Glossary
Reasoning model
In short
A model built to work through problems step by step before answering, rather than responding in a single pass.
Standard models answer in one shot. Reasoning models spend extra effort working through a problem, which helps on tasks like math, logic, and complex coding where a careless first answer is often wrong.
That deliberation costs more time and money, so it is worth reaching for on hard problems and skipping on simple ones.
In LLMWeave
A weave can include reasoning models for the hard part of a task and lean on faster models elsewhere, so you pay for deep thinking only where it earns its keep.
Related terms
Model routing
Sending each task, or each part of a task, to the model best suited for it, rather than using one model for everything.
Multi-agent debate
Having models argue different positions on a question, then settle on a conclusion, so the reasoning is tested rather than taken at face value.
Multi-model AI
Using more than one AI model on the same task, instead of relying on a single model for every answer.
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