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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.
Turn-by-turn navigation is not new technology.
For over two decades, drivers have relied on Garmin, TomTom, and later smartphone apps like Google Maps and Waze to receive precise, reliable directions. These systems have guided millions safely through unfamiliar cities, highways, and backroads with remarkable effectiveness. They handle real-time traffic, construction detours, and complex intersections with minimal fuss.
Yet Tesla, the company that promised revolutionary Full Self-Driving (FSD), continues to struggle with this foundational capability. As FSD (Supervised) v14.3.4 has started rolling out to cars this week, navigation remains its glaring Achilles’ heel, undermining the entire autonomous vision.
Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much
Tesla’s FSD excels in many driving behaviors—smooth acceleration, confident lane changes in ideal conditions, and responsive handling of visible obstacles. However, when it comes to following a route accurately, the system falters repeatedly.
Owners report wrong turns, missed exits, inefficient routing through local roads instead of highways, phantom speed limit errors, and even directing vehicles to building rear entrances. Interventions for navigation issues often outnumber those for core driving maneuvers. Tesla has begun surveying owners specifically about these errors, acknowledging the problem after years of complaints.
Navigation is perhaps my biggest complaint when it comes to FSD, because sometimes, we do know better. Some of us have been living in our areas for our entire lives, but even those who have not have years or even decades of experience driving on local roads. We might know a little better about routing.
But the navigation mistakes are more than just FSD potentially taking a slightly different route that may or may not save you a few minutes. Sometimes, they’re genuinely mind-boggling.
This isn’t just annoying; it cascades into broader failures. A flawed route plan confuses the AI’s decision-making, leading to hesitant behavior, unnecessary disengagements, or dangerous maneuvers like attempting impossible U-turns or ignoring clear ramps. In a system meant to operate with minimal supervision, unreliable navigation erodes trust.
More often than not, false or plain incorrect navigation is what causes me to interrupt FSD operation. Unfortunately, I believe the latest FSD version is the worst example of it, and it leads me to believe that Tesla might be making some changes; they’ve just made them in the wrong direction.
It makes you wonder: Why is a company that has done so much with the progress of FSD and autonomy struggling so much with navigation, something that is not new and has been around a long time?
Multiple Data Sources
First, Tesla’s navigation relies on a fragile patchwork of multiple data sources—Google Maps, TomTom, OpenStreetMap, Valhalla, and its own fleet-derived data—stitched together rather than a single authoritative map. When these conflict on lane geometry, road status, or turn details, the system hesitates or chooses incorrectly.
Traditional GPS providers maintain centralized, regularly validated databases with professional curation and rapid updates. Tesla’s hybrid approach, while innovative in crowdsourcing, introduces inconsistencies that a purely vision-based or end-to-end AI approach may not easily reconcile in real time.
Persistent Learning
FSD seems to struggle with persistent learning from driver interventions.
Unlike consumer apps that quickly adapt to repeated corrections or user preferences (e.g., avoiding certain routes or remembering habitual detours), Tesla’s FSD often fails to internalize fixes on the same trip or across similar scenarios. Owners note making the same manual override multiple times without the routing engine updating its behavior meaningfully.
This stems from the neural architecture prioritizing real-time perception and control over long-term route memory and personalization, making navigation feel rigid and “opinionated” compared to the adaptive logic in Waze or Google Maps.
I noticed that when I asked Grok to try and get me home a certain way (a way that FSD routinely took in the past because it was the most efficient), it had to place a waypoint between my location at the time and my house. When I went to edit the waypoint out, as Grok had placed it for a way to get FSD to get off the highway at the right exit, it was stumped again, rerouted, and took a longer way home.
The next thing I’ve noticed, and this might be controversial, is that Nav has gotten even worse.
I think that might actually be a good thing; Tesla seems to be adjusting it. They just need to adjust it the opposite way.
The car is taking extremely strange routes to very… https://t.co/UHg3tVfNA2
— TESLARATI (@Teslarati) June 16, 2026
Reasoning, Scaling, and Intuition
Third, scaling navigation for unsupervised or robotaxi ambitions requires not just accuracy but adaptability and user-like reasoning. Current FSD often defaults to single routes that ignore driver preferences or real-world nuances like time-of-day traffic patterns. It fails to match the intuitive, context-aware planning that traditional systems have refined over the years.
