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Tesla Delivers A Strong Second Quarter, But The Market Is Looking Beyond The Headlines

Tesla delivered stronger-than-expected second-quarter vehicle shipments, comfortably beating Wall Street forecasts as the electric vehicle maker looks to regain momentum after a prolonged sales slowdown.

Deliveries Top Expectations

Tesla reported 480,126 vehicle deliveries and 451,758 vehicles produced during the second quarter. Analysts had expected about 406,600 deliveries, according to StreetAccount, while Tesla’s own consensus estimate stood at 406,024.

Deliveries increased 25% from a year earlier, when Tesla shipped about 384,000 vehicles, and 34% from the first quarter of 2026, when deliveries totaled 358,023.

Despite the stronger results, Tesla shares fell about 6% on Thursday, highlighting investors’ continued focus on the company’s longer-term growth prospects rather than a single quarter of improved deliveries.

Model 3 And Model Y Remain The Core Business

Tesla said its Model 3 sedan and Model Y SUV accounted for 467,762 deliveries, or about 97% of the total, underlining the continued importance of its two highest-volume models even as the company expands into autonomous driving, robotics and energy storage.

Although deliveries are widely viewed as the closest proxy for sales, Tesla does not report regional performance or model-specific sales figures in the same detail as traditional automakers.

Competition Remains Intense

The stronger quarter comes as Tesla works to reverse consecutive annual declines in vehicle sales. The company has faced growing competition from Chinese manufacturers including BYD, Nio and Xiaomi, while also competing with Hyundai Motor Group and European automakers such as Volkswagen Group.

Demand has also been affected by the removal of a U.S. federal EV tax credit and by backlash against CEO Elon Musk’s increasingly polarising political profile.

To support sales, Tesla has introduced lower-priced versions of the Model 3 and Model Y while expanding availability of its Full Self-Driving (Supervised) system in selected European markets. Those initiatives reflect the company’s broader strategy of protecting its leadership in electric vehicles while preparing for a future centred on autonomy, robotics and software.

Energy Business Continues To Grow

Higher gasoline prices during the conflict involving Iran also encouraged some European consumers to consider electric vehicles, providing a temporary boost to EV demand before oil prices eased.

Tesla’s Energy division also continued to expand. The company deployed 13.5 gigawatt-hours of energy storage and solar products during the quarter, up from 9.6 gigawatt-hours a year earlier and slightly above analysts’ expectations of 13.3 gigawatt-hours.

Focus Shifts To Earnings

Looking beyond vehicle sales, Musk continues to position Tesla around products including the Cybercab, Tesla Semi and Optimus humanoid robot. The company has previously said it expects volume production of both the Cybercab and Semi to begin this year, while factory capacity previously used for the Model S and Model X is being repurposed for Optimus production.

Investors will get a clearer picture when Tesla reports second-quarter earnings on July 22. Alongside margins and profitability, markets will be looking for greater clarity on what drove the stronger delivery numbers and whether the momentum can be sustained in an increasingly competitive global EV market.

Mirendil Signs $100 Million Google Cloud Deal To Advance Self-Improving AI

AI startup Mirendil has signed a multi-year agreement worth more than $100 million with Google Cloud to secure computing infrastructure for its self-improving AI research.

The partnership reflects growing competition among AI companies to lock in access to high-performance computing, while cloud providers race to attract promising startups developing next-generation AI models.

Backing The Next Stage Of AI Research

Mirendil plans to use Google’s Tensor Processing Units (TPUs), Nvidia GPUs and managed training infrastructure to develop AI systems capable of improving their own performance over time.

Known as recursive self-improvement, the concept focuses on building AI that can refine its knowledge and capabilities with minimal human intervention. The technology is attracting growing interest across the industry, with several startups and leading AI labs exploring similar approaches.

According to co-founder and Chief Executive Behnam Neyshabur, the long-term goal is to develop AI that can automate scientific research and accelerate discoveries in fields such as medicine, biology and materials science.

Compute Capacity Becomes A Strategic Asset

Training increasingly advanced AI models requires enormous computing resources, making long-term infrastructure agreements a critical competitive advantage.

Mirendil said Google’s combination of TPUs and GPUs allows workloads to be matched with the most suitable hardware, improving efficiency while reducing costs for customers.

For Google Cloud, the agreement strengthens its position in the race to provide infrastructure for frontier AI developers, while giving the company exposure to one of the industry’s emerging approaches to next-generation artificial intelligence.

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