Tesla raises Cybertruck prices by up to 7% despite sluggish sales

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Reviewed by
Ashish TScanX News Team
Key Highlights
  • Tesla raises Dual-Motor AWD Cybertruck price to $74,990, a 7.1% increase
  • Premium AWD trim rises 6.2% to $84,990; Cyberbeast holds at $99,990
  • Only 7,133 Cybertrucks registered in the US through May 2026
  • Analysts note Tesla prioritizing Cybercab over Model Y Robotaxi ramp-up
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Tesla Inc. (NASDAQ: TSLA) has increased the price of its Cybertruck electric pickup truck in the United States by up to $5,000 for select trim levels. The pricing adjustment affects the entry-level and mid-range models while leaving the top-tier variant unchanged.

Cybertruck Pricing Changes

The EV manufacturer hiked the price of the Dual-Motor AWD trim to $74,990, a 7.1% increase from its previous price of $69,990. The mid-level Premium AWD trim saw a 6.2% rise to $84,990, up from $79,990. These figures were confirmed by influencer Sawyer Merritt based on data from the company’s website on August 25, 2026.

The range-topping Cyberbeast trim remains at $99,990. Consequently, the price gap between the entry-level Dual-Motor AWD and the Cyberbeast has narrowed to approximately $25,000. Tesla did not provide an explicit reason for the timing of these adjustments.

Trim Level New Price Previous Price Change
Dual-Motor AWD $74,990 $69,990 +7.1%
Premium AWD $84,990 $79,990 +6.2%
Cyberbeast $99,990 $99,990 0%

Sales Context and Product Updates

The price hike follows the launch of an entry-level trim earlier this year at $59,990 with a 325-mile range and a towing capacity of 7,500 lbs. However, demand appears limited, with only 7,133 Cybertrucks registered in the United States through May 2026.

In June, Elon Musk highlighted upcoming software features, including Actually Smart Summon, which will allow the vehicle to navigate parking lots and drive itself to the owner via a future update.

Strategic Focus and Analyst Views

JP Morgan Chase & Co. (NYSE: JPM) analysts noted in an investor note that Tesla is prioritizing the Cybercab over the Model Y Robotaxi ramp-up. The bank cited management confidence in scaling Cybercab operations and developing future models based on its platform.

Conversely, Ross Gerber of Gerber Kawasaki expressed skepticism regarding Tesla’s Full Self-Driving (FSD) capabilities. He questioned whether the HW4/AI4 chips would support unsupervised FSD, noting that FSD V15 requires additional compute power despite promised improvements.

TSLA shares rose 0.78% to $351.66 in pre-market trading on Tuesday.

Will the narrowed price gap between the Dual-Motor AWD and Cyberbeast trims cannibalize sales of the higher-margin top-tier model?

How might the limited registration numbers for the entry-level trim influence Tesla's production volume targets for 2027?

Could the prioritization of the Cybercab platform over the Model Y Robotaxi signal a strategic pivot away from traditional consumer EV sales?

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RoboStrategy CEO: Tesla's robotics edge is manufacturing, not AI

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Reviewed by
Suketu GScanX News Team
Key Highlights
  • RoboStrategy CEO Andrew Kang identifies manufacturing competency as Tesla Inc's greatest long-term advantage in robotics
  • He argues manufacturing scale enables robot production at volumes few competitors can match
  • Kang notes large amounts of robot data serve as key inputs to AI models
  • Tesla's production scale provides an advantage in procuring real-world operational data
  • The view suggests manufacturing and AI reinforce each other rather than acting as separate strengths
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Andrew Kang, chief executive of RoboStrategy Inc (NASDAQ: BOT), argues that Tesla Inc (NASDAQ: TSLA) possesses a more durable competitive advantage in humanoid robotics than its artificial intelligence capabilities suggest.

Kang told Benzinga that investors often overlook the less glamorous foundation of the technology. He identified manufacturing competency and resources as Tesla's greatest long-term strength.

Manufacturing Scale as Moat

The broader narrative surrounding humanoid robotics frequently prioritizes breakthroughs in AI. Kang's thesis contrasts with this view, positioning manufacturing as the enabler for scale.

He stated that this foundation allows Tesla to build robots at a volume few competitors can match once production ramps up. This perspective suggests that leadership in the sector may depend heavily on execution during the transition from prototypes to mass production.

Data Feedback Loops

Kang noted that there have not been many public releases of long-horizon autonomous capability from Optimus yet. However, he argued that manufacturing scale creates a valuable feedback loop for improving future AI models.

He explained that large amounts of robot data serve as a key input to AI models. Tesla will have an advantage in procuring this data given its production scale.

This view links manufacturing and AI closely. Building more robots generates real-world operational data, which trains increasingly capable robot foundation models. Rather than treating these as separate strengths, Kang suggests one reinforces the other.

Investment Takeaway

Kang's perspective reframes how investors may evaluate Tesla's robotics strategy. While the industry focuses on AI demonstrations, he argues the more durable advantage comes from manufacturing scale and continuous improvement through real-world data.

As Optimus moves closer to commercial production, investors will watch whether this combination translates into a lasting lead in humanoid robotics.

How might Tesla's manufacturing scale impact the pricing strategy and market penetration of Optimus compared to specialized robotics competitors?

What specific regulatory or safety hurdles could delay the deployment of large-scale humanoid robot fleets in commercial environments?

Could the data feedback loop advantage be replicated by competitors with access to diverse industrial automation datasets, or is Tesla's vertical integration unique?

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