Resolving navigation is critical for several reasons. Practically, it is the backbone of any autonomous journey: without trustworthy routing, the car cannot reliably reach destinations, rendering FSD useless for robotaxis or hands-free commutes. Safety depends on it—mismatched plans create hesitation in merges or intersections, increasing accident risk.
Economically, Tesla’s valuation and future hinge on FSD delivering unsupervised driving; persistent navigation flaws delay regulatory approval and erode consumer confidence. For owners who paid premiums for FSD, these issues represent unfulfilled promises. While it is unlikely Tesla will lose too many customers due to bad navigation, some will be frustrated with the constant need for human input.
Tesla has achieved miracles in electric vehicles and battery tech. Mastering turn-by-turn—technology Garmin nailed in the early 2000s—should not be this hard. By investing in tighter data integration, faster learning loops from interventions, and more intuitive routing algorithms, Tesla could close this gap.
Until then, FSD’s navigation struggles highlight a humbling truth: even the most ambitious innovator must sometimes master the basics before conquering the future.
A Tesla Cybertruck driver in the United Kingdom had their all-electric pickup seized by local police in the Greater Manchester area after the department cited “legitimate concerns.”
Last Thursday, police saw the pickup on the roads and decided to pull the driver over. Greater Manchester Police said:
“Whilst this may seem trivial to some, legitimate concerns exist around the safety of other road users or pedestrians if they were involved in a collision with the Cybertruck.”
🚨 A Tesla Cybertruck, which is illegal to drive in the UK due to safety concerns, has been seized by police in Greater Manchester
“Whilst this may seem trivial to some, legitimate concerns exist around the safety of other road users or pedestrians if they were involved in a… pic.twitter.com/cqhdPok3DM
— TESLARATI (@Teslarati) June 16, 2026
The Cybertruck in question was, according to the BBC, registered and insured abroad and was confiscated. The driver, who is a UK resident, was reported.
The Greater Manchester Police Department then added:
“The Tesla Cybertruck is not road-legal in the UK and does not hold a certificate of conformity.”
The Cybertruck cannot be legally driven in the UK because it has no UK Type Approval for operation in the country. This is due to some safety concerns, which are related to its angular shape and design. The stainless steel exoskeleton has sharp edges and projections that violate UK/EU rules on pedestrian protection.
Tesla has considered creating what it referred to as an “international version” that would be approved for operation in Europe. However, there has been no real movement on that front by the company, as it has been focused on the Robotaxi rollout primarily.
A new report claims that Apple is in the process of developing what would be the missing link for Tesla to get CarPlay.
Apple and Tesla have been reportedly working together for some time to give Tesla owners the opportunity to utilize CarPlay within their vehicles. While many owners are more than happy with Tesla’s in-house UI, which is seamless, effective, and smooth, some still want CarPlay, which does have its advantages.
A report from 9to5Mac now states that a new CarPlay technology that was highlighted during the Worldwide Developers Conference (WWDC) would potentially be the bridge between Tesla and Apple. With the addition of a feature known as “Route Sharing,” which gives a navigation app the ability to share routing data with the vehicle, Tesla would be able to launch CarPlay in its vehicles, the report states.
CarPlay has not been a priority for Tesla because it has done extremely well with its in-house UI, but some drivers are just used to it. Additionally, it could improve Tesla’s subpar Navigation or offer improved app capabilities, especially with iMessage.
Route Sharing is an intended addition to CarPlay’s iteration in iOS 26.4, which was released in March:
The addition of CarPlay would undoubtedly be welcome, but at the same time, it seems like Tesla realizes it is not of the utmost priority. There are so many things that Tesla is working on currently within its own vehicles, especially attempting to solve self-driving.
Back in February, Bloomberg had reported that Tesla was still working on bringing CarPlay to its vehicles, but it had not due to app compatibility issues and incredibly low adoption rates of iOS 26.
This bottleneck could buy Tesla the proper amount of time to develop CarPlay for its vehicles. It would be a welcome addition, and could be brought on with either the Summer or Fall 2026 Software Updates.
Tesla’s Navigation Nightmare: Why the easiest part of FSD might be the hardest
Tesla Cybertruck driver gets pickup seized for ‘legitimate concerns’ in UK
