Jun 19, 2026 · Artificial Intelligence

How NVIDIA Dynamo Boosts Multi‑Node Distributed Inference MFU for Agentic AI

The article explains how NVIDIA Dynamo tackles the production bottlenecks of Agentic AI by using KV‑Cache‑aware routing, a three‑stage multimodal inference architecture, and intelligent cache scheduling on Kubernetes to improve multi‑node throughput (MFU) while maintaining latency SLAs.

Distributed InferenceKV cacheKubernetes

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How NVIDIA Dynamo Boosts Multi‑Node Distributed Inference MFU for Agentic AI

DataFunSummit

Jun 17, 2026 · Artificial Intelligence

Why Agentic AI Inference Is Slow and How NVIDIA Dynamo 1.1 Solves It

Developers deploying Agentic AI face multi‑turn latency caused by repeated token recomputation, KV‑cache eviction, and cold‑starts, and NVIDIA Dynamo 1.1 addresses these issues with KV‑cache‑aware routing, multi‑level cache offload, priority scheduling, and Prefill/Decode separation, as demonstrated in an upcoming Kubernetes‑based live session.

AI inferenceDistributed InferenceKV cache

0 likes · 3 min read

Why Agentic AI Inference Is Slow and How NVIDIA Dynamo 1.1 Solves It