Tag
A developer discusses the high cost of agentic workflows due to treating all inference as realtime, and asks the community for frameworks or patterns that support batch API natively to reduce costs.
A practical guide listing 10 strategies to reduce costs when using LLM APIs, including model selection, prompt caching, batch processing, and monitoring expenses.
A roundtable at OpenAI DevDay 2026 discusses how to optimize AI costs: the key metric should be "cost per task" rather than cost per token, with ongoing iteration and evaluation driven by four levers — model selection (Astra 6, Sol 6.1, Luna), prompt caching, programmatic tool calls, reasoning effort, and the Batch/Flex APIs.