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Tesla Model 3 travels longest but deemed ‘least efficient’ in Polestar-backed study

(Credit: u/gs2k1/Reddit)

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The battle for the top of the midsize electric vehicle segment just got a bit spicier, as a Polestar-backed study recently deemed the Tesla Model 3 as the “least efficient” vehicle following a “real-world” test against two variants of the Polestar 2, the Audi e-tron, and the Jaguar I-PACE. The study came to this conclusion despite the Model 3 going the farthest distance while having the smallest battery pack. 

The tests were conducted by FT Techno, an independent automotive research group based in Michigan whose services include vehicle evaluation like IIHS and NCAP standardization. As noted in a Jalopnik report, Polestar was actually the source of the study. 

Polestar’s test aimed to determine the efficiency of five electric vehicles that are currently on sale in a setting that is equivalent to a “real-world” environment. This allowed FT Techno of America, LLC to examine and evaluate how much of a vehicle’s claimed range could be achieved during sustained highway speeds. The vehicles included a standard Polestar 2, a Polestar 2 with Performance Package, a Jaguar I-PACE, an Audi e-tron, and a Tesla Model 3 Performance. 

(Credit: Top Gear)

The “real-world” test conducted by FT Techno involved the vehicles traveling at 70 mph on an oval track to mimic a road trip. Climate control was set at 72 degrees, and outside temperatures were at 85 degrees. Regenerative braking was disabled or changed to its least-aggressive setting for the purposes of the test, and each car was pushed until its battery was completely depleted. 

As noted in a Roadshow report, the Audi e-tron was deemed “most efficient,” since the SUV was able to travel 187 miles before running out of charge, or 92% of its EPA range of 204 miles. Next in line was the standard Polestar 2, which was able to achieve 82% of its estimated EPA range of 250 miles by traveling 205 miles. Following was the Jaguar I-PACE, which was able to travel 188 miles before running out of battery, achieving 80% of its EPA range of 234 miles. 

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(Credit: FT Techno)

The Polestar 2 with Performance Package was able to achieve 79% of its estimated 250-mile EPA range, traveling 197 miles before running out of charge. At the bottom of the pile was the Tesla Model 3 Performance, which ran out of battery after 234 miles, or just 75% of its EPA range of 310 miles. With this in mind, the Polestar-backed study deemed the Model 3 the least efficient EV among the cars it evaluated. 

Interestingly enough, FT Techno has not highlighted the miles per kWh for each vehicle, nor did the firm emphasize the distance traveled by the vehicles compared to the respective sizes of their battery packs. Both these factors could have skewed the test a bit towards the Model 3’s favor, considering that it has the smallest battery pack and it was still able to reach the farthest distance before its battery was fully drained. 

Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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Elon Musk

Tesla Hardware 3 owners could be made whole this month

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Credit: Tesla Asia/Twitter

Tesla Hardware 3 owners are set to get a new Full Self-Driving version this month as the company plans to release what it is referring to as v14 Lite.

The rollout is not yet confirmed for June, but Tesla executives have stated on several occasions that this more refined FSD iteration will work with their cars and increase its capabilities.

This comes after Tesla admitted during its last Earnings Call that these Hardware 3 vehicles would not be able to achieve Full Self-Driving, something that they did not know when they bought these cars. We regularly receive messages from Hardware 3 owners asking when v14 Lite will come out, what they should expect, and whether it is worth it to upgrade the self-driving computer or buy a new car altogether.

It is hard not to feel for them; Tesla CEO Elon Musk said at the company’s 2019 Autonomy Day that all vehicles produced at the time, including Hardware 3 cars, had “all the hardware necessary, compute and otherwise, for Full Self-Driving.”

Musk also said in March of that year that, “Anyone who purchased Full Self-Driving will get FSD computer upgrade for free.”

However, during the Q1 2026 Earnings Call, Musk admitted that Hardware 3 vehicles would not be capable of FSD, as “It has only 1/8th the memory bandwidth of Hardware 4, and memory bandwidth is one of the key elements needed for unsupervised FSD.”

Tesla has made some effort to remedy these Hardware 3 owners by offering:

  • Discounted trade-ins toward AI4 cars
  • Hardware retrofits, which would replace the self-driving computer and upgrade all cameras
  • Full Self-Driving v14 Lite

The issue is that many of these owners were led to believe their cars would be capable of unsupervised self-driving. Now, they’re left scrambling for options, and while there are several, they will all require more money out of their pockets.

Expectations for Tesla v14 Lite for Hardware 3 Owners

The big differences between the AI4 v14 and v14 Lite for Hardware 3 owners will stem primarily from hardware constraints. Tesla developed v14 Lite with an optimized frame of mind; the v14 neural nets are toned down to run on an HW3 computer.

Tesla v14 will use the same behavior, but its limits will be hardware-related, especially given that the cameras on HW3 vehicles are lower-resolution.

Tesla reveals its plans for Hardware 3 owners who are eager for updates

This will result in potentially more edge cases due to the lower quality perception and less long-range detection, but reaction time and overall confidence should be more refined.

