Nvidia unveils new AI chip platform amid rising competition

AI juggernaut Nvidia unveiled its latest AI platform on Monday, as the world’s most valuable company works to maintain its leadership in supplying the chips that power the artificial intelligence revolution.

The California-based company made its announcement at the annual Consumer Electronics Show in Las Vegas, where CEO Jensen Huang’s keynote was an early must-see event at the globe’s biggest tech showcase.

With its new Vera Rubin product, first announced in September, Nvidia is seeking to lock in its dominance of the AI chip business. The company currently holds an estimated 80 percent of the global market for AI data centre chips.

However, Nvidia faces mounting pressure from multiple fronts, with traditional chip-making rivals like AMD and Intel pushing hard to compete.

Meanwhile, Nvidia’s biggest customers – Google, Amazon, and Microsoft – are increasingly developing their own chips to reduce their dependence on the company.

Google’s latest AI model, Gemini 3, was trained without Nvidia’s technology.

China is also racing to build domestic alternatives to Nvidia products, which have faced US export restrictions, hobbling the Chinese tech sector.

Nvidia said Rubin-based products would be available from partners in the second half of 2026.

The company described the new model, named after American astronomer Vera Rubin, as marking a profound shift from its previous generation of AI architecture, Blackwell, which launched in late 2024.

The company promises that the Rubin product will run five times more efficiently than previous offerings, a key performance metric as the energy needs related to AI become an increasing concern.

The platform itself comprises “six chips that make one AI supercomputer,” said Dion Harris, Nvidia’s director of data center and high-performance computing.

These will “meet the needs of the most advanced models and drive down the cost of intelligence,” he added.

Since ChatGPT’s release in 2022, Nvidia has been updating its product line at a furious pace, raising questions about whether tech companies building AI models can afford to keep their technology state-of-the-art.