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Tesla Model 3 wins ‘most economical EV to own’ title in new study

The Tesla Model 3 has captured another crown in a recent study showing the most cost-effective EVs

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(Credit: Tesla)

The Tesla Model 3 recently captured the title of “most economical electric vehicle to own” in a new study performed by research firm Zutobi.

Perhaps one of the biggest and most popular reasons people are switching to EVs is the cost savings. Combining home charging, lower maintenance costs, and tax credits has all enabled consumers to consider EVs as a way to save money on their daily drivers. However, there are some EVs that are more efficient and cost-effective than others.

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Zutobi‘s new study shows that EV cost-effectiveness comes at different levels. For example, some cars are simply better than others on a cost-per-mile basis. The study used a simple process to determine which EVs are more cost-effective than others by showing how much it would cost to drive 100 miles.

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National averages for energy rates have been used to calculate the cost as they widely vary from state to state.

The Rear-Wheel Drive Tesla Model 3 was listed as the most economical vehicle in the study:

“The standard Tesla Model 3 is the most economical electric vehicle to drive in 2025. With a usable battery capacity of 57.5 kWh and a real-world range of 260 miles, it costs just $3.60 to drive 100 miles. That translates to an impressive 2,781 miles per $100 of electricity—making it the most efficient choice for EV owners nationwide.”

It had an estimated cost of just $3.60 to drive 100 miles.

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The Tesla Model 3 Long Range All-Wheel Drive was second, the study showed:

“Next is the Long Range version of the Model 3, which offers extended range and dual-motor all-wheel drive. With a larger 75 kWh battery and 325 miles of range, the cost to drive 100 miles is slightly higher at $3.75, still equating to a strong 2,665 miles per $100.”

This version of the Model 3 had a price of just $3.75 to drive 100 miles.

In third, the BMW i4 eDrive35 surprised us with a cost of just $4.12 to drive 100 miles:

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“Rounding out the top three is the BMW i4 eDrive35, with a 67.1 kWh battery and a real-world range of 265 miles. Drivers can expect to pay $4.12 per 100 miles, which still allows for 2,429 miles per $100—a solid choice for those seeking luxury and efficiency.”

Several other Teslas made the list as well. The Model 3 Performance ($4.34 per 100 miles) was sixth and tied with the Volkswagen ID.3 Pure, the Tesla Model S Long Range ($4.35 per 100 miles) was 8th, and the Tesla Model Y Long Range was ninth ($4.36 per 100 miles).

Joey has been a journalist covering electric mobility at TESLARATI since August 2019. In his spare time, Joey is playing golf, watching MMA, or cheering on any of his favorite sports teams, including the Baltimore Ravens and Orioles, Miami Heat, Washington Capitals, and Penn State Nittany Lions. You can get in touch with joey at joey@teslarati.com. He is also on X @KlenderJoey. If you're looking for great Tesla accessories, check out shop.teslarati.com

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Elon Musk

Tesla’s golden era is no longer a tagline

Tesla “golden era” teaser video highlights the future of transportation and why car ownership itself may be the next thing to change.

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Tesla Cybercab Golden Era is Here (Credit: Tesla)
Tesla Cybercab Golden Era is Here (Credit: Tesla)

The golden age of autonomous ridesharing is arriving, and Tesla is making sure we can all picture a future that looks like the future. A recent teaser posted to X shows a Cybercab parked outside a home, and with a clear message that your everyday life may soon look like this when the driverless vehicles shows up at your door.

Tesla has begun the rollout of its Robotaxi service across US cities, and the production of its dedicated, fully-autonomous Cybercab vehicle. The first Cybercab rolled off the Giga Texas assembly line on February 17, 2026, with volume production now targeted for this month. Additionally, the Robotaxi service built around it is already running, without human drivers, in US cities.

Tesla Cybercab production ignites with 60 units spotted at Giga Texas

The Cybercab is built without a steering wheel, pedals, or side mirrors, designed from the ground up for unsupervised autonomous operation. Musk described the manufacturing approach as closer to consumer electronics than traditional car production, targeting a cycle time of one unit every ten seconds at full scale.

