OpenAI launches Flex API to cut costs for low-priority AI tasks

OpenAI has launched Flex processing, a new API option designed to reduce costs for users by offering lower prices in exchange for slower response times and occasional resource unavailability.

Flex is in beta and available for o3 and o4-mini models, targeting low-priority tasks like data enrichment and async work.

Prices for Flex are half the standard rates, with o3 now costing US$5 per million input tokens and US$20 per million output tokens.

For the o4-mini model, costs drop to US$0.55 per million input tokens and US$2.20 per million output tokens, compared to previous rates of US$1.10 and US$4.40.

The launch comes as rivals like Google push cheaper AI models, such as Gemini 2.5 Flash, into the market.

🔗 Source: TechCrunch

🧠 Food for thought

1️⃣ AI pricing undergoes strategic shift toward flexible consumption models

OpenAI’s introduction of “Flex processing” at exactly half the price of standard options represents a significant evolution in AI pricing strategies that aligns with broader industry trends.

This new tier with explicitly slower performance and “occasional resource unavailability” creates a pricing dynamic similar to what transformed cloud computing, where customers can choose between premium (on-demand) and economy (spot/reserved) options based on workload priorities.

The approach makes economic sense for both parties: OpenAI can better optimize its compute resources by routing non-time-sensitive workloads to periods of lower demand, while cost-sensitive developers gain access to powerful models at substantially reduced rates.

This pricing innovation comes amid intensifying competition, with Google’s simultaneous release of Gemini 2.5 Flash positioned as a more affordable alternative that “matches or bests DeepSeek’s R1 in performance at a lower input token cost.”

The industry appears to be moving toward more sophisticated, usage-based pricing structures that align with what pricing experts recommend, considering “complexity, user value, and market demand” when developing AI monetization strategies 1.

2️⃣ Identity verification emerges as critical frontier in responsible AI deployment

OpenAI’s new requirement for ID verification for higher-tier API users signals an important shift in how AI companies are approaching governance and security concerns.

This verification requirement, which OpenAI states is designed to “stop bad actors from violating its usage policies,” arrives during a period of growing concern about AI-enabled fraud and misuse.