Snowflake signs 200 million dollars OpenAI deal as enterprises go multi-model

Snowflake just added another major frontier-model supplier to its enterprise stack, signing a 200 million dollars multi-year partnership with OpenAI that expands how customers can deploy generative AI on governed data.

OpenAI models land inside Snowflake’s governed data layer

Snowflake says the deal makes OpenAI models available to its 12,600 customers across all three major cloud providers, reducing friction for teams that want to run the same app patterns across AWS, Azure, and Google Cloud without re-architecting.

For B2B marketers and e-commerce operators, the practical angle is speed-to-production: connecting customer, product, and campaign data already in Snowflake to LLM-powered use cases such as support automation, audience segmentation, and content QA—while keeping permissions and compliance controls in place.

Snowflake employees are also getting access to ChatGPT Enterprise, a signal that internal productivity (sales enablement, analytics assistance, drafting) is part of the ROI story, not just customer-facing product features.

The companies also plan to co-build AI agents—software that can take actions across tools, not just generate text—often powered by techniques like RAG (retrieval-augmented generation, which grounds responses in a company’s own data).

Model-agnostic enterprise buying is becoming the default

This isn’t Snowflake’s first big model partnership. In early December, it announced a separate 200 million dollars enterprise agreement with Anthropic, highlighting how enterprises are increasingly paying for “choice” rather than betting on a single vendor.

Snowflake AI VP Baris Gultekin described the strategy as intentionally model-agnostic, positioning OpenAI as one of several providers available alongside Anthropic, Google, and Meta.

Broader market signals point the same way. ServiceNow recently signed multi-year deals with both OpenAI and Anthropic, and competing investor surveys disagree on who leads enterprise adoption—Menlo Ventures’ late-2025 survey favored Anthropic, while an Andreessen Horowitz report pointed to OpenAI.

Enterprises appear to be optimizing for task fit (quality, latency, cost, governance) rather than loyalty. For buyers, expect procurement and platform teams to standardize around multi-model routing, evaluation, and compliance—because the “best” model is increasingly workload-specific.

Conclusion: Snowflake’s OpenAI commitment underscores a near-term reality for enterprise AI: multi-model stacks are becoming normal, and data platforms want to be the control plane where those models meet governed business data.