Stripe Doubles Down on AI With OpenRouter Deal

Stripe is in talks to buy OpenRouter, an artificial intelligence startup. The deal could value the company at roughly $10 billion, The Wall Street Journal reported. An agreement could be announced soon. Still, talks could fall through, or another buyer could step in. The exact price has not been confirmed.

OpenRouter was valued at $1.3 billion in May. That came after a $113 million funding round led by CapitalG, Google’s venture capital arm. A $10 billion sale, by comparison, would value OpenRouter at nearly eight times that figure. And that jump would come in under three months.

That jump underscores how quickly OpenRouter has grown. It also shows how central the company has become to how businesses deploy AI. So, understanding the potential deal starts with understanding what OpenRouter actually does.

What OpenRouter Does

OpenRouter does not build AI models. Instead, it decides which one should answer each request. The platform gives developers a single connection point. From there, they can reach more than 400 AI models from over 60 companies, including OpenAI, Anthropic, Google, Meta and DeepSeek. As a result, a company can switch AI models without rebuilding its software each time.

OpenRouter now handles an estimated 1.5 quadrillion “tokens” a year. Tokens are the units AI systems use to process text. More than 8 million developers use the platform, according to Menlo Ventures, one of its investors. Menlo estimates that volume equals 15% to 30% of Google’s total token traffic. It also equals 20% to 40% of OpenAI’s traffic, and more than half of Microsoft’s Azure AI Foundry service.

OpenRouter’s business model has helped fuel that growth. It does not sell access to any AI model of its own. It does not charge more than the underlying AI companies already charge, either. So, a developer using OpenRouter pays the same price they would pay by going straight to OpenAI or Anthropic, according to OpenRouter’s own pricing documentation.

Instead, OpenRouter makes money from a small fee. It charges that fee when developers add funds to their account. That business, Sacra estimates, reached $50 million in yearly revenue by March. That is up from about $19 million at the end of 2025. It is growing quickly, too, as more companies build on multiple AI models rather than committing to just one.

OpenRouter and Stripe already work together closely. Stripe announced last year that OpenRouter uses several of Stripe’s tools. These include Stripe Invoicing, which bills its customers around the world. They also include Stripe Tax, which calculates and collects taxes across different countries. And they include Stripe’s fraud detection tool, which manages risk.

OpenRouter also uses Stripe to accept payments, including credit cards and regional payment methods like Alipay and Google Pay. Altogether, then, Stripe already runs a significant share of OpenRouter’s financial operations behind the scenes. That overlap makes a full acquisition look like a natural next step.

OpenRouter Picks the Model. Metronome Sends the Invoice.

This would be Stripe’s second AI-related purchase in less than a year. In January, Stripe completed its acquisition of Metronome. Metronome is a company built around tracking usage in real time. Think of things like an API call, a chunk of computing time or a set of tokens processed. It then turns that usage into a bill right away, rather than waiting to calculate costs later.

Metronome’s customers before the purchase included OpenAI, Anthropic and Nvidia. All three are companies that need to bill customers for usage that can change from one second to the next.

Metronome and OpenRouter solve two different parts of the same problem, in a specific order. Metronome answers how much the request costs, and how it should be billed. These questions, though, only come up after the request has already gone to a specific AI model. OpenRouter, meanwhile, answers an earlier question: Which model should handle the request in the first place? That decision comes down to price, speed and quality. In short, one system measures what already happened. The other decides what happens next.

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