Tesla CEO Elon Musk has revealed new details about the company’s next-generation AI5 chip, describing it as “an amazing design” that could outperform its predecessor by a factor of 40. Speaking during Tesla’s Q3 2025 earnings call, Musk outlined how the chip will be manufactured in partnership with both Samsung and TSMC, with production based entirely in the United States.

What makes AI5 special

According to Musk, the AI5 represents a complete evolution of Tesla’s in-house AI hardware, building on lessons learned from the AI4 system currently used in its vehicles and data centers. “By some metrics, the AI5 chip will be 40x better than the AI4 chip, not 40%, 40x,” Musk said during the Q3 2025 earnings call. He credited Tesla’s unique vertical integration for the breakthrough, noting that the company designs both the software and hardware stack for its self-driving systems.

To streamline the new chip, Tesla eliminated several traditional components, including the legacy GPU and image signal processor, since the AI5 architecture already incorporates those capabilities. Musk explained that these deletions allow the chip to fit within a half-reticle design, improving efficiency and power management. 

“This is a beautiful chip,” Musk said. “I’ve poured so much life energy into this chip personally, and I’m confident this is going to be a winner.”

Tesla’s dual manufacturing strategy for AI5

Musk confirmed that both Samsung’s Texas facility and TSMC’s Arizona plant will fabricate AI5 chips, with each partner contributing to early production. “It makes sense to have both Samsung and TSMC focus on AI5,” the CEO said, adding that while Samsung has slightly more advanced equipment, both fabs will support Tesla’s U.S.-based production goals.

Tesla’s explicit objective, according to Musk, is to create an oversupply of AI5 chips. The surplus units could be used in Tesla’s vehicles, humanoid robots, or data centers, which already use a mix of AI4 and NVIDIA hardware for training. “We’re not about to replace NVIDIA,” Musk clarified. “But if we have too many AI5 chips, we can always put them in the data center.”

Musk emphasized that Tesla’s focus on designing for a single customer gives it a massive advantage in simplicity and optimization. “NVIDIA… (has to) satisfy a large range of requirements from many customers. Tesla only has to satisfy one customer, Tesla,” he said. This, Musk stressed, allows Tesla to delete unnecessary complexity and deliver what could be the best performance per watt and per dollar in the industry once AI5 production scales.

Tesla’s long-awaited and way underrated Solar Roof may finally be getting its moment. During the company’s Q3 2025 earnings call, Vice President of Energy Engineering Michael Snyder revealed that production of a new residential solar panel has started at Tesla’s Buffalo, New York facility, with shipments to customers beginning in the first quarter of 2026. 

The comments hint at possible renewed life for the Solar Roof program, which has seen years of slow growth since its 2016 unveiling.

Tesla Energy’s strong demand

Responding to an investor question about Tesla’s energy backlog, Snyder said demand for Megapack and Powerwall continues to be “really strong” into next year. He also noted positive customer feedback for the company’s new Megablock product, which is expected to start shipping from Houston in 2026.

“We’re seeing remarkable growth in the demand for AI and data center applications as hyperscalers and utilities have seen the versatility of the Megapack product. It increases reliability and relieves grid constraints,” he said.

Snyder also highlighted a “surge in residential solar demand in the US,” attributing the spike to recent policy changes that incentivize home installations. Tesla expects this trend to continue into 2026, helped by the rollout of a new solar lease product that makes adoption more affordable for homeowners.

Possible Solar Roof revival?

Perhaps the most intriguing part of Snyder’s remarks, however, was Tesla’s move to begin production of its “residential solar panel” in Buffalo, New York. He described the new panels as having “industry-leading aesthetics” and shape performance, language Tesla has used to market its Solar Roof tiles in the past.

“We also began production of our Tesla residential solar panel in our Buffalo factory, and we will be shipping that to customers starting Q1. The panel has industry-leading aesthetics and shape performance and demonstrates our continued commitment to US manufacturing,” Snyder said during the Q3 2025 earnings call.

Snyder did not explicitly name the product, though his reference to aesthetics has fueled speculation that Tesla may finally be preparing a large-scale and serious rollout of its Solar Roof line.

Originally unveiled in 2016, the Solar Roof was intended to transform rooftops into clean energy generators without compromising on design. However, despite early enthusiasm, production and installation volumes have remained limited for years. In 2023, a report from Wood Mackenzie claimed that there were only 3,000 operational Solar Roof installations across the United States at the time, far below forecasts. In response, the official Tesla Energy account on X stated that the report was “incorrect by a large margin.”

Tesla’s VP of AI/Autopilot software, Ashok Elluswamy, has offered a rare inside look at how the company’s AI system learns to drive. After speaking at the International Conference on Computer Vision, Elluswamy shared details of Tesla’s “end-to-end” neural network in a post on social media platform X.

How Tesla’s end-to-end system differs from competitors

As per Elluswamy’s post, most other autonomous driving companies rely on modular, sensor-heavy systems that separate perception, planning, and control. In contrast, Tesla’s approach, the VP stated, links all of these together into one continuously trained neural network. “The gradients flow all the way from controls to sensor inputs, thus optimizing the entire network holistically,” he explained.

He noted that the benefit of this architecture is scalability and alignment with human-like reasoning. Using examples from real-world driving, he said Tesla’s AI can learn subtle value judgments, such as deciding whether to drive around a puddle or briefly enter an empty oncoming lane. “Self-driving cars are constantly subject to mini-trolley problems,” Elluswamy wrote. “By training on human data, the robots learn values that are aligned with what humans value.”

This system, Elluswamy stressed, allows the AI to interpret nuanced intent, such as whether animals on the road intend to cross or stay put. These nuances are quite difficult to code manually.

Tackling scale, interpretability, and simulation

Elluswamy acknowledged that the challenges are immense. Tesla’s AI processes billions of “input tokens” from multiple cameras, navigation maps, and kinematic data. To handle that scale, the company’s global fleet provides what he called a “Niagara Falls of data,” generating the equivalent of 500 years of driving every day. Sophisticated data pipelines then curate the most valuable training samples.

Tesla built tools to make its network interpretable and testable. The company’s Generative Gaussian Splatting method can reconstruct 3D scenes in milliseconds and model dynamic objects without complex setup. Apart from this, Tesla’s neural world simulator allows engineers to safely test new driving models in realistic virtual environments, generating high-resolution, causal responses in real time.

Elluswamy concluded that this same architecture will eventually extend to Optimus, Tesla’s humanoid robot. “The work done here will tremendously benefit all of humanity,” he said, calling Tesla “the best place to work on AI on the planet currently.”