Stripe、AI モデルルーティングの OpenRouter を買収へ

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.

Routing beyond model choice

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 infrastructure expands

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.

OpenRouter is also one of several infrastructure providers adding model routing. Snowflake announced dynamic model routing for Cortex AI Gateway on August 18, with the feature expected to enter private preview.

Snowflake said the system will assign requests according to factors including quality, speed, customer preferences, and cost. Cloudflare offers Dynamic Routing in beta through AI Gateway, with rules covering model selection, quotas, and fallbacks.

AWS provides Intelligent Prompt Routing through Bedrock, while Microsoft Foundry offers routing profiles that balance model quality and price. AWS and Snowflake both describe systems that can direct less demanding workloads to smaller or lower-cost models while reserving other models for tasks requiring higher response quality or more complex reasoning.

Routing also adds operational requirements. Microsoft’s Azure Architecture Center notes that dynamic model selection can complicate cost forecasting, debugging, and performance analysis when different requests are handled by different models.

Stripe and OpenRouter were already working together before the acquisition. In January 2026, Stripe said developers using OpenRouter could route model requests through the platform while Stripe tracked usage, applied pricing, and handled billing.

The arrangement paired OpenRouter’s routing layer with Stripe’s usage measurement and billing systems before the acquisition agreement.

Token usage meets billing

Stripe has also been developing token-based billing tools for AI applications. Its LLM token-billing service, which Stripe currently lists as being in private preview, can meter consumption according to model and token type, including input, output, and cached tokens where supported.

Stripe’s documentation says businesses can use the system for per-token pricing, prepaid credits, fixed fees with included usage, or combinations of those approaches. The company can also update supported model prices when providers change their underlying pricing.

OpenRouter already produces much of the usage data involved in those billing calculations. Its API reports prompt, completion, reasoning, and cached token counts with individual responses, along with the cost of the request.

It also records the underlying inference cost charged by the provider separately from the amount charged to an OpenRouter account. Token counts are calculated using each model’s native tokeniser rather than applying a single counting method across all models.

Stripe CEO Patrick Collison has linked the acquisition to the role of tokens and computing resources in AI applications. Collison said tokens are a central unit for companies building with AI and tied their economic use to how companies manage available computing resources.

Enterprise token consumption is already reaching large volumes. Deloitte surveyed 515 US-based business and technology decision-makers in late 2025, all from organisations generating at least $500 million in annual revenue.

The survey found that 37% of respondents were consuming between one billion and 10 billion AI tokens per month, while another 30% were consuming more than 10 billion. By 2028, 61% expect monthly consumption to exceed 10 billion tokens.

Deloitte said much of the increase would come from workloads exceeding 100 billion tokens per month, with token use in that range expected to triple from 2026 to 2028.

The firm cautioned that higher token consumption does not necessarily indicate more effective AI adoption. Deloitte identified oversized prompts, weak context management, and limited reuse as factors that can increase token consumption.

The cost of processing those tokens can also differ by model and, in some cases, by the provider serving the same model.

OpenRouter says it processes more than 10 trillion tokens per day across a community of more than 10 million developers and companies. Earlier figures published by OpenRouter provide some indication of how its traffic had changed before the acquisition.

In May, the company said its weekly volume had increased from five trillion to 25 trillion tokens over the previous six months. At the time, OpenRouter reported serving more than eight million developers across more than 400 models.

OpenRouter was founded in 2023 and has raised funding from investors including Menlo Ventures and Andreessen Horowitz. Its $113 million Series B round in May was led by CapitalG, Alphabet’s independent growth fund, with participation from investors including NVentures, ServiceNow Ventures, MongoDB Ventures, Snowflake Ventures, and Databricks Ventures.

Stripe and OpenRouter did not disclose the financial terms of the acquisition. Reuters reported that the transaction is worth slightly more than $8 billion, citing a person familiar with the matter who requested anonymity because the information was confidential.

(Photo by appshunter.io)

See also: OpenAI president urges enterprises to hasten AI security defences

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