Microsoft and OpenAI end their exclusive and revenue-sharing deal

Original Article ↗ Hacker News Discussion ↗

Microsoft and OpenAI are restructuring their multibillion‑dollar partnership so that Microsoft will stop sharing revenue from its OpenAI‑powered products and lose exclusivity over hosting OpenAI’s models, while remaining the “primary” cloud provider and major shareholder. OpenAI, in turn, can now sell its models on other clouds like AWS and Google Cloud, though it still owes Microsoft a capped share of its own revenues through 2030 and has committed to buying roughly $250B of Azure compute. Commenters see this as both a competitive opening for other hyperscalers and a sign of mounting tension over control, profitability, and the credibility of OpenAI’s AGI‑driven narrative, which has been defined in strikingly financial rather than technical terms.

Deal structure changes

  • Microsoft will stop sharing revenue from its AI products with OpenAI; commenters infer the old rev-share was mainly compensation for exclusivity.
  • OpenAI will still pay a revenue share to Microsoft until 2030, now capped; exact percentages and cap size are undisclosed.
  • Exclusivity largely ends: Microsoft remains “primary cloud provider” and gets models “first on Azure,” but OpenAI can sell and deploy on other clouds.
  • Microsoft keeps long‑term IP rights and a large equity stake (often cited as ~27%), plus OpenAI has contracted to buy an additional $250B of Azure services over ~a decade.
  • Many details (model pricing, whether Microsoft now “gets models for free,” precise exclusivity windows) are called unclear.

Who benefits? Perspectives

  • One view: this is a very strong deal for Microsoft—no rev‑share out, continued rev‑share in, big equity, and guaranteed Azure spend.
  • Opposing view: OpenAI “had to get out,” was compute‑constrained and frustrated with Azure quality, and needed freedom to work with AWS/GCP and others.
  • Some see it as a mutual damage‑control compromise after rising tensions and possible antitrust posturing on both sides.

Cloud and model ecosystem impact

  • Expected that OpenAI models will soon appear on AWS Bedrock (confirmed by public statements referenced in the thread) and potentially GCP.
  • This could make Google Cloud the only provider that could in theory offer all three major lab families (OpenAI, Anthropic, Gemini), though Google may keep Gemini exclusive.
  • Several argue that hyperscalers are becoming “infrastructure suppliers” to increasingly powerful model companies rather than the other way around.

Financial engineering and economics

  • Commenters highlight a “circular economy”: OpenAI commits massive Azure spend, Microsoft’s stake in OpenAI is enormous on paper, yet OpenAI is still burning large sums on training and infrastructure.
  • Debate over whether inference itself is profit‑making vs. the overall business being heavily loss‑making.
  • Some see the numbers as partly marketing theater designed to signal inevitability and scale.

AGI rhetoric and skepticism

  • Many are turned off by repeated AGI talk in the press materials and prior agreements.
  • The partnership previously used a financial definition of AGI (e.g., AI systems generating ~$100B profit); this is widely mocked as non‑scientific.
  • Long subthreads debate whether current LLMs are already a form of AGI, whether “AGI” is a moving goalpost, and whether the term has become mostly marketing.

Broader AI/LLM sentiment

  • Split between enthusiasm for rapid capability gains and strong skepticism about hype, economic sustainability, and genuine “intelligence.”
  • Several note that, regardless of AGI, open‑source and cheaper models (e.g., DeepSeek, Qwen, Chinese labs) are now “good enough” for many tasks, eroding moat narratives.