Amazon’s in-house processors are growing fast enough to make the company a serious rival to Nvidia, even though Amazon remains one of Nvidia’s biggest customers. The e-commerce and cloud giant said in its latest earnings report that its custom chips business has reached an annual revenue run rate of $25 billion. That figure arrives just as Nvidia prepares to enter a CPU segment where Amazon already has a head start.
The growth is concentrated in two product lines. Amazon said both Graviton, its general-purpose CPU, and Trainium, its AI accelerator, are delivering triple-digit growth. Nvidia, by comparison, reported record quarterly revenue of $96 billion in its most recent period, according to the source report. That shows the scale gap Amazon is still working against.
The bigger question for the AI Chip Market is whether cheaper custom chips will cut into demand for Nvidia’s premium hardware or simply expand the pie. So far, the evidence points toward expansion. But Amazon’s stated interest in possibly spinning its chip work into a stand-alone business suggests its ambitions reach beyond serving its own cloud.
Why Amazon Is Both Partner and Competitor
Amazon Web Services, the world’s largest cloud provider, sells access to Nvidia’s top GPUs and platforms to customers running AI workloads. Amazon CEO Andy Jassy made that commitment explicit on the company’s recent earnings call: “We’ll continue making AWS the best place to run Nvidia chips.”
At the same time, AWS offers its own silicon on the same platform. Customers can choose Nvidia hardware for some jobs and Amazon’s chips for others, often inside the same cloud account. Few companies anywhere in the industry hold that kind of dual position.
The Value Pitch
Amazon is not trying to beat Nvidia on raw performance. It is competing on price. The company says Graviton offers at least 30% better price performance than other CPUs. It markets Trainium as a lower-cost option for training and running AI models. For cost-conscious customers, particularly those moving from experimentation to large-scale deployment, that pitch carries weight.
In his shareholder letter earlier this year, Jassy raised the possibility that Amazon’s chip operation could one day become a stand-alone business. It was a notable signal from a company that has historically built hardware mainly to support its own services.
A Brief Look at Amazon’s Chip Lineup
AWS introduced its first Graviton processor in 2018 and later added Trainium for AI training workloads. Both are designed in-house and available mainly through AWS rather than sold as physical parts to outside buyers. Amazon has also built large Trainium-based computing clusters for AI developers, including Anthropic, which reflects the growing role these chips play in frontier model work.
How the Two Companies Compare
| Area | Nvidia | Amazon |
|---|---|---|
| Core AI product | GPUs and full AI systems | Trainium accelerators |
| CPU position | Launching a stand-alone CPU this fall, per the report | Graviton, already widely used on AWS |
| Main selling point | Highest available performance | Lower cost, strong price performance |
| Latest reported figure | $96 billion quarterly revenue | $25 billion annual run rate for custom chips |
| Relationship | Supplier to AWS | Customer of Nvidia and a rival |
The CPU Battle Ahead
The timing of Nvidia’s CPU push matters. CPUs are the general-purpose chips found in every computer. They are increasingly seen as central to agentic AI, in which software systems carry out multistep tasks on their own. Many in the industry view agentic AI as the next major growth driver.
That puts Nvidia’s upcoming CPU in direct competition with Graviton, which already has an established customer base inside AWS. For once, Nvidia will be the newcomer in a segment where Amazon has years of adoption behind it.
Pressure on Inference Pricing
Amazon has argued that a wider range of chip options should push down the cost of AI inference, the process of running trained models to produce answers. Lower prices would benefit buyers. They could also squeeze a company like Nvidia, whose business depends on premium pricing. Amazon’s value-focused approach is designed to capture customers looking for cheaper alternatives.
Why Nvidia’s Lead Still Looks Secure
Despite Amazon’s momentum, there is little sign so far that its gains are coming at Nvidia’s expense. Two factors explain why.
First, demand for AI computing remains strong enough that no single supplier can meet it. As companies put AI to work in real products, that demand appears likely to hold.
Second, the chips are not direct substitutes. Customers who need maximum performance for certain workloads still turn to Nvidia, while price-sensitive projects may run on Amazon’s hardware. Many large buyers use both.
The likeliest near-term outcome is that both companies keep growing. Amazon may not unseat Nvidia at the top of the market, but its breadth across CPUs and accelerators, combined with direct access to millions of cloud customers, makes it arguably a more consequential challenger than traditional chipmakers such as AMD.
Disclaimer: This content was partially produced with the help of AI tools and This content is for informational purposes only and not investment advice.
