When a cheap model stumbles on a hard task, the reflex is to jump to the frontier tier. Often the cheaper move is to keep the small model and turn its reasoning effort up โ its per-token rate is so low it can brute-reason through the problem and still cost far less.
Buy More Reasoning on the Cheap Model Before You Upgrade the Tier
Unlock this tip โ and 105 more
This is one of 106 advanced, fact-checked tactics reserved for Pro. Get the full 128-tip library, a searchable archive, and a new tip every morning. Free for 7 days, then $9/mo.
Prefer to browse? The 22 Beginner tips are free forever.
More in Model Selection
Stop Paying Frontier Prices for Boilerplate Work
Most of your token spend is on tasks a small model handles perfectly. Match the model to the job instead of defaulting to your most expensive option for everything.
Cascade: Try the Cheap Model First, Escalate Only When It Fails
Send every request to a small model first, programmatically check the answer, and only escalate to a frontier model when the cheap one falls short.
Set service_tier flex for Batch Prices on the Sync Endpoint
Add a single parameter to your OpenAI Responses or Chat Completions calls to pay Batch-API rates without restructuring anything into async batch jobs. You keep a normal synchronous request/response flow and give up only guaranteed speed.