The artificial intelligence boom runs on specialized chips, and for a giant like Amazon, the question of where to get them is a multi-billion-dollar dilemma. Should it build its own, or buy from the experts? The answer shapes its entire strategy.
The Case for 'Buy': Partnering With the King
In the
world of AI chips, Nvidia is the undisputed king. Its powerful GPUs (Graphics Processing Units) have become the industry standard for training and running the most demanding AI models. For Amazon Web Services (AWS), the company's cloud computing juggernaut, buying from Nvidia offers a clear advantage: immediate access to best-in-class, off-the-shelf technology that developers already know and love. This is the fastest way to meet crushing demand. In fact, AWS plans to deploy millions of new Nvidia GPUs in the coming years. This 'buy' strategy ensures that AWS customers who want the raw power of Nvidia's latest hardware have it, keeping AWS competitive with rivals like Microsoft Azure and Google Cloud. Relying on an external supplier is a straightforward path to providing top-tier performance without the immense R&D and manufacturing headaches of creating cutting-edge silicon from scratch.
The Allure of 'Build': Forging Its Own Path
While buying is fast, building offers control. Since acquiring chip designer Annapurna Labs in 2015, Amazon has been developing its own custom silicon. Its main AI-focused chips are 'Trainium' for training models and 'Inferentia' for running them (a process called inference). The primary motivation, according to CEO Andy Jassy, is cost. Jassy has stated that AI inference is still far too expensive for widespread business use, and custom chips are a key part of the solution. By designing hardware specifically for the workloads running on AWS, Amazon can achieve 30-40% better price-performance, a massive advantage at cloud scale. Building also provides a crucial hedge against supply chain disruptions and reliance on a single dominant supplier, which is a lesson the tech industry has learned the hard way.
The Real Answer: A Hybrid 'And' Strategy
Ultimately, the 'build or buy' framing presents a false choice. Amazon's real strategy isn't 'or'—it's 'and.' AWS is aggressively pursuing a hybrid model where its own custom chips coexist with those from Nvidia. This gives customers the ultimate flexibility. A startup might prefer the raw power and broad compatibility of Nvidia's GPUs, while a large enterprise looking to optimize costs for a specific, high-volume task might choose Amazon's more cost-effective Trainium or Inferentia chips. This dual approach allows Amazon to cater to the entire market. However, it's not without challenges. Some customers have reported friction when trying to adopt Amazon's custom chips, which can require more software work to use effectively compared to the well-established Nvidia ecosystem. But Amazon is working to lower this barrier, recently open-sourcing software to make it easier for developers.
A New Twist: Selling Its Own Chips
The dilemma has recently taken on a new dimension. In late 2026, Amazon announced its intention to begin selling its Trainium chips directly to external customers starting in late 2027. This move would transform a cost saving internal project into a direct revenue stream, putting Amazon in competition not just with other cloud providers, but with chipmakers themselves. This presents a new trade off : selling a chip generates immediate revenue, but keeping it inside AWS allows Amazon to generate recurring revenue over the chip s five to six year lifespan. CEO Andy Jassy acknowledged this complex decision, noting the company will have to balance how it allocates its limited supply of custom made chips. This evolution shows that Amazon s chip strategy is not just about powering its own cloud but potentially about becoming a key player in the broader semiconductor market.
