Cloud and cybersecurity company Akamai has signed a seven-year agreement worth $11.6 billion with Anthropic to provide cloud infrastructure and software for the AI company’s growing CPU workloads.
The agreement could expand by another $9 billion, taking the total potential commitment to about $20 billion over the seven-year term.
Under the deal, Anthropic will use Akamai Cloud’s distributed infrastructure to support CPU workloads. Akamai said the agreement adds to more than $2.8 billion in multi-year Cloud Infrastructure Services commitments across its customer base announced earlier this year.
“Akamai has an unparalleled reputation for helping our customers achieve their business-critical goals and build the future,” said Tom Leighton, Co-founder and CEO of Akamai Technologies. “Our expanding global footprint, combined with our years of experience serving the world’s largest enterprises, positions us to be the infrastructure provider for secure and responsible AI applications and workloads.”
Akamai said the agreement will require about $5.5 billion in capital expenditure. The company expects to spend an additional $1.7 billion in 2026 to secure and pre-purchase supply chain components, including memory.
Akamai does not expect the deal to affect its 2026 revenue guidance.
As part of the agreement, Akamai has issued Anthropic a warrant to purchase non-voting convertible Series B Preferred Stock representing 7.7 million Akamai shares on an as-converted basis.
The warrant could represent about 5% of Akamai’s outstanding common stock. Around 2% is expected to vest in connection with the initial $11.6 billion commitment.
The remaining 3% is tied to the agreement's potential expansion. Each additional $3 billion purchase of cloud services, subject to mutually agreed terms, would result in the vesting of approximately 1% of Akamai’s common stock outstanding.
Akamai said its cloud platform provides compute across core and edge locations through a distributed network spanning thousands of points of presence.
The agreement comes as AI companies expand infrastructure spending beyond GPU computing to support the CPU workloads involved in running and operating AI applications at scale.


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