Glossary
Model routing
In short
Sending each task, or each part of a task, to the model best suited for it, rather than using one model for everything.
Different models have different strengths and prices. Routing means matching the work to the model: a cheap, fast model for routine steps, a strong reasoning model for the hard part, a model with a long context window for big documents.
Done well, routing gets you most of the quality of the best model at a fraction of the cost, because you are not paying premium rates for work that a smaller model handles fine.
In LLMWeave
Inside a weave, work is matched to the right model rather than forced through a single one. Cheaper models handle the routine passes, and stronger models are reserved for the steps that actually need them.
Related terms
Multi-model AI
Using more than one AI model on the same task, instead of relying on a single model for every answer.
Reasoning model
A model built to work through problems step by step before answering, rather than responding in a single pass.
LLM orchestration
Coordinating one or more large language models, and the steps around them, to complete a task that a single prompt would not handle well on its own.
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