Workflow · saas · workflow
OpenRouter: Founding story and architecture of a multi-model AI inference marketplace
The AI inference ecosystem grew into a fragmented, heterogeneous landscape of providers with incompatible features—different samplers, caching support, tool calling, and pricing—making it difficult for developers to choose, compare, or switch between models.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Developer API request
A developer submits a request through a single API to access any language model.
Tools used
Window AI
Outcome
OpenRouter became a marketplace aggregating over 400 models and over 60 active providers, growing 10 to a hundred percent month over month for the last two years, and achieving about 30 milliseconds latency, while its data supports the conclusion that AI inference is not winner-take-all.
Results
Time saved10 to a hundred percent month over month for the last two years
Volumeover 400 models
Grounding & classification
Source type: technical build writeup
18 fields verified against source quotes, 1 dropped as unverifiable.
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