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Official Source· OpenAI· Published Oct 7, 2026

OpenAI DevDay 2026 session focuses on AI costs, from per-task measurement to caching and batch APIs

Published October 7, OpenAI’s DevDay 2026 session “Stop Overpaying for Intelligence” covers measuring cost per completed task, choosing models and reasoning effort, and using prompt caching, Programmatic Tool Calling, and the Batch API.

Full Report

OpenAI published “Stop Overpaying for Intelligence,” a DevDay 2026 session, on October 7. The session focuses on lowering AI costs while preserving quality, including measuring cost per completed task and choosing models and reasoning effort.

The listed cost-management topics include prompt caching, Programmatic Tool Calling, and the Batch API. The session description connects spending to model selection, tool use, and request processing, but does not give specific savings figures or explain when each method applies.

The discussion follows an earlier OpenAI update on prompt caching. On September 22, the company described improved caching for GPT-6, saying eligible shared prefixes could be reused within a 30-minute window and cached input tokens could receive discounts of up to 90%.

Why This Matters

Measuring cost per completed task links spending to whether a task is actually finished, rather than looking only at individual API calls or token use. The session also groups model choice, reasoning effort, and three cost-management methods as areas for developers to consider; the results will depend on the workflow.

Evidence

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Primary Evidence

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  • OfficialOpenAIOfficial videoOriginal

    Stop Overpaying for Intelligence | DevDay 2026

    OpenAI

    “Cut AI costs while preserving quality. Learn to measure cost per completed task, choose models and reasoning effort, and use prompt caching, Programmatic Tool Calling, and the Batch API.”

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