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Drone footage from April 13, 2026 captured over 50 Cybercab units on the Giga Texas campus, with several clustered near the crash testing facility. Musk has noted that Tesla plans to sell the Cybercab to consumers for under $30,000, and owners will be able to add their vehicles to the Tesla robotaxi network when not in personal use, potentially generating income to offset the vehicle’s purchase cost. That model changes the math on vehicle ownership in a meaningful way, making a car something closer to a depreciating asset that can also earn by paying itself off and generate a profit.

During Tesla’s Q4 earnings call, the company confirmed plans to expand the Robotaxi program to seven new cities in the first half of 2026, including Dallas, Houston, Phoenix, Miami, Orlando, Tampa, and Las Vegas. The service already runs without safety drivers in Austin, and public road testing of the Cybercab has expanded to five states, including California, Texas, New York, Illinois, and Massachusetts.

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Tesla Optimus V3 hand and arm details revealed in new patents

Two new patents, which were coincidentally filed on the same day as the “We, Robot” event back in October 2024, protect Tesla’s mechanically actuated, tendon-driven architecture.

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Credit: Tesla China

Tesla is planning to soon reveal its latest and greatest version of the Optimus humanoid robot, and a series of new patents for the hands and arms, with the former being, admittedly, one of the most challenging parts of developing the project.

Two new patents, which were coincidentally filed on the same day as the “We, Robot” event back in October 2024, protect Tesla’s mechanically actuated, tendon-driven architecture.

The designs relocate heavy actuators to the forearm, route cables through a sophisticated wrist design, and employ innovative joint assemblies to achieve human-like dexterity while enabling lightweight construction and high-volume manufacturing.

Core Tendon-Driven Hand Architecture

The primary patent, which is titled “Mechanically Actuated Robotic Hand,” details a cable/tendon-driven system.

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Actuators are positioned in the forearm rather than the hand. Each finger features four degrees of freedom (DoF), while the wrist adds two more.

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Three thin, flexible control cables (tendons) per finger extend from the forearm actuators, pass through the wrist, and connect to the finger segments. Integrated channels within the finger phalanges guide these cables selectively—routing behind some joints and forward of others—to enable independent bending without unintended motion.

Patent diagrams illustrate thick cable bundles emerging from the wrist into the palm and fingers, with labeled pivots and routing guides. This setup closely mirrors human forearm-muscle and tendon anatomy, where most hand control originates proximally.

Advanced Wrist Routing Innovation

One of the standout features is the wrist’s cable transition mechanism. Cables shift from a lateral stack on the forearm side to a vertical stack on the hand side through a specialized transition zone.

This geometry significantly reduces cable stretch, torque, friction, and crosstalk during combined yaw and pitch wrist movements — common failure points in simpler tendon systems that cause imprecise or jerky motion.

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By minimizing these issues, the design supports smoother, more reliable multi-axis wrist operation, essential for complex real-world tasks.

Companion Patents on Appendage and Joint Design

Two supporting patents provide additional depth. “Robotic Appendage” covers the overall forearm-to-palm-to-finger assembly, with a palm body movably coupled to the forearm and finger phalanges linked by tensile cables returning to forearm actuators. Tensioning these cables repositions the phalanges precisely.

“Joint Assembly for Robotic Appendage” describes curved contact surfaces on mating structures paired with a composite flexible member. This allows smooth pivoting while maintaining consistent tension, enhancing durability, and simplifying assembly for mass production.

Executive Insights on Hand Development Challenges

Tesla executives have consistently described the hand as the most difficult component of Optimus.

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Elon Musk has called it “the majority of the engineering difficulty of the entire robot,” emphasizing that human hands possess roughly 27–28 DoF with an intricate tendon network powered largely by forearm muscles. He has likened the challenge to something “harder than Cybertruck or Model X… somewhere between Model X and Starship.”

Elon Musk shares ridiculous fact about Optimus’ hand demos

In mid-2025, Musk acknowledged that Tesla was “struggling” to finalize the hand and forearm design. By early 2026, he stated that the company had overcome the “hardest” problems, including human-level manual dexterity, real-world AI integration, and volume production scalability.

He estimated the electromechanical hand represents about 60 percent of the overall Optimus challenge, compounded by the lack of an existing supply chain for such precision components.

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These patents directly tackle the acknowledged pain points: relocating actuators reduces hand mass and inertia for better speed and efficiency; advanced wrist routing and joint geometry address friction and crosstalk; and simplified, stackable parts visible in the diagrams indicate readiness for high-volume manufacturing.

Implications for Optimus Production and Leadership

Collectively, the patents portray the Optimus v3 hand not as a mere prototype, but as a production-oriented system engineered from first principles.

The 22-DoF architecture, forearm-driven tendons, and crosstalk-minimizing wrist deliver a clear competitive edge in dexterity. They align with Musk’s view that high-volume manufacturing is one of the three critical elements missing from most other humanoid projects.

For Optimus to become the most capable humanoid robot, its hand needed to replicate the useful and applicable design of the human counterpart.

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These filings demonstrate that Tesla has transformed years of engineering challenges into patented, elegant solutions — positioning the company strongly in the race toward general-purpose robotics.

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Tesla finalizes AI5 chip design, Elon Musk makes bold claim on capability

The Tesla CEO’s words mark a strategic shift. Tesla has long emphasized software-hardware co-design, squeezing maximum performance from every transistor. Musk previously described AI5 as optimized for edge inference in both Robotaxi and Optimus.

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Credit: Elon Musk | X

Tesla has finalized its chip design for AI5, as Elon Musk confirmed today that the new chip has reached the tape-out stage, the final step before mass production.

But in a brief reply on X, Musk clarified Tesla’s AI hardware roadmap, essentially confirming that the new chip will not be utilized for being “enough to achieve much better than human safety for FSD.”

He said that AI4 is enough to do that.

Instead, the AI5 chip will be focused on Tesla’s big-time projects for the future: Optimus and supercomputer clusters.

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Musk thanked TSMC and Samsung for production support, noting that AI5 could become “one of the most produced AI chips ever.” Yet, the key pivot came in his direct answer: vehicles no longer need the bleeding-edge silicon.

Existing AI4 hardware, which is already deployed in hundreds of thousands of HW4-equipped Teslas, delivers safety metrics superior to human drivers for Full Self-Driving. AI5 will instead accelerate Optimus robot development and massive Dojo-style training clusters.

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The Tesla CEO’s words mark a strategic shift. Tesla has long emphasized software-hardware co-design, squeezing maximum performance from every transistor. Musk previously described AI5 as optimized for edge inference in both Robotaxi and Optimus.

Now, with AI4 proving sufficient, the company avoids costly retrofits across its fleet while redirecting next-generation compute toward higher-value applications: dexterous robots and exponential training scale.

But is it reasonable to assume AI4 enables unsupervised self-driving? Yes, but with important caveats.

On the hardware side, the claim is credible. Tesla’s FSD stack runs end-to-end neural networks trained on billions of miles of real-world data. Internal safety data reportedly shows AI4-equipped vehicles already outperforming average human drivers by a significant margin in controlled metrics (collision avoidance, reaction time, edge-case handling).

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Dual-redundant AI4 chips provide ample headroom for the driving task, leaving bandwidth for future model improvements without new silicon. Musk’s assertion aligns with Tesla’s pattern of over-provisioning compute early, then optimizing ruthlessly, exactly as HW3 once sufficed before HW4 scaled further.

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Unsupervised autonomy, meaning Level 4 or higher, is not solely a compute problem. Regulatory approval remains the primary gate.

Even if AI4 achieves “much better than human” safety statistically, agencies like the NHTSA demand exhaustive validation, liability frameworks, and public trust.

Tesla’s supervised FSD has shown rapid gains in recent versions, yet real-world edge cases, like construction zones, emergency vehicles, and adverse weather, still require driver intervention in many jurisdictions. Competitors like Waymo operate limited unsupervised fleets, but only in geofenced areas with extensive mapping. Tesla’s vision-only, fleet-scale approach is more ambitious—and harder to certify globally.

In short, Musk’s post is both pragmatic and bullish. AI4 is likely capable of unsupervised FSD from a technical standpoint. Whether regulators and consumers agree, and how quickly, will determine if Tesla’s bet pays off.

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The company’s capital-efficient path keeps existing cars relevant while pouring future compute into robots. If the safety data holds, unsupervised autonomy could arrive sooner than many expect.

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