An artificial intelligence model pool groups models that meet the requirements for a task. A coding pool, for example, may contain models with suitable code quality, tool use and context limits, while a fast classification pool may use smaller models.
A router selects among eligible models in the pool using ranking, latency, cost or availability rules. Pool membership should be versioned and reevaluated because model behavior, pricing and service reliability can change.
Acronyms and aliases
model candidate pool synonymAI model pool variantartificial intelligence model pool variant
Related terms
Frequently asked questions
Why create task-specific model pools?
They prevent unsuitable models from receiving a request and let the router compare only candidates that meet task requirements.
Can one model belong to several pools?
Yes. A model can be eligible for multiple task types when it satisfies the capability and operating constraints of each pool.
