For leading AI labs like Anthropic and OpenAI, the primary value from cloud partnerships isn't a sales channel but guaranteed access to scarce compute and GPUs. This turns negotiations into a complex, symbiotic bundle covering hardware access, cloud credits, and revenue sharing, where hardware is the most critical component.
Related Insights
Firms like OpenAI and Meta claim a compute shortage while also exploring selling compute capacity. This isn't a contradiction but a strategic evolution. They are buying all available supply to secure their own needs and then arbitraging the excess, effectively becoming smaller-scale cloud providers for AI.
Specialized AI cloud providers like CoreWeave face a unique business reality where customer demand is robust and assured for the near future. Their primary business challenge and gating factor is not sales or marketing, but their ability to secure the physical supply of high-demand GPUs and other AI chips to service that demand.
OpenAI's strategy involves getting partners like Oracle and Microsoft to bear the immense balance sheet risk of building data centers and securing chips. OpenAI provides the demand catalyst but avoids the fixed asset downside, positioning itself to capture the majority of the upside while its partners become commodity compute providers.
Top AI labs like Anthropic are simultaneously taking massive investments from direct competitors like Microsoft, NVIDIA, Google, and Amazon. This creates a confusing web of reciprocal deals for capital and cloud compute, blurring traditional competitive lines and creating complex interdependencies.
NVIDIA's multi-billion dollar deals with AI labs like OpenAI and Anthropic are framed not just as financial investments, but as a form of R&D. By securing deep partnerships, NVIDIA gains invaluable proximity to its most advanced customers, allowing it to understand their future technological needs and ensure its hardware roadmap remains perfectly aligned with the industry's cutting edge.
Major AI labs aren't just evaluating Google's TPUs for technical merit; they are using the mere threat of adopting a viable alternative to extract significant concessions from Nvidia. This strategic leverage forces Nvidia to offer better pricing, priority access, or other favorable terms to maintain its market dominance.
Major AI labs like OpenAI and Anthropic are partnering with competing cloud and chip providers (Amazon, Google, Microsoft). This creates a complex web of alliances where rivals become partners, spreading risk and ensuring access to the best available technology, regardless of primary corporate allegiances.
Anthropic’s cloud partnerships, like its one with Amazon, are structured as a 50% gross profit share, meaning costs like inference are deducted before sharing. This contrasts sharply with OpenAI's simpler 20% total revenue share with Microsoft, revealing different economic models for AI platform distribution.
The deal isn't just about cloud credits; it's a strategic play to onboard OpenAI as a major customer for Amazon's proprietary Tranium AI chips. This helps Amazon compete with Nvidia by subsidizing a top AI lab to adopt and validate its hardware.
OpenAI’s pivotal partnership with Microsoft was driven more by the need for massive-scale cloud computing than just cash. To train its ambitious GPT models, OpenAI required infrastructure it could not build itself. Microsoft Azure provided this essential, non-commoditized resource, making them a perfect strategic partner beyond their balance sheet.
