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Top AI Performance Starts on a Cloud Built for Speed

Accelerate inference, lower costs, and scale AI apps everywhere

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Move AI workloads to the cloud built for speed.

Decentralized compute removes the physical distance between your models and your users, so your apps deliver faster responses.

Explore Akamai Inference Cloud

AI is moving to the edge. Akamai is already there.

Build, deploy, and scale AI applications faster on our open, developer-friendly platform, with predictable pricing and integrated security.

GPUs on a distributed cloud

Powerful NVIDIA Blackwell GPUs on our distributed infrastructure deliver real-time AI performance.

Ultra-fast AI inference

Achieve sub–50-ms latency and 3x better throughput for agents by eliminating the lag of centralized clouds.

Built-in security at scale

Defend against prompt injection and data exfiltration with built-in Zero Trust security and DDoS protection.

Proven results

Deploy on a distributed cloud to reduce latency by up to 60%, while also achieving significant cost savings.

The State of AI Inference: 50% of AI fails at peak load

Discover the data behind the latency wall and how organizations use distributed compute to scale production AI ROI.

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New AI survey: Inference breaks the latency wall
New AI survey: Inference breaks the latency wall

The State of AI Inference: 50% of AI fails at peak load

Discover the data behind the latency wall and how organizations use distributed compute to scale production AI ROI.

Download report

Next steps

Why distributed AI inference

The shifting landscape of AI infrastructure reveals that bottlenecks are no longer found in raw compute, but in inference placement.

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Explore beta test results

Harmonic uses Akamai’s GPUs to deliver real-time 8K video, achieving a 60% reduction in latency and 86% lower costs.

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Get the latest NVIDIA GPUs

Access NVIDIA RTX PRO™ 6000 Blackwell GPUs, optimized for distributed AI inference.

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Frequently Asked Questions (FAQ)

Frequently Asked Questions (FAQ)

Most traditional cloud architecture is centralized, meaning it relies on a few massive data centers located far away from the average user. When an AI app is centralized, every request must travel hundreds or thousands of miles and back again. This long-haul trip creates physical latency. For real-time applications like voice assistants or chatbots, even a 100-ms delay can make the interaction feel disjointed and un-human.  

Actually, it usually lowers them. Centralized clouds often charge heavy egress fees to move data out of their ecosystem. Edge architecture minimizes these costs compared to legacy cloud providers.

Yes. Akamai provides the flexibility to run any model size, from fine-tuning specialized versions to building dedicated custom clusters designed for large-scale workloads.

Security is baked into our distributed fabric. Because inference happens closer to the user, sensitive data often doesn’t need to travel across the public internet to a distant data center. We layer this with AI-native DDoS protection and Zero Trust security to protect both your models and your users.

Centralized clouds aren’t ideal for real-time AI. Innovation is vital to move GPU power close to users, enabling millisecond responses and ensuring that high-performance scaling remains fast, secure, and cost-effective.

Talk to architects and engineers who have done this before.

Let’s Talk

Talk to architects and engineers who have done this before. We’ll help you run your AI in production.

Top AI Performance Starts on a Cloud Built for Speed