Equinix, NVIDIA and Together AI Form Strategic Alliance for Enterprise AI Inference Platform

2 Sources

Share

Equinix announced Equinix Inference Exchange at its inaugural Horizon event, combining NVIDIA Enterprise Reference Architectures with Together AI's platform across 280+ global data centers. The distributed AI inference platform supports over 200 open-source models and targets Q1 2027 availability, addressing where inference runs as enterprises scale AI workloads.

Equinix Expands NVIDIA Partnership with Together AI to Accelerate AI Inference for Enterprises

Equinix announced a major expansion of its collaboration with NVIDIA and a new partnership with Together AI to deliver Equinix Inference Exchange, a distributed AI inference platform designed for global enterprises

1

2

. The strategic alliance was unveiled at Equinix Horizon, the company's inaugural customer and partner event, alongside Equinix Fabric One, which simplifies connectivity across globally distributed AI environments

1

.

This collaboration addresses a critical challenge as enterprises move AI from experimentation to production deployment: determining where inference runs and how it connects to data, applications and workloads. "AI is transforming enterprise technology at extraordinary speed, and the infrastructure decisions enterprises make today will define their competitive position for years to come," said Adaire Fox-Martin, Chief Executive Officer and President at Equinix

1

.

Strategic Alliance Combines Three Layers for Distributed AI Inference Platform

The Equinix Inference Exchange brings together NVIDIA's validated Enterprise Reference Architectures with Together AI's inference platform, which supports more than 200 open-source models

1

2

. Delivered through Equinix global data center infrastructure spanning over 280 data centers across 77 metros, the solution provides connectivity to clouds, networks and AI providers through Equinix Fabric

1

.

The platform combines three complementary layers: Equinix provides the infrastructure foundation, including power, advanced cooling and day-two operations. NVIDIA anchors the build with its Enterprise Reference Architectures and AI infrastructure purpose-built to maximize AI factory throughput and minimize token cost. Together AI runs the platform on top, supporting both multitenant deployments for shared efficiency and dedicated single-tenant environments for workloads requiring dedicated capacity

2

.

Low-Latency Connectivity and Ecosystem Integration Drive Enterprise Value

Equinix Inference Exchange will give enterprises a faster path from AI experimentation to production, with secure, low-latency connectivity to the data, users and ecosystem they depend on

1

. Built on Equinix Fabric, the solution connects to inference providers across major metros worldwide, cutting time-to-first-token while connecting to an expansive ecosystem of clouds, networks and AI providers to reduce deployment complexity

2

.

Equinix brings significant scale to this challenge, with 230 cloud on-ramps and over 10,500 businesses interconnected on its neutral exchange. Eight of the top 10 AI model providers and nine of the top 10 AI clouds are deployed with Equinix, underscoring the company's position at the center of the AI ecosystem

1

.

Model Choice and Operational Flexibility Address Enterprise AI Workloads

"Together AI was built on the conviction that open, accessible AI is what will define the industry moving forward, because enterprises shouldn't have to choose between model performance and operational flexibility," said Vipul Ved Prakash, co-founder and CEO at Together AI

1

. The Together AI inference platform enables model choice by supporting open-source models, giving enterprises flexibility to scale on their terms.

Raj Mirpuri, vice president of global AI clouds and infrastructure ecosystem at NVIDIA, noted that "Equinix Inference Exchange turns the world's leading digital interconnection platform into a global fabric for AI inference," combining NVIDIA's infrastructure and technology with Together AI's open-model inference platform and Equinix's global reach to bring intelligence closer to data, applications and customers

1

.

Performance, Cost and Governance Considerations for Production Deployment

Nick Patience, Vice President & Practice Lead for AI Platforms at The Futurum Group, emphasized that "performance, cost and governance have become strategic considerations as AI workloads grow more distributed across providers, data sources and environments." Organizations are increasingly focused on where inference runs and how quickly it can be deployed into production

1

.

The solution aims to support a broad range of enterprise inference scenarios, including metro edge inference, open model migration, and sovereign AI

2

. Managing distributed inference deployments introduces significant operational complexity precisely when enterprises need greater control and visibility as the pace of enterprise AI adoption outpaces supporting infrastructure

1

.

Equinix Inference Exchange will be available starting in the first quarter of 2027

2

, giving enterprises time to plan their infrastructure strategies as they determine how to deploy AI infrastructure and where it should run to optimize deployment speed, flexibility and cost efficiency.

Today's Top Stories

© 2026 TheOutpost.AI All rights reserved