Amazon is doubling down on AI: the e-commerce giant late Monday agreed to invest up to $25 billion more in Anthropic, the startup behind the Claude models. The pledge includes $5 billion up front and as much as $20 billion more tied to commercial milestones, adding to Amazon’s prior $8 billion commitment and bringing its total potential stake to $33 billion.
In exchange Anthropic agreed to run its AI workloads on Amazon Web Services, committing to more than $100 billion in AWS spending through 2036. That deal gives Anthropic access to up to 5 gigawatts of compute capacity for training and deploying Claude on Amazon’s custom silicon. Today Anthropic already runs on roughly 1 million AWS Trainium2 chips; Amazon will add more Trainium2 and Trainium3 capacity as it brings an additional 1 GW online by the end of 2026.
“Our custom AI silicon offers high performance at significantly lower cost for customers, which is why it’s in such hot demand,” Amazon CEO Andy Jassy said. “Anthropic’s commitment to run its large language models on AWS Trainium for the next decade reflects the progress we’ve made together on custom silicon, as we continue delivering the technology and infrastructure our customers need to build with generative AI.”
The move follows Amazon’s other recent AI splash — a reported $50 billion contribution to OpenAI’s $110 billion funding round two months ago that valued OpenAI at about $730 billion pre-money — and comes as Amazon plans roughly $200 billion in capital expenditures this year, with the bulk earmarked for AI infrastructure.
A few more facts: Anthropic was founded in 2021 by former OpenAI researchers and executives and has scaled quickly, reporting annualized revenue north of $30 billion. Its Claude models compete directly with OpenAI’s GPT series and Google’s Gemini. On the hardware front, AWS released Trainium3 in December 2025 and is already gearing up Trainium4, which AWS says will deliver about 2 exaflops of FP4 performance.
For crypto audiences, the deal is notable on two fronts: it signals continued centralization of the massive compute resources needed for cutting-edge LLMs—resources that cloud giants control—and it could lower the price and increase availability of high-performance AI services that might be integrated with blockchain, smart contracts, and tokenized AI products.
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