There should also be a handful of additional features that are available on AI4 cars, such as:

  • Starting Full Self-Driving from Park
  • Auto Shift
  • Streaks
  • Speed Profiles
  • Improved Dynamics, like Pulling Over for Emergency Vehicles

Tesla plans to release v14 Lite this month, but we are all familiar with how the company can be with timelines. Additionally, if v14 Lite has not proven to be ready for a wide release, Tesla will slam the brakes on the rollout.

We would anticipate that Tesla is testing v14 Lite internally, and likely has been for several months.

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SpaceXAI just launched into your kitchen with their new app

SpaceXAI just powered its first consumer app and it predicts what you want to buy.

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SpaceXAI just made its first move into consumer AI, and it involves your grocery cart. On June 3, 2026, Gopuff and SpaceXAI announced the launch of Go, a Grok-powered shopping assistant built directly into the Gopuff app that predicts what you need before you even start searching for it.

Gopuff is an instant delivery platform that operates more than 400 micro-fulfillment centers across the U.S., delivering everyday essentials, snacks, drinks, and household items in as little as 15 minutes. It is not a restaurant delivery app or a marketplace. It owns its inventory, controls its warehouses, and handles its own logistics, which means it has built one of the most detailed consumer behavior datasets in retail over its 13-year history.

Go combines SpaceXAI’s advanced reasoning, voice, and image generation models with Gopuff’s dataset of hundreds of millions of orders and real-time cultural signals from X to prepare a suggested cart the moment a customer opens the app. It learns each shopper’s habits and automatically builds a personalized cart based on time of day, location, order history, and real-time indicators. Returning customers can check out with a single tap.


Rather than searching for specific items, users can describe a situation like a game-day party or the desire for a healthy breakfast and Go will assemble a cart automatically. It can also predict when shoppers are running low on items like coffee or paper towels and have them packed and delivered in under 15 minutes. Grok voice integration lets users talk to the app in plain conversational language and check out completely hands-free.

Gopuff co-founder and co-CEO Yakir Gola said: “Today, we believe the greatest friction left in commerce is not delivery or instantaneous access to the essentials customers need. It’s the moment before: the thinking, the deciding, the remembering. We’re combining Gopuff’s demand intelligence with xAI’s frontier reasoning to create an everyday shopping experience that feels like a true extension of you.”

Why SpaceX just made a $60 billion bet on AI coding ahead of historic IPO

The timing carries context beyond the product launch. SpaceXAI was formed after SpaceX completed an all-stock merger with Elon Musk’s xAI earlier this year, folding one of the most advanced AI labs in the world into the same corporate structure as the company preparing what could be the largest IPO in history. SpaceXAI is dipping into consumer-focused AI just as it prepares for its public debut, and while Musk has openly discussed building an everything app, this launch uses Grok to power another company’s product rather than launching a standalone consumer platform. Every consumer-facing deployment of Grok ahead of the IPO roadshow adds tangible evidence that SpaceXAI is not just an infrastructure play but a direct competitor in the AI application layer where OpenAI and Google are already fighting for dominance.

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Tesla adds new Supercharger feature for a better idea of what to expect

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Credit: Tesla

Tesla has introduced an enhanced visualization in its Supercharger navigation system, building directly on the Site Maps feature rolled out a few months ago.

This latest software update adds detailed 3D icons that represent specific vehicle models parked at charging stalls, offering drivers a more precise view of site occupancy and layout.

The Site Maps debuted in Tesla’s 2025 Holiday Update, providing 3D overviews of select Supercharger locations with real-time stall availability.

Tesla supplements Holiday Update by sneaking in new Full Self-Driving version

Drivers could see which spots were open, occupied, or out of service when navigating to supported stations.

Now, the system takes this capability further by rendering accurate representations of Tesla vehicles, including distinctions between models such as the Model 3, Model Y, Model S, Model X, and Cybertruck. These icons appear as lifelike 3D renderings, complete with recognizable shapes and proportions that match the actual cars charging at the site:

This refinement improves the user experience during road trips and daily charging stops. As drivers approach a Supercharger, the navigation display now shows not just generic occupied markers but identifiable vehicle types plugged into each stall.

Blue indicators highlight active charging sessions, while other visual cues denote availability or maintenance status. The feature integrates seamlessly with the existing map interface, allowing quick assessment of the best available spot based on vehicle size and positioning.

Tesla continues to expand the availability of these detailed Site Maps across its global network. Initially piloted at a limited number of locations, the rollout has progressed steadily, with more stations gaining support in recent software versions.

Owners benefit from better planning, as the system helps identify compatible stalls and reduces uncertainty upon arrival. The update reflects Tesla’s ongoing commitment to refining its navigation and charging ecosystem through iterative software improvements.

In addition to model-specific icons, the enhanced maps maintain all prior functionalities, such as integration with nearby amenities and energy usage predictions. This ensures a comprehensive tool for efficient Supercharging.

As Tesla’s fleet grows and the network scales, such features play a key role in optimizing the overall ownership experience. Future updates may extend similar visualizations to additional sites and incorporate even more data points for drivers.

With this piggyback enhancement, Tesla demonstrates how small but thoughtful additions can elevate an already useful tool, making Supercharger visits smoother and more informed for its customers. The company is expected to broaden the feature’s reach in upcoming releases, further solidifying its leadership in EV charging infrastructure.

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