Akamai Launches AI Inference Service and Agent Execution Environment

Multiyear cloud contracts worth more than $14 billion underpin Akamai’s addition of managed AI services.

Rhea-AI Summary

Akamai (Nasdaq: AKAM) introduced Akamai Inference and Akamai Agent Sandbox to add managed AI model serving and isolated agent execution to Akamai Cloud. Both products are available in beta, with serverless deployment options included in the Inference beta. The underlying cloud infrastructure has already secured multiyear contracts collectively worth more than $14 billion.

Akamai also expanded its dedicated GPU fleet with NVIDIA Blackwell Ultra clusters and is preparing its data centers to support NVIDIA Vera Rubin in 2027. Inference offers managed access to open-weight and custom models, while Agent Sandbox separates agent-generated code from the agent’s runtime.

3 points · 1 major

PositiveiHow this balance works

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Rhea-AI Sentiment measures something else, the tone of the wording.

How the balance worksHow Sentiment works

0 major · 1 point

Hollow bars mark forward-looking points. How the balance works

Positive

• Major pointAkamai Cloud infrastructure has secured multiyear contracts collectively worth more than $14 billion. 99% of market cap
• Minor pointDedicated GPU fleet expansion adds NVIDIA Blackwell Ultra GPU clusters.
• Minor point. Forward-looking: it has not happened yet and may not happen.Data center preparations target support for NVIDIA Vera Rubin in 2027.

Negative

• Minor pointAkamai Inference and Akamai Agent Sandbox remain in beta.

Key Figures

Existing multiyear cloud contracts: More than $14 billion Edge locations: More than 4,350 locations Open-weight model catalog: 12 models +4 more

Existing multiyear cloud contracts

More than $14 billion

Akamai Cloud contracts cited alongside the new services

Edge locations

More than 4,350 locations

Akamai Cloud infrastructure

Open-weight model catalog

12 models

Available at launch

Model parameter range

8 billion–2.8 trillion parameters

Models in the launch catalog

GPUs per node

8 GPUs

Blackwell Ultra node

HBM3e memory per GPU

288 GB

Blackwell Ultra node

Total node memory

2.3 TB

Blackwell Ultra node

Previous AI Reports

1 past event · Latest: Oct 15

Same Type 1 event

1. Oct 15

   AI cloud adoption

   24h Move

   +0.7%

   Customer commitments included Blackwell GPU pilots and AI workload deployments across enterprise customers.

24h Move is the share-price change in the day after each event; other market factors may also have contributed.

Key Terms

open-weight models, retrieval-augmented generation, webassembly, hbm3e memory

4 terms

open-weight models technical

"catalog includes 12 open-weight models"

Open-weight models are machine-learning systems whose internal parameters (the numeric “weights” that determine how inputs are turned into outputs) are publicly available for inspection, modification, and reuse. For investors, that transparency makes it easier to audit performance claims, assess risks and biases, and accelerate product development—think of it as a recipe where every ingredient and measurement is shown, so anyone can test, tweak, or reproduce the result.

retrieval-augmented generation technical

"embedding models for retrieval-augmented generation"

An AI method that combines a conversational language system with live access to external documents or databases, so the AI first fetches relevant facts and then uses them to form its answer. Think of it as an assistant that checks a file cabinet for source papers before replying, which helps reduce mistakes and reveal evidence. For investors it matters because it can produce more accurate, verifiable summaries of filings, news and research, speeding due diligence while still depending on the quality of the underlying data.

webassembly technical

"uses WebAssembly isolation to set clear limits"

WebAssembly is a compact, fast code format that lets software run inside web browsers and other platforms almost as quickly as native apps on your computer. Think of it as a universal engine that lets developers bring heavy-duty programs—like games, design tools or data analysis—into the browser without rewriting them, which can speed product delivery, broaden customer reach and affect a company’s technology costs, performance, and competitive edge.

hbm3e memory technical

"carries 288 GB of HBM3e memory per GPU"

HBM3E is a generation of High Bandwidth Memory, a type of volatile, 3D-stacked DRAM that delivers very high data transfer rates by stacking memory dies and connecting them with through-silicon vias (TSVs) and an on-package interposer or substrate. It provides much greater bandwidth and a smaller board footprint than conventional DIMM memory by placing many narrow, fast channels close to a processor, but it requires specialized packaging, controllers and cooling and is not interchangeable with standard off‑the‑shelf memory modules.

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Akamai Inference and Akamai Agent Sandbox extend Akamai Cloud’s ability to serve, run, and secure AI applications and agents from core to edge

CAMBRIDGE, Mass., Oct. 27, 2026 (GLOBE NEWSWIRE) -- Bringing managed model serving and isolated execution for AI agents to Akamai Cloud, Akamai (Nasdaq: AKAM) today introduced two foundational products for its AI stack: Akamai Inference and Akamai Agent Sandbox. With these additions, enterprises can build and tune their own or hosted open-weight models, ground them in their own data, run agents inside enforced boundaries, and secure the applications, agents, and infrastructure involved, all on one cloud platform with AI-optimized infrastructure.

These capabilities mark the latest step in Akamai’s AI strategy: giving enterprises the trusted global infrastructure and services required to serve, run, and secure AI applications and agents, close to the users and data they depend on. Akamai Inference and Akamai Agent Sandbox now add managed services on top of that infrastructure — a foundation that has already secured multiyear contracts for Akamai Cloud collectively worth more than $14 billion. The momentum highlights how Akamai’s ability to leverage both CPUs and GPUs — together with cloud storage, networking, and edge functions on its interconnected global network fabric — is quickly becoming the trusted foundation for customers to build, deploy, and operate AI workloads at scale.

Enterprises moving AI into production need far more than models. They need serving infrastructure, access to their data, routing and governance, and, as agents begin to write and execute their own code, a hard boundary around what that code can reach. Most teams assemble those pieces from separate providers and secure the interaction points themselves. Akamai Cloud now delivers a connected AI environment, placed across a continuum of compute that runs from dense GPU and CPU clusters in core regions to more than 4,350 edge locations, and protected by the same security portfolio that defends many of the world’s largest online businesses.

“We have been implementing an AI infrastructure strategy based on the notion that AI inference will represent the majority of enterprise focus and investment. Our customers proved that thesis and pulled us further,” said Adam Karon, Chief Operating Officer and GM of Akamai Cloud. “They want to build, run, and protect AI on the same platform. Akamai Inference and Akamai Agent Sandbox add the inference and execution layers that turn our AI infrastructure into a full AI stack, and our security portfolio protects every layer of it. Akamai is uniquely positioned to bring our scale and distribution to address scaling real-time inference and agentic workloads.”

Access models without operating the stack: Akamai Inference

Akamai Inference gives enterprises managed access to open-weight and custom models through OpenAI-compatible APIs, so existing applications move without rewrites. Customers choose serverless, pay-per-use inference or dedicated deployments. At launch, the catalog includes 12 open-weight models ranging from 8 billion to 2.8 trillion parameters, including NVIDIA^™ Nemotron 3 Ultra, OpenAI^™ gpt-oss-120b, and Google^™ Gemma 4, along with embedding models for retrieval-augmented generation.

Akamai Cloud provides access to managed databases and object storage, and seamlessly connects to private and public cloud platforms, so models can draw on enterprise data. Akamai Inference then handles the orchestration, model execution, and authentication. Requests run on the Akamai global network, which reduces latency, and helps to ensure high availability and consistent performance while maintaining predictable service levels. 

Give agents a place to execute: Akamai Agent Sandbox

AI agents are increasingly doing real work, from taking actions on a user’s behalf to writing and running their own code. Akamai Agent Sandbox gives developers a secure place to run both. Agents run on Akamai Functions, and the code they write runs in its own isolated environment, sequestered from the agent’s runtime. Delivered as an open source component of the Spin framework, Akamai Agent Sandbox uses WebAssembly isolation to set clear limits on compute, memory outbound connections, and system capabilities. Developers can deploy agents with confidence about where they run and what they can reach.

Agent isolation is converging on several models, from microVMs with snapshot and fork capability, to policy-enforced containers, to WebAssembly-isolated functions. Akamai allows developers to choose the architecture that fits their workload, with NVIDIA-accelerated and dedicated CPU infrastructure, managed Kubernetes, and Akamai Functions for serverless execution across edge and core. Akamai also plans to add capabilities that govern what agents can reach and what can reach them.

Build and tune on a broader GPU fleet: NVIDIA Blackwell Ultra today, Vera Rubin next

Akamai also expanded its dedicated GPU fleet to include NVIDIA Blackwell Ultra GPU clusters and is preparing its infrastructure to support the NVIDIA Vera Rubin platform next year. Akamai’s GPU fleet now spans NVIDIA RTX PRO^™ 6000 Blackwell Server Edition^® GPUs for low-latency inference and NVIDIA Blackwell Ultra GPU clusters for enterprises that want to build, tune, and self-host models on infrastructure they control. Akamai is also preparing its data centers to support the NVIDIA Vera Rubin platform in 2027.

Each eight-GPU Blackwell Ultra node carries 288 GB of HBM3e memory per GPU, 2.3 TB in total, enough to hold frontier-class models. The Blackwell Ultra architecture targets the workloads driving that memory demand: test-time scaling, chain-of-thought reasoning, and long-context agentic work. GPU clusters give enterprises control over model versions and deprecation timelines, and run without rate limits or shared-tenancy queueing. They connect to the same data, networking, and security services as the rest of Akamai Cloud.

“Enterprises should not have to choose between speed and control when they put AI into production,” said Jon Alexander, Senior Vice President of Cloud Technology at Akamai. “Some teams want to ship an AI feature this quarter on a managed platform. Others need dedicated GPUs to run frontier-class open models on their own terms. Every team running agents needs a boundary around the code those agents write. Akamai Cloud now supports all of them on one platform, with security and resilience built in.”

Availability
Akamai Agent Sandbox (via Spin SDK) and Akamai Inference are available in beta. Akamai Inference beta includes serverless deployment options. Contact Akamai Sales for NVIDIA B300 GPU clusters availability.

About Akamai

Akamai is the cloud company that powers and protects an AI-driven world. Our cloud platform extends high-performance cloud computing from the core to the edge, enabling organizations to build and scale next-generation AI applications and providing comprehensive, multilayered security to safeguard enterprises against evolving cyberthreats. Learn more at akamai.com and akamai.com/blog, or follow Akamai Technologies on X and LinkedIn.

Akamai Statement Under the Private Securities Litigation Reform Act

This press release contains statements that are not statements of historical fact and constitute forward-looking statements for purposes of the safe harbor provisions under The Private Securities Litigation Reform Act of 1995, including, but not limited to, statements about Akamai Inference Cloud, its anticipated capabilities, scalability, performance, global deployment plans and the expected benefits to Akamai, current and prospective customers and end users. Each of the forward-looking statements is subject to change as a result of various important factors, many of which are beyond Akamai’s control, including, but not limited to: Akamai's inability to achieve the expected performance or benefits of Akamai Inference Cloud; Akamai’s capabilities failing to meet expectations, including due to defects, security breaches, delays in performance, challenges in leveraging NVIDIA's technologies, or other similar problems; effects of competition, including pricing pressure and changing business models; changes in customer or user preferences or demands; macroeconomic trends and uncertainties, including industry volatility, the effects of inflation, fluctuating interest and foreign currency exchange rates, supply chain and logistics costs, constraints, changes or disruptions; defects or disruptions in Akamai’s or NVIDIA's products or IT systems, including cyber-attacks, data breaches or malware; changes to economic, political and regulatory conditions in the United States or internationally; and other factors that are discussed in Akamai’s most recent annual report on Form 10-K, subsequent quarterly reports on Form 10-Q and other documents filed with the Securities and Exchange Commission. The forward-looking statements contained herein are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, Akamai disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.

Contacts
Akamai Media Relations
akamaipr@akamai.com

Akamai Investor Relations
invrel@akamai.com

FAQ

AI-generated questions and answers. How Rhea-AI works. Not financial advice.

What are Akamai Inference and Akamai Agent Sandbox?

Akamai Inference provides managed access to AI models, while Akamai Agent Sandbox provides isolated execution for AI agents and their generated code. Both are available in beta on Akamai Cloud.

Which models does Akamai Inference support at launch?

The launch catalog includes 12 open-weight models ranging from 8 billion to 2.8 trillion parameters. These include NVIDIA Nemotron 3 Ultra, OpenAI gpt-oss-120b, and Google Gemma 4, alongside embedding models used to connect model responses with retrieved data.

How does Akamai Agent Sandbox limit agent-generated code?

Akamai Agent Sandbox uses WebAssembly isolation to limit compute, memory, outbound connections, and system capabilities. Agents run on Akamai Functions, while their generated code runs in a separate environment. The sandbox is available through the Spin SDK as an open source component of the Spin framework.