OpenRouter routes requests to the best available providers for your model, given your preferences. By default, requests are load balanced across the top providers to maximize uptime.
Load Balancing
For each model in your request, OpenRouter’s default behavior is to load balance requests across providers with the following strategy:
Prioritize providers that have not seen significant outages in the last 10 seconds.
For the stable providers, look at the lowest-cost candidates and select one weighted by price.
Use the remaining providers as fallbacks.
Here’s an example. Let’s say Provider A is $1/million tokens, Provider B is $2/million, and Provider C is $3/million. Provider B recently saw a few outages.
Your request is 3x more likely to be first routed to Provider A than Provider C.
If Provider A is tried first and fails, then Provider C will be tried next.
If both providers fail, Provider B will be tried last.
OpenRouter is an API that can be used with most AI SDKs, and has a very similar format to OpenAI’s own API.
Change the model you want to use by configuring Models in the Processor . You can use models from OpenAI, Anthropic, Google, and more. See the OpenRouter docs for all the options.
Oh, really interesting node! As I understand, you can switch the neural network that’s performing the task at any time. A unified API for all LLMs can be very useful. The main thing is for the prices not to be too high.
