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# Microsoft and OpenAI update their partnership terms

**[Collections](https://daily.dev/sources/collections)** · 5 min read · 6 upvotes · 0 comments

## Summary

Microsoft and OpenAI have renegotiated their partnership, ending the exclusive arrangement that gave Azure a lock on OpenAI's models. OpenAI can now sell across any cloud provider. AWS immediately launched GPT-5 family models, Codex, and a new Bedrock Managed Agents service on its platform. The restructuring was driven by OpenAI's $50B deal with Amazon, which included $100B in AWS infrastructure commitments over eight years. Microsoft retains a non-exclusive IP license through 2032, roughly 27% equity in OpenAI, and Azure remains the primary cloud partner. OpenAI faces significant financial pressure, burning $25B against $30B in revenue while managing hundreds of billions in infrastructure commitments across AWS, Azure, and Oracle. The broader trend is all three major hyperscalers converging on multi-model marketplaces with agentic integration, competing on infrastructure quality rather than model exclusivity.

## Content

## What happened

Microsoft and OpenAI have renegotiated their partnership, ending the exclusive arrangement that had given Azure a lock on OpenAI's models and APIs. OpenAI can now sell its products across any cloud provider. AWS and Google Cloud are the immediate beneficiaries.

The key terms of the new deal:

- Microsoft retains a non-exclusive license to OpenAI's IP through 2032
- Microsoft stops paying revenue share to OpenAI; OpenAI continues paying Microsoft through 2030, up to a cap
- Microsoft keeps roughly 27% equity in OpenAI's for-profit entity
- Azure remains OpenAI's "primary cloud partner" and gets first access to new products
- The AGI clause — which gave Microsoft interpretive power over when AGI was reached — is gone entirely

Sam Altman confirmed the basics on social media: Microsoft stays the primary cloud partner, but OpenAI can now make its products available across all clouds.

## Why this happened

The restructuring was essentially forced by OpenAI's $50 billion deal with Amazon, announced in February 2026. That deal — part of a $110 billion funding round — included a commitment to spend $100 billion on AWS infrastructure over eight years and an exclusive hosting arrangement for OpenAI's Frontier agent tool. All of that was in direct conflict with Microsoft's prior exclusivity rights.

Rather than litigate it, both sides renegotiated. Microsoft gets out of paying revenue share to OpenAI. OpenAI gets the freedom to operate across clouds. The Amazon deal is unblocked.

## What AWS actually got

Within days of the announcement, AWS launched three new Bedrock integrations:

- **OpenAI GPT-5 family models** available on Bedrock
- **Codex**, OpenAI's coding agent
- **Bedrock Managed Agents**, a new service built around OpenAI's agent harness with built-in identity, permissions, state management, logging, and governance — all running inside a customer's VPC

The Managed Agents product is the more interesting piece. It packages OpenAI's frontier models inside an AWS-native runtime, which is a different approach from Amazon's existing AgentCore primitives. Matt Garman and Sam Altman framed it as the right architecture for enterprises that want agentic workflows but need cloud-grade security and auditability.

But the deeper story is silicon. Both OpenAI (roughly 2 gigawatts of capacity) and Anthropic (roughly 5 gigawatts) have made multi-year commitments to AWS's custom Trainium chip roadmap, spanning Trainium2 through Trainium4. Unlike Azure's Foundry, where Claude inference runs on Anthropic's own infrastructure, Bedrock runs both Claude and OpenAI models on AWS-managed hardware. AWS's custom silicon business already generates over $20 billion annually. Having two of the world's top AI labs committed to that roadmap simultaneously is a structural advantage that's easy to underestimate.

## The internal Amazon angle

Separately, Amazon is rolling out company-wide access to both Claude Code and OpenAI's Codex for its tens of thousands of developers, starting May 12. This followed internal pushback after Amazon had restricted developers to its own Kiro agentic coding tool. Both tools run on AWS and Bedrock.

For context on where enterprise AI coding adoption is heading: Walmart reported AI coding tools saved 4 million developer hours, with over 95% of its engineers already using them. One Amazon staff engineer described the shift as moving engineering focus from writing code line-by-line to reviewing AI outputs and validating system behavior.

## What Microsoft actually kept

Satya Nadella addressed the deal during Q3 FY2026 earnings, framing it as a net positive. His argument: Microsoft gets royalty-free access to OpenAI's frontier models and IP through 2032 without paying for them, OpenAI has committed over $250 billion in cloud services to Microsoft, and Microsoft holds a 27% equity stake. He also noted Microsoft's AI business hit a $37 billion annual revenue run rate, up 123% year over year, with over 10,000 customers using multiple models.

Markets were less convinced. Microsoft shares fell about 3% on the news. Amazon and Alphabet gained slightly.

## The financial picture is messier than the announcements suggest

The Wall Street Journal reported that OpenAI missed multiple revenue and user growth targets in 2026, expects to burn $25 billion in cash against $30 billion in revenue, and now faces hundreds of billions in infrastructure commitments to AWS, Azure, and Oracle simultaneously. Those commitments assume growth OpenAI hasn't yet demonstrated.

Altman has framed OpenAI as an "intelligence factory" and argued that the integration between models and their deployment harness is the key value layer going forward. That may be true. But the gap between the ambition and the current financials is real, and the infrastructure bets are enormous.

## The broader shift

What's actually happening is that all three major hyperscalers are converging on the same architecture: multi-model marketplaces with agentic integration, competing on infrastructure quality and enterprise controls rather than model exclusivity. The era of one lab being tied to one cloud is over. Whether that's good for OpenAI's margins, given its infrastructure commitments, is a different question.

---

Tags: [#cloud](https://daily.dev/tags/cloud), [#microsoft](https://daily.dev/tags/microsoft), [#azure](https://daily.dev/tags/azure), [#openai](https://daily.dev/tags/openai)

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