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We ran 1,730 visual reasoning questions across 5 models. Dropping image detail to "low" costs real accuracy, and on gpt-5.5 the bill went up too. The lever that reliably cuts cost is reasoning effort.
What RADAR observed and classified to build this opportunity. It is what the source published, not a verification that the offer is still active.
Choosing the Optimal Image Input Detail Level in LLMs. We ran 1,730 visual reasoning questions across 5 models. Dropping image detail to "low" costs real accuracy, and on gpt-5.5 the bill went up too. The lever that reliably cuts cost is reasoning effort.
Open sourceThe catalog shows persisted RADAR opportunities. Storage availability does not mean sources are verified or offers are active.