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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
Tesla AI boss reveals how big Optimus is going to get
Tesla’s Optimus chief corrected himself on X, confirming a staggering 10 million robot production target.
Tesla’s Optimus program has a new number attached to it, after Ashok Elluswamy, the executive who has run the humanoid robot program since June 2025, posted a three word correction on X Thursday, “Correction, 10 million robots.”
The line clarifies the long term annual capacity Tesla is building toward its planned second Optimus production line at Gigafactory Texas, a figure Musk has cited repeatedly since last year’s shareholder meeting.
The scale is worth noting, because ten million robots a year would mean Tesla building more units annually than most countries sell in new cars. Tesla has framed this as a second line, not the first. The buildout is happening in two phases: a roughly one million unit per year line inside Tesla’s Fremont factory, installed on the floor space vacated when Model S and Model X production ended earlier this year, and a much larger dedicated facility under construction at Giga Texas that broke ground on its first steel structure in May. That Texas facility is the one Elluswamy’s correction refers to, and is expected to reach volume production sometime in 2027.
Correction, 10 million robots https://t.co/0z4nyQNTzp
— Ashok Elluswamy (@aelluswamy) July 30, 2026
Tesla Optimus project fires up as Musk sees production line progress
Elluswamy took over Optimus from Milan Kovac last summer and has spent the months since talking up the program’s trajectory. Elon Musk has also floated the ten million figure at Tesla’s 2025 shareholder meeting.
Ending Model S and Model X production to make room for the first Optimus line was one of the more consequential manufacturing decisions in the company’s recent history, retiring two flagship vehicles in favor of a robot that has yet to enter mass production. Musk has previously estimated per unit production costs at $20,000 to $25,000 once Tesla reaches a million units a year, though he hasn’t said what that cost looks like at ten times the volume.
News
Autonomous vehicle red tape gets slashed by Trump Administration
The Trump Administration today made several key moves to help with the deployment of autonomous vehicles by cutting overreaching red tape that has stifled growth and innovation for years.
The moves, which were put forth by the National Highway Traffic Safety Administration (NHTSA), aim to grant temporary exemptions to at least one company currently, although that could expand in the coming months. Additionally, it will work with organizations to develop standards and a sound but efficient regulatory landscape.
Zoox is the only company mentioned explicitly by the Trump Administration in its press release announcing the new terms today. They will receive a temporary two-year exemption that will allow the commercial deployment of up to 2,500 vehicles annually for two years.
There is a potential exemption for Robomart, Inc., which “requests a temporary exemption from certain FMVSS No. 500 requirements for a low-speed vehicle operated by an ADS without a human driver onboard. NHTSA will publish a separate notice seeking public comment on its merits once the initial evaluation is complete,” the agency said.
Here are the five new terms that Secretary Sean Duffy has implemented through the NHTSA today:
- Allow Zoox to commercially deploy its robotaxis through a temporary exemption.
This temporary exemption will allow the commercial deployment of up to 2,500 vehicles annually for two years, subject to an enhanced, adaptable oversight structure that can evolve as Zoox’s technology advances. - Accelerate development of first-ever AV performance standards through a partnership with SAE Industry Technologies Consortia (ITC).
This partnership will fund a three-year, $5 million “A2SCEND” consortium, bringing together experts to gather data and accelerate creation of the first-ever AV performance standards. This project will inform a single national standard for AV safety to eliminate the patchwork regulatory landscape that has stifled innovation for years. - Publish an interim final rule that allows vehicles manufactured prior to an exemption to be eligible for a commercial deployment exemption.
This rule will modernize the application process and improve access to exemptions for innovators, including AV developers, by granting the NHTSA Administrator the discretion to apply temporary exemptions to vehicles manufactured prior to the effective date of an exemption grant. - Streamline the application process for Part 555 exemptions by updating guidance and soliciting feedback from the public.
By updating the Part 555 exemption process—which allows automakers to temporarily sell a limited number of non-compliant vehicles, primarily to test new technologies—NHTSA is aiming to create a more flexible oversight structure for exemptions and summarize recent AV framework activities, including expanded exemption pathways, streamlined crash reporting, and ongoing efforts to modernize Federal Motor Vehicle Safety Standards (FMVSS). - Establish a new Federal Docket for public feedback on NHTSA’s updated safe AV development and deployment guidance.
NHTSA is updating its technical guidance for AVs for the first time since 2017—focusing on key safety areas like emergency responder interactions, safety management systems, remote assistance, and post-crash behavior to help the industry scale up driverless deployments safely.
Additionally, the NHTSA said it has modernized some safety standards by proposing updates to:
- FMVSS 102 – Transmission shifting
- FMVSS 103/104 – Windshield defrosting and wiping
- FMVSS 110 – Tire placards
- FMVSS 135 – Braking systems
- FMVSS 101 – Controls and displays
- FMVSS 108 – Vehicle lighting
- FMVSS 111 – Mirrors and rearview display
- FMVSS 126 – Electronic stability control systems
- FMVSS 201/208 – Sun visors and warning labels
These changes aim to make the regulatory process for autonomous vehicles more streamlined and efficient, which could help the U.S. gain dominance over autonomous vehicle systems moving forward.
Elon Musk
Elon Musk has a crazy prediction about AI in two years
Elon Musk is, in many respects, one of the biggest and most influential figures in modern-day artificial intelligence.
Given that Tesla, SpaceX, and xAI are all looked at in their respective fields as leaders to an extent, each of them has a heavy influence on the future of AI, even though two of them are not thought of, at face value, as AI companies.
Musk has grand expectations for what is to come with AI, not only as a form of assistance to make human lives easier, but to make humans multiplanetary and solve some of the biggest issues that face us today. But even he is astounded by AI’s pace of progress.
He believes that in two years, AI will be so mind-blowing it might be unrecognizable.
Given that AI from 2 years ago feels so old that it should be in a museum, then obviously AI 2 years from now will be mind-blowing https://t.co/TcsKZ8o8OE
— Elon Musk (@elonmusk) July 30, 2026
This progress can be seen in a variety of ways, but perhaps the most popular way people have shown AI’s progress, especially on social media, is through an incredibly arbitrary way of watching Will Smith eat spaghetti:
The progression in AI of Will Smith eating spaghetti (2023 – 2026) pic.twitter.com/VDv82mB5gs
— internet hall of fame (@InternetH0F) February 10, 2026
This is a great way to show people how AI is improving, especially from a perspective that examines how it can manufacture images and video from prompts. AI is an incredibly complex concept, however, and it goes much deeper than Will Smith eating Italian food.
Musk’s most widely adopted method of AI is likely Tesla Full Self-Driving, which impacts millions of people as they utilize it to increase safety with their travel. Musk has routinely pushed incredibly aggressive timelines for self-driving, especially unsupervised.
Perhaps this perspective is why he feels that things will be solved in a timeframe that is much more aggressive than most of us would think. Regardless, the progress of AI is moving fast, and it seems that Musk’s expectations for it could be high.
But if it can actually achieve full-length motion pictures and even more realistic production value, it will be hard to distinguish between reality and AI very soon.

