Meta and Amazon close billionaire agreement to use AWS chips and challenge NVIDIA domain

Meta has established a strategic partnership with Amazon that can reshape the semiconductor market for artificial intelligence. According to Zamin's report, Mark Zuckerberg's company will use millions of Amazon's proprietary AWS Graviton processors in the development of AI systems. The agreement directs these chips to complex tasks of AI agents, such as real-time inference and coding, with the clear objective of reducing NVIDIA dependence, currently dominant in the sector.

Meta and Amazon Agreement: What does it represent for the AI market?

The movement replaces, in part, the use of NVIDIA GPUs by ARM processors developed by Amazon. While NVIDIA leads the model training market with its H100 and B200 GPUs, the bet on chips like AWS Graviton focuses on the inference stage — a time when the trained model processes data in real time. The Meta, which has one of the largest AI workloads in the world, seeks to diversify suppliers to avoid scalability bottlenecks. The partnership inserts Amazon as a relevant player in the hardware segment for AI, previously dominated almost exclusively by NVIDIA.

Chips AWS Graviton vs NVIDIA: How do you compete in AI?

AWS Graviton processors are based on ARM architecture and were originally designed for efficient cloud computing. However, Amazon adapted them for AI inference loads, especially in tasks that require low latency and high throughput, such as coding assistants and autonomous agents. Although they do not replace GPUs in heavy model training, they offer lower cost and reduced energy consumption for large scale inference. Meta intends to use these chips in millions of instances, which can force NVIDIA to review its price and offer strategy.

Why does the Amazon Meta agreement matter for the future of the AI?

Overdependence on a single chip supplier has always been seen as a risk — both for costs and innovation. With Meta adopting AWS Graviton chips, other large companies can follow the same path, accelerating the decentralization of the market. This also makes room for alternative architectures, such as AMD and Chinese startups, as discussed in the AI arms race that accelerates with new OpenAI, DeepSeek and Anthropic models. In the short term, NVIDIA maintains leadership in training, but inference represents most of the operational cost of AI systems in production.

Frequently Asked Questions about the Amazon Meta Agreement

Does the agreement between Meta and Amazon completely replace the use of NVIDIA chips?

Nope. The agreement focuses on inference and coding tasks with AI agents; model training still strongly depends on NVIDIA GPUs.

What AI tasks will Amazon's AWS Graviton chips perform on Meta?

They will be mainly used for real-time inference on AI agents, including coding assistants and recommendation systems that require quick response.

When will AWS Graviton chips begin to be deployed by Meta?

Zamin's report does not specify exact deadlines, but the agreement involves millions of processors and is already in the implementation phase in Meta's data centers.

> Source: Meta and Amazon deal expected to strike at Nvidia dominance