What is ai models?
AI model selection is the process of choosing a model and endpoint that meet a task's quality, feature, latency, and operating requirements. Compare actual application behavior before using price as the deciding factor.
o10Reviewed 2026-09-06
AI model selection: capabilities, constraints and evidence
AI model selection is the process of choosing a model and endpoint that meet a task's quality, feature, latency, and operating requirements. Compare actual application behavior before using price as the deciding factor.
SummaryKey takeaways
What you need to know
Start with the core questions, then examine the examples and tradeoffs below.
01Deep dive
Filter by required capabilities
Identify the input and output types, tool interface, structured-output requirements, context size, and operating constraints of the task. A model that cannot support a required capability is not a cheaper substitute.
The same model name can appear behind different endpoints with different feature support, quotas, retention terms, and pricing. Keep the provider, endpoint, and version in the comparison record.
02Deep dive
Evaluate on your task distribution
Use examples representative of real inputs and material errors. Test the complete prompt and surrounding application, including retrieval and tools where applicable. Separate development examples from held-out release checks.
Benchmark rankings help identify candidates; they are not a guarantee for a different language, domain, toolset, or error tolerance. Inspect individual failures and avoid hiding rare but expensive mistakes in an average score.
03Deep dive
Compare complete operating cost
Measure cost per accepted result, latency, retries, and manual correction. For self-hosted models, account for utilization, spare capacity, and operations. For an API, verify the endpoint's billing dimensions and eligibility for discounts.
The o10 catalog is a dated reference, not proof of model availability or quality. A missing value means the snapshot lacks that information; it must not be read as a zero price or an unlimited context window.
SourceMethodology
Cost examples are illustrative. Measure quality and total costs on your own tasks, and check current endpoint terms before implementation.
FAQFrequently asked questions
Common questions
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See what you're overpaying →verified savings methodology · State of Inference Spend 2026