Amazon (AMZN) Web Services (AWS) is launching its fourth-generation Graviton processor, the Graviton4 chip, the company shared exclusively with Yahoo Finance.

The new chip promises to deliver substantial improvements in performance and efficiency, including three times the compute power and memory of its predecessor, 75% more memory bandwidth, and 30% better performance, according to Rahul Kulkarni, Amazon’s director of product management for Compute and AI.

“Collectively it's delivering more price performance, which means for every dollar spent, you get a lot more performance,” Kulkarni shared with Yahoo Finance at Amazon’s chips lab in Austin, Texas.

Demand for chips is growing as semiconductors continue to play a vital role in the global economy, powering nearly everything we use. The industry is currently valued at $544 billion and is expected to exceed $1 trillion by 2033, driven by increasing demand for AI.

As a result, hyperscalers such as Amazon, Apple (AAPL), Alphabet (GOOG, GOOGL), and Microsoft (MSFT) are creating custom chips to meet their specific needs, cut costs, and offer customers more affordable options.

"All of these companies are spending a lot of money on developing chips," said Patrick Moorhead, who spent over a decade as a vice president at AMD. "They won't talk about how much they're investing, but they have these giant R&D budgets."

Nvidia (NVDA) remains the dominant player in the AI chips market, with more than 80% share of the market for graphics processing units (GPUs). But there is enough demand to support multiple competitors, according to Moorhead, who currently serves as CEO and chief analyst at Moor Insights & Strategy.

Although the Graviton4 chip is not an AI chip, it supports AWS's Inferentia and Trainium chips, which are focused on the technology. Trainium competes directly with Nvidia's AI chips, which are considered the fastest and most powerful in the market.

However, AWS's goal is not to unseat Nvidia, Kulkarni emphasized. Instead, the cloud service provider hopes to offer a viable alternative for customers focused on price performance, which they hope will allow them to take a profitable slice of the rapidly expanding AI-driven chips market.

"Right now, if a customer is more focused on time to market, Nvidia-based products that we offer are a great option," Kulkarni said. "There are customers for whom cost becomes a very prohibitive aspect of running their business. If they want to do more cost-optimized AI workloads like training or inference, then our Inferentia and Trainium products become a great alternative."