Tesla Inc shares traded higher following third-quarter delivery figures that exceeded analyst expectations. The results signal a potential shift in market dynamics as the company navigates the expiration of federal incentives.

Delivery performance and market context

Tesla reported a 2% year-over-year decline in September deliveries. However, this figure contrasts with a comparable period that included the federal EV tax credit, which expired on September 30, 2025. Adjusting for the tax credit's impact, Deepwater Asset Management Managing Partner Gene Munster estimated that September deliveries would have been up 8% year-over-year.

Munster noted that Tesla's automotive business has returned to growth for two consecutive quarters. He attributed this momentum to rising gas prices in the United States and the company's specific value proposition to buyers.

Competitive landscape and Ford, GM

Traditional automakers face significant headwinds in the electric vehicle segment. Munster highlighted that companies such as Ford Motor Company and General Motors Company saw electric vehicle deliveries drop by approximately 75% in September. He described these competitors as being in a difficult position, forced to choose between pricing vehicles cheaply at a loss or pricing them higher with limited demand.

Growth outlook and full self-driving

Munster projects that Tesla's deliveries will increase by around 15% next year, surpassing the Street's current estimate of 9%. This forecast relies on two sustainable tailwinds: increased demand driven by fuel costs and the adoption of Full Self-Driving (FSD) software.

The analyst emphasized FSD as a critical differentiator against traditional automakers' EVs, which lack equivalent autonomous capabilities. He suggested that word-of-mouth from FSD users could drive further sales. While acknowledging that overall EV demand might soften if gas prices fall, Munster maintained that Tesla retains the most compelling lineup for the dollar, excluding Chinese EV makers. He noted that traditional automakers might need to license FSD technology to remain competitive, a process he expects to unfold over the next decade.

Tesla Inc. CEO Elon Musk affirmed that the automaker's early investment in custom inference computers may prove pivotal as artificial intelligence demand accelerates. Musk agreed with an internal engineer's assessment that current compute shortages represent only the initial phase of a broader constraint.

Engineer cites scaling advantage

In response to Tesla engineer Yun-Ta Tsai on X, Musk stated "Yes" regarding the strategic value of Tesla's proprietary hardware. Tsai argued that the company's years of iterating and scaling its own inference computers for each vehicle sold could be "unprecedented" before the superintelligence era. He noted, "The current compute shortage is only the tip of the iceberg. When autonomy becomes indispensable, the real shortage will follow."

Tesla's approach relies on advanced vision and planning AI supported by efficient inference hardware. The company states its custom chips are optimized for performance per watt and mass deployment in cars, reducing reliance on general-purpose processors.

Chip roadmap and Terafab strategy

Tesla's hardware strategy is advancing through its AI5 and AI6 chip generations. The company reported in January that development of both custom inference chips had progressed, with production planned for 2027 and 2028, respectively. Musk has indicated AI5 will "punch far above its weight," primarily optimizing for edge computing in Robotaxi and Optimus applications.

To address long-term supply constraints, Tesla is pursuing the Terafab project. During the second-quarter earnings call, Musk explained that the facility is necessary because Tesla otherwise "simply won't have enough AI chips" to scale Optimus. The project aims to accelerate iteration across logic, memory, packaging, and chip testing.

Reuters reported in April that Tesla, SpaceX, and xAI are pursuing Terafab partly because Musk expects external suppliers cannot satisfy their long-term chip requirements. The broader industry context involves hundreds of billions of dollars flowing into AI infrastructure as companies secure chips, cloud capacity, and power.

What the numbers show

The disclosed figures highlight a divergence between near-term product timelines and long-term infrastructure needs. While AI5 and AI6 production are scheduled for 2027 and 2028, the $3 billion Austin fab investment signals that Tesla anticipates chip scarcity extending well beyond these dates. This suggests the company views semiconductor supply, rather than software capability alone, as the primary bottleneck for scaling autonomous systems.