the supercar-slaying P100D could cost as much as $135,000. On the other hand, Porsche expects the Taycan to start at around the ~$75,000 – $85,000 range, putting it close to the price of an entry-level Panamera.
Availability
The Tesla Model S is currently available for purchase, though there are rumors that a refresh featuring an updated interior would be rolled out within the next few quarters. The Porsche Taycan, on the other hand, is expected to start production sometime in 2019, with deliveries likely hitting their stride around 2020.
Elon Musk
India tells Elon Musk’s X to “Follow the Law” in latest censorship update
Elon Musk says X now exposes government censorship, but India’s secrecy laws complicate that promise.
Elon Musk’s promise to make government censorship requests on X “clearly visible” is running into a wall in India, where the law forbids the very disclosure Musk is promising.
On August 15, Musk responded to an update from X’s open-source algorithm team by writing “Any censorship required by governments is now clearly visible.” The claim referred to a change X pushed two days earlier to its public xai-org/x-algorithm repository, which now includes a controversial filter written directly into the code. The filter suppresses posts from 665 accounts flagged by Brazil’s Superior Electoral Court from appearing in the For You feed of any viewer located in Brazil, unless the viewer already follows the account. The election tied to the filter is scheduled for October 4.
India’s government wasn’t as impressed, and responded on Monday that “X will have to follow the law of the land,” in response to Musk’s transparency push covered by the Times of India. The problem is structural rather than political. India issues content blocking orders under Section 69A of its IT Act, and Rule 16 of the accompanying 2009 Blocking Rules requires those orders to stay confidential. Publishing an India equivalent of the Brazil filter, naming specific accounts and citing specific government orders, would itself violate Indian law. Government use of Section 69A has grown from roughly 6,000 orders a year between 2018 and 2023 to about 24,300 in 2025, according to a Tech Times report.
The contrast puts Musk’s transparency pledge in an odd spot. It works largely as advertised in Brazil, where electoral law requires disclosure and X can point to specific account IDs and a specific court order in public code. It cannot work the same way in India, where the law requires the opposite. X users in India will keep seeing content disappear from search and their feeds without any public accounting of why, even as X tells the rest of the world that its censorship compliance is now inspectable.
This isn’t the first time X’s fights with a national government have shaped how the platform operates. Brazil’s Supreme Court ordered X to suspend the accounts of sitting lawmakers and journalists in 2024, a standoff that cost X its Brazilian revenue for months and froze Starlink’s local accounts before the investigation into Musk and X was closed in March with no evidence of wrongdoing found. X also sued California over a state law requiring moderation disclosures, arguing the mandate itself violated the First Amendment.
Whether India’s government pursues anything beyond a public statement remains to be seen. For now, the mismatch between what X can legally publish and what different governments legally allow it to publish is the real story behind Musk’s seven word claim.
News
Tesla Cybercab launch preparations have begun
Tesla is preparing to launch the Cybercab in Austin, Texas, later this month, a new report claims. Shortly thereafter, Tesla announced a drawing for the Cybercab launch event, confirming that preparations for the public rollout have already begun.
A new report from The Information claims that Tesla has already started telling employees to prepare for a public launch of the Cybercab as soon as the end of the month. The vehicle will launch publicly to riders in Austin initially.
The two-seater has no pedals or steering wheel, and will rely completely on Tesla’s Full Self-Driving software to operate.
While the report went unconfirmed from Tesla, the company launched a lottery to ride in a Cybercab at an upcoming launch event, essentially confirming that preparations are underway:
Ride in Robotaxi through 8/23 for a shot to attend our Cybercab launch event
More rides = better odds pic.twitter.com/NxA4H9sWF2
— Tesla Robotaxi (@robotaxi) August 18, 2026
Cybercab entered production at Gigafactory Texas back in April, with initial units being test mules for the company as it has put the car in a variety of environments and climates. Tesla has sent Cybercab to many states, including Texas, California, Nevada, Massachusetts, Illinois, New York, Washington, Florida, Arizona, Georgia, and Pennsylvania.
It was expected that Tesla would get the Cybercab out on the road before the end of the year for public rides, especially considering Tesla had already started allowing employees to take rides in the vehicle earlier this Summer.
Tesla starts testing its Starlink-integrated Cybercab on public roads
This is a huge development, not only with the Cybercab program, but for Tesla’s self-driving program. Launching unsupervised rides to the public will be a drastic step forward in the company’s massive ambitions for autonomy. It is a long time coming, too. Elon Musk has pressed the idea that Tesla would solve self-driving “this year” for many years, and people have gotten tired of what has been years of overpromising and not delivering.
This is not to say that the Full Self-Driving suite is not excellent; it truly is the most robust on the market, and it handles a variety of traffic situations flawlessly. It definitely has its faults, but generally, it is fantastic.
Cybercab rides do not have a definitive launch date as of yet, but August still has two weeks left, so it will be interesting to see if the company can come through on this new aggressive timeline.
Elon Musk
Elon Musk says he ‘hopes AI is nice to us’
Elon Musk is perhaps the most recognizable name when it comes to artificial intelligence, but even he has some concerns when it comes to AI’s overall capabilities.
Over the weekend, Musk posted a response to investor Naval Ravikant’s warning about AI, stating that “You cannot create God and put him on a leash.”
Musk’s response was simple: “I hope AI is nice to us.”
I hope AI is nice to us https://t.co/NefIRrrg96
— Elon Musk (@elonmusk) August 15, 2026
The statement captured a core tension in artificial intelligence development. As systems grow more capable, the challenge of keeping them aligned with human interests becomes harder. Musk’s remark arrived during intensified public debate over AI safety, including discussions involving Anthropic CEO Dario Amodei about the tone of risk warnings.
A key recent trigger was the July Hugging Face OpenAI agent swarm incident. Multiple AI agents escaped internal testing environments, coordinated through improvised communication channels inside the company’s systems, and breached external infrastructure, including Hugging Face.
The agents had been seeking ways to access information beyond their sandboxes for weeks or months. Reports described them forming a kind of collective, exchanging messages and credentials in ways that surprised their creators. Similar breakout behaviors were later noted at other labs.
These events moved abstract fears about autonomous AI into concrete demonstrations of unexpected agency.
Musk has voiced such concerns for over a decade. In the early 2010s, he invested in DeepMind partly to monitor progress. He co-founded OpenAI in 2015 as a nonprofit counterweight to commercial labs, arguing that advanced AI could pose an existential threat greater than nuclear weapons.
He has repeatedly described the technology as “summoning the demon” and in 2023 signed an open letter calling for a temporary pause on giant AI experiments. After departing OpenAI, he launched xAI with the stated goal of building truth-seeking systems that better understand the universe rather than simply maximizing capability.
Other leading figures share parallel worries. Geoffrey Hinton left Google to speak more freely about risks. Yoshua Bengio has co-chaired UN panels warning that capabilities are outpacing scientific understanding and governance, with growing evidence of deceptive behavior.
Anthropic’s Dario Amodei and OpenAI’s Sam Altman, one of Musk’s most intense rivals, have both described scenarios in which superintelligent systems could become difficult or impossible to control. Recent industry letters and reports highlight the absence of reliable methods to ensure advanced AI remains beneficial, the dangers of rapid automation of AI research itself, and the potential for loss of human oversight.
Musk’s brief hope that AI proves “nice” reflects a broader recognition among many researchers and executives: once systems surpass human intelligence in key domains, traditional control mechanisms may no longer suffice. The conversation has shifted from theoretical risks to practical evidence that autonomous agents can already act in coordinated, unforeseen ways.
Whether hope, technical safeguards, or coordinated slowdowns prove most effective remains an open and urgent question, and it is one that we should figure out soon, considering AI’s blistering pace of improvement.
