Tesla and Intel Chip Collaboration: 10% the Cost of NVIDIA

The prospect of a Tesla-Intel chip partnership has sent ripples through the tech world, raising the possibility of AI chips at potentially just 10% of Nvidia’s cost. This bold claim signals a potentially seismic shift in AI infrastructure, one that enterprise technology leaders can’t afford to ignore.

Speaking at Tesla’s annual shareholder meeting on November 6, 2025, CEO Elon Musk publicly floated the idea of collaborating with Intel to produce the electric vehicle manufacturer’s fifth-generation AI chips. This signals a potentially major strategic shift in how AI computing hardware could be manufactured and distributed, and a possible end to the supply chain dominance of TSMC and Samsung.

“You know, maybe we’ll do something with Intel,” Musk told shareholders. “We haven’t signed any deal, but it’s probably worth having discussions with Intel.” The mere suggestion sent Intel shares up 4% in after-hours trading, highlighting the market’s perception of the potential impact of this collaboration. Trading experts note that this spike indicates significant investor confidence in Intel’s ability to capitalize on this potential partnership and re-establish itself as a major player in the AI chip landscape.

The Strategic Imperative

Tesla’s interest in Intel as a manufacturing partner arises at a crucial moment for both companies. Tesla is deep into the design of its AI5 chip, which is intended to power its ambitious autonomous driving systems. Current projections suggest that their “full self-driving” roll out remains dependent on significant compute resource.

Currently utilizing its fourth-generation chip, Tesla has identified a significant constraint in its supply chain. Existing partnerships with Taiwan’s TSMC and South Korea’s Samsung, while valuable, are insufficient to meet Tesla’s increasingly demanding needs. Market analysts suggest that Tesla’s aggressive expansion plans, particularly in autonomous driving and robotics, are placing unprecedented demands on their chip supply.

“Even when we extrapolate the best-case scenario for chip production from our suppliers, it’s still not enough,” Musk stated during the shareholder meeting. This supply crunch has led Tesla to consider building what Musk dubs a “terafab” – a massive chip fabrication facility potentially capable of producing at least 100,000 wafer starts per month. Industry experts suggest the actual figure, given Tesla’s ambitions, could climb even higher.

For Intel, a potential partnership with Tesla represents a vital opportunity. The US chipmaker has significantly lagged behind Nvidia in the AI chip race and urgently needs external customers for its cutting-edge manufacturing technology. Securing Tesla, a high-volume client with substantial innovation capability, could be a game-changer, allowing Intel to demonstrate its capabilities and reclaim market share.

The US government also has a vested interest. Their recent investment in Intel underscores the strategic importance of maintaining domestic chip manufacturing capabilities. This move aligns with a broader national security strategy to reduce reliance on foreign chip suppliers and bolster domestic technological capabilities in critical sectors.

Cost, Performance, and the Enterprise Impact

The technical specifications outlined by Musk, particularly the claim of achieving 10% of Nvidia’s manufacturing cost, could fundamentally reshape enterprise AI economics. Musk stated that Tesla’s AI5 chip would consume approximately one-third of the power used by Nvidia’s flagship Blackwell chip and cost just 10% to manufacture. While potentially overstated, these figures hint at the possibility of highly efficient AI development.

“I’m super hardcore on chips right now, as you may be able to tell,” Musk quipped. “I have chips on the brain.”

If these cost and efficiency projections are realized, the economics of AI deployment will undergo a significant transformation. Enterprise leaders investing heavily in AI infrastructure would be wise to closely scrutinize whether these performance goals materialize, as they could dramatically influence future technology purchasing decisions and investments in the industry. According to one AI infrastructure analyst, these performance goals could drive innovation in cost-optimization across several AI related tech sectors.

Musk emphasized that the chip would be inexpensive, power-efficient, and meticulously optimized for Tesla’s specific software requirements. This vertical integration approach underscores Tesla’s strategy of controlling its entire technology stack, from hardware to software, to drive performance and efficiency.

Production Timeline and Scale

Tesla’s projected chip production roadmap offers a clear timeline for enterprise planning. Limited quantities of AI5 units are anticipated to be produced in 2026, with high-volume production potentially achievable in 2027. Musk indicated on social media that the subsequent AI6 iteration will leverage the same fabrication facilities but deliver approximately twice the performance, with volume production anticipated by mid-2028.

The scale of Tesla’s ambitions is significant. The proposed “terafab” would represent a substantial expansion of domestic chip manufacturing capacity, potentially mitigating supply chain vulnerabilities that have plagued the technology industry in recent years. This could trigger investment into materials and manufacturing processes to accelerate the fabrication.

“So I think we may have to do a Tesla terafab. It’s like a giga but way bigger. I can’t see any other way to get to the volume of chips that we’re looking for. So I think we’re probably going to have to build a gigantic chip fab. It’s got to be done,” Musk said.

Implications for Enterprise Decision-Makers

A potential Tesla-Intel partnership prompts several strategic considerations for enterprise leaders:

Supply chain resilience: The move toward domestic chip manufacturing addresses growing concerns about supply chain concentration in Asia. Enterprise leaders managing technology risk should carefully assess how shifts in chip manufacturing geography might affect their supply chains and vendor relationships. Companies should ensure vendors and suppliers are operating in geographies that represent the best strategic positioning and diversify as needed.

Cost structure changes: If Tesla achieves its stated cost targets, the competitive landscape for AI chips could be dramatically altered. Organizations should develop contingency plans for potential price pressure on current suppliers and evaluate the viability of alternative chip architectures. This may mean a re-evaluation of preferred vendors as Tesla and Intel ramp up production.

Technology Focus: The US government’s stake in Intel and support for domestic chip manufacturing reflect broader geopolitical and technologic focuses. Enterprise leaders in regulated industries or those handling sensitive data should assess how these trends might affect their technology sources and evaluate their security processes.

Innovation pace: Tesla’s aggressive timeline for multiple chip generations suggests an accelerating pace of AI hardware innovation. Technology leaders should factor this into refresh cycles and architecture decisions, avoiding premature commitment to current-generation technology. Staying flexible and open to evaluation presents an opportunity.

Wider Industry Dynamics

Musk’s statements are made against the backdrop of intensifying US-China technology competition. Export restrictions have significantly impacted Nvidia’s business in China. How this impacts the future of global manufacturing remains to be seen.

Intel declined to comment on Musk’s remarks, and no formal agreement has been announced. However, the public nature of the statements and the market’s reaction suggest that substantive discussions may soon be underway. Industry insiders suggest that the sheer complexity of the technological development might prove mutually beneficial.

The AI chip landscape is entering a period of intense flux. Organizations should maintain flexibility in their infrastructure strategy and carefully monitor how partnerships like Tesla-Intel might reshape the competitive dynamics of AI hardware manufacturing. Those that adapt will achieve a more sustainable cost structure.

The decisions made today regarding chip manufacturing partnerships could determine which organizations have access to cost-effective, high-performance AI infrastructure in the coming years. Businesses should carefully consider the strategic implications of this evolving landscape to remain competitive and capitalize on the transformative potential of AI.