Stripe has agreed to acquire OpenRouter, an AI model-routing platform that gives developers access to hundreds of models through a single interface. The deal adds model selection and routing to Stripe’s existing work around AI usage and token-based billing.
OpenRouter supports more than 400 models from over 80 providers, according to Stripe. Rather than requiring separate integrations with each model provider, developers can use OpenRouter to send requests through one API.
The platform evaluates requests using factors including task complexity, price, speed, and reliability. It can then direct each request to a model suited to those requirements.
OpenRouter also handles a second layer of routing between providers serving the same model. Its documentation says customers can prioritise endpoints based on price, throughput, or latency, while setting requirements such as maximum prices or minimum performance levels.
The platform measures latency and throughput for individual model-provider combinations using rolling performance data. This allows a request to be routed to an endpoint that meets specified cost or performance criteria rather than relying on a fixed provider.
That separates two routing decisions: which model handles a request and which provider endpoint serves it.
Provider choice can also affect inference costs even when the underlying model remains the same. In a June 2026 example, OpenRouter listed Llama 3.3 70B input pricing at $0.10 per million tokens through DeepInfra and $1.04 through Together, while output pricing ranged from $0.32 to $1.04 per million tokens across the providers shown.
Routing can provide failover when an endpoint becomes unavailable. OpenRouter says its system can move requests to alternative providers or models when it encounters problems including provider outages, rate limits, context-length errors, or moderation refusals.
Data-handling requirements can also form part of provider selection. OpenRouter lets users restrict requests to Zero Data Retention endpoints and prevent routing to providers that collect data or train on prompts, while enterprise customers can request in-region processing in the US or EU.
Routing criteria can therefore include model capability, provider availability, processing location, latency, throughput, and cost.
Multi-model environments are already common among surveyed organisations. F5’s 2026 State of Application Strategy report, based on responses from more than 1,100 IT decision-makers, found that 52% of organisations were chaining or orchestrating multiple AI models, with respondents using an average of seven models.
Menlo Ventures, an OpenRouter investor, reported a different measure of provider behaviour in its 2025 mid-year survey. It found that 66% of builders upgraded models while staying with their existing provider, while 11% switched vendors.