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# NVIDIA BlueField-4 Powers New Scale-In Network Infrastructure for Agentic AI Factories

**[NVIDIA Developer](https://daily.dev/sources/nvidiadev)** · 11 min read · 0 upvotes · 0 comments

## Summary

NVIDIA introduces Scale-In network infrastructure, described as the fifth pillar of NVIDIA AI networking, powered by the new BlueField-4 DPU, NVIDIA DOCA software, and Spectrum-X Ethernet. Scale-In moves security, storage access, tenant isolation, and infrastructure operations off host CPUs onto dedicated, host-independent processing to prevent bottlenecks as agentic AI factories scale. BlueField-4 offers a 64-core Grace CPU, 800 Gb/s network interface, PCIe Gen6, and inline acceleration engines, delivering 4x memory bandwidth and 2x network bandwidth over BlueField-3. It underpins use cases including isolated AI factory VPCs, hardware-enforced security, accelerated storage access (NVMe-oF, RDMA/TCP), Kubernetes-native control-plane provisioning via DOCA Platform Framework, and fleet-wide telemetry, and is co-designed with the upcoming NVIDIA Vera Rubin NVL72 platform.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://developer.nvidia.com/blog/nvidia-bluefield-4-powers-new-scale-in-network-infrastructure-for-agentic-ai-factories>

## Questions this post answers

### What is NVIDIA Scale-In network infrastructure and how does it relate to BlueField-4?

Scale-In is NVIDIA's fifth pillar of AI networking, powered by the BlueField-4 DPU, NVIDIA DOCA software, and Spectrum-X Ethernet. It evolves north-south networks into a coordinated, accelerated infrastructure domain that offloads security, data movement, tenant isolation, and operations from host CPUs, keeping these functions from becoming bottlenecks as AI compute scales in agentic AI factories.

_daily.dev helps infrastructure engineers track new networking architectures like Scale-In as AI data centers scale._

### How does BlueField-4 compare to BlueField-3 in terms of bandwidth?

BlueField-4 provides 4x more memory bandwidth and 2x more network bandwidth compared to BlueField-3, supporting an 800 Gb/s network interface and PCIe Gen6 host connection. It also features a 64-core NVIDIA Grace CPU offering 6x more compute than its predecessor, enabling more concurrent infrastructure services, larger telemetry datasets, and higher security throughput.

_Engineers evaluating DPU upgrades can follow bandwidth and architecture changes like this on daily.dev._

### What are the five pillars of NVIDIA AI networking for AI factories?

The five pillars are Scale-Up (NVLink uniting GPUs), Scale-Out (Spectrum-X Ethernet and Quantum InfiniBand connecting servers), Scale-Across (Spectrum-XGS Ethernet connecting distributed data centers), Context Memory (NVIDIA CMX for shared KV-cache storage), and Scale-In (BlueField-4, DOCA, and Spectrum-X Ethernet accelerating access, security, and operations around AI compute).

_daily.dev keeps architects up to date as vendors define new scaling pillars for AI factory design._

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---

Tags: [#networking](https://daily.dev/tags/networking), [#nvidia](https://daily.dev/tags/nvidia), [#ai-infrastructure](https://daily.dev/tags/ai-infrastructure)

[View this post on daily.dev](https://daily.dev/posts/nvidia-bluefield-4-powers-new-scale-in-network-infrastructure-for-agentic-ai-factories-zvsuy0rob